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- data/sampled_jsons/'Grassmannian_cluster_algebra_dataset'_Table_10_Machine_Learning_meets_Algebraic_Combinatorics_year_2024.jsonl +10 -0
- data/sampled_jsons/'Machine_Learning_meets_Algebraic_Combinatorics'_'S18_characters_dataset'_'symmetric_group'_Appendix.jsonl +10 -0
- data/sampled_jsons/0C3bLHwjsY_Promoting_Fairness_Among_Dynamic_Agents_in_Online-Matching_Markets_under_Known_Stationary.jsonl +10 -0
- data/sampled_jsons/100000_148658_S18_Grassmannian_cluster_algebra_characters_dataset.jsonl +10 -0
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- data/sampled_jsons/Balke_Pearl_1994_probabilistic_evaluation_counterfactual_queries_abstract.jsonl +10 -0
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data/sampled_jsons/'Grassmannian_cluster_algebra_dataset'_Table_10_Machine_Learning_meets_Algebraic_Combinatorics_year_2024.jsonl
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{"idx": 0, "title": "Machine Learning meets Algebraic Combinatorics : A Suite of...", "date": "", "ddg_snippet": "Among the many algebraic - combinatorial properties of Grassmannians is an algebraic structure on its coordinate ring making it something called a cluster algebra (Williams, 2014) . Table 10 : Statistics of the Grassmannian cluster algebra dataset .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.06366v1", "content": "Among the many algebraic - combinatorial properties of Grassmannians is an algebraic structure on its coordinate ring making it something called a cluster algebra (Williams, 2014) . Table 10 : Statistics of the Grassmannian cluster algebra dataset ."}
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{"idx": 1, "title": "Machine Learning meets Algebraic Combinatorics : A", "date": "", "ddg_snippet": "Model Performance. Baseline hyperparameters. Machine Learning meets Algebraic Combinatorics : A Suite of Datasets to Accelerate AI for Mathematics Research.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=KQ1gI5qzAf", "content": "Model Performance. Baseline hyperparameters. Machine Learning meets Algebraic Combinatorics : A Suite of Datasets to Accelerate AI for Mathematics Research."}
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{"idx": 2, "title": "Clustering cluster algebras with clusters | Request PDF", "date": "", "ddg_snippet": "The Grassmannian cluster algebra .This computational algebra paradigm generates a dataset that can then be mined using techniques from data science such as supervised and unsupervised machine learning .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/381241767_Clustering_cluster_algebras_with_clusters", "content": "The Grassmannian cluster algebra .This computational algebra paradigm generates a dataset that can then be mined using techniques from data science such as supervised and unsupervised machine learning ."}
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{"idx": 3, "title": "Twists of $\\mathrm{Gr}(3, n)$ Cluster Variables as Double and Triple...", "date": "", "ddg_snippet": "ALGEBRAIC COMBINATORICS .We give a combinatorial interpretation for certain cluster variables in Grassmannian cluster algebras in terms of double and triple dimer configurations. More specifically, we examine several. Gr(3,n).", "subpage_snippet": "", "source": "alco.centre-mersenne.org", "link": "https://alco.centre-mersenne.org/articles/10.5802/alco.376/", "content": "ALGEBRAIC COMBINATORICS .We give a combinatorial interpretation for certain cluster variables in Grassmannian cluster algebras in terms of double and triple dimer configurations. More specifically, we examine several. Gr(3,n)."}
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{"idx": 4, "title": "Grassmannians and Cluster Structures | Bulletin of the Iranian...", "date": "", "ddg_snippet": "Cluster structures have been established on numerous algebraic varieties. These lectures focus on the Grassmannian variety and explain the cluster structures on it. The tools include dimer models on surfaces, associated algebras , and the study of associated module categories.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s41980-021-00542-6", "content": "Cluster structures have been established on numerous algebraic varieties. These lectures focus on the Grassmannian variety and explain the cluster structures on it. The tools include dimer models on surfaces, associated algebras , and the study of associated module categories."}
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{"idx": 5, "title": "Machine Learning meets Algebraic Combinatorics : A Suite... | PNNL", "date": "", "ddg_snippet": "The use of benchmark datasets has become an important engine of progress in machine learning (ML) over the past 15 years. Recently there has been growing interest in utilizing machine learning to drive advances in research-level mathematics.", "subpage_snippet": "", "source": "www.pnnl.gov", "link": "https://www.pnnl.gov/publications/machine-learning-meets-algebraic-combinatorics-suite-benchmark-datasets-accelerate-ai", "content": "The use of benchmark datasets has become an important engine of progress in machine learning (ML) over the past 15 years. Recently there has been growing interest in utilizing machine learning to drive advances in research-level mathematics."}
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{"idx": 6, "title": "ag. algebraic geometry - Combinatorics of the... - MathOverflow", "date": "", "ddg_snippet": "Combinatorics of the Cohomology Ring of the Lagrangian Grassmannians .As is well-known, the cohomology ring of the Grassmannians has a very nice combinatorial description in terms of partitions, see this very nice M.O. answer for example.", "subpage_snippet": "", "source": "mathoverflow.net", "link": "https://mathoverflow.net/questions/261903/combinatorics-of-the-cohomology-ring-of-the-lagrangian-grassmannians", "content": "Combinatorics of the Cohomology Ring of the Lagrangian Grassmannians .As is well-known, the cohomology ring of the Grassmannians has a very nice combinatorial description in terms of partitions, see this very nice M.O. answer for example."}
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{"idx": 7, "title": "Free Video: Combinatorics of the Amplituhedron from... | Class Central", "date": "", "ddg_snippet": "Explore the amplituhedron's connections to cluster algebras , matroids, and combinatorics in this gentle introduction by Lauren Williams from Harvard University.", "subpage_snippet": "", "source": "www.classcentral.com", "link": "https://www.classcentral.com/course/youtube-lauren-williams-combinatorics-of-the-amplituhedron-319071", "content": "Explore the amplituhedron's connections to cluster algebras , matroids, and combinatorics in this gentle introduction by Lauren Williams from Harvard University."}
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{"idx": 8, "title": "A categorification of Grassmannian cluster algebras - the University...", "date": "", "ddg_snippet": "Jensen BT , King AD , Su X . A categorification of Grassmannian cluster algebras . Proceedings of the London Mathematical Society . 2016 Aug 2;113(2):185-212.", "subpage_snippet": "", "source": "researchportal.bath.ac.uk", "link": "https://researchportal.bath.ac.uk/en/publications/a-categorification-of-grassmannian-cluster-algebras", "content": "Jensen BT , King AD , Su X . A categorification of Grassmannian cluster algebras . Proceedings of the London Mathematical Society . 2016 Aug 2;113(2):185-212."}
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{"idx": 9, "title": "UNAM Oaxaca - Cited by 254 - Grassmannians - toric degenerations...", "date": "", "ddg_snippet": "Combinatorial Algebraic Geometry: Selected Papers From the 2016 …, 2017.2020. Families of Gröbner degenerations, Grassmannians and universal cluster algebras .", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=husFyf8AAAAJ&hl=en", "content": "Combinatorial Algebraic Geometry: Selected Papers From the 2016 …, 2017.2020. Families of Gröbner degenerations, Grassmannians and universal cluster algebras ."}
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data/sampled_jsons/'Machine_Learning_meets_Algebraic_Combinatorics'_'S18_characters_dataset'_'symmetric_group'_Appendix.jsonl
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{"idx": 0, "title": "Machine - Wikipedia", "date": "", "ddg_snippet": "A machine is a thermodynamic system that uses power to apply forces and control movement to perform an action. The term is commonly applied to artificial devices, such as those employing engines or motors, but also to natural biological macromolecules, such as molecular machines .", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Machine", "content": "A machine is a thermodynamic system that uses power to apply forces and control movement to perform an action. The term is commonly applied to artificial devices, such as those employing engines or motors, but also to natural biological macromolecules, such as molecular machines ."}
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{"idx": 1, "title": "MACHINE Definition & Meaning | Dictionary .com", "date": "", "ddg_snippet": "Machine definition: an apparatus consisting of interrelated parts with separate functions, used in the performance of some kind of work.. See examples of MACHINE used in a sentence.", "subpage_snippet": "", "source": "www.dictionary.com", "link": "https://www.dictionary.com/browse/machine", "content": "Machine definition: an apparatus consisting of interrelated parts with separate functions, used in the performance of some kind of work.. See examples of MACHINE used in a sentence."}
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{"idx": 2, "title": "MACHINE Definition & Meaning - Merriam-Webster", "date": "", "ddg_snippet": "The meaning of MACHINE is a mechanically, electrically, or electronically operated device for performing a task. How to use machine in a sentence.", "subpage_snippet": "", "source": "www.merriam-webster.com", "link": "https://www.merriam-webster.com/dictionary/machine", "content": "The meaning of MACHINE is a mechanically, electrically, or electronically operated device for performing a task. How to use machine in a sentence."}
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{"idx": 3, "title": "Machine | Definition, Mechanisms & Efficiency | Britannica", "date": "", "ddg_snippet": "machine , device, having a unique purpose, that augments or replaces human or animal effort for the accomplishment of physical tasks.", "subpage_snippet": "", "source": "www.britannica.com", "link": "https://www.britannica.com/technology/machine", "content": "machine , device, having a unique purpose, that augments or replaces human or animal effort for the accomplishment of physical tasks."}
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{"idx": 4, "title": "MACHINE | English meaning - Cambridge Dictionary", "date": "", "ddg_snippet": "MACHINE definition: 1. a piece of equipment with several moving parts that uses power to do a particular type of work…. Learn more.", "subpage_snippet": "", "source": "dictionary.cambridge.org", "link": "https://dictionary.cambridge.org/dictionary/english/machine", "content": "MACHINE definition: 1. a piece of equipment with several moving parts that uses power to do a particular type of work…. Learn more."}
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{"idx": 5, "title": "machine , n. meanings, etymology and more | Oxford English...", "date": "", "ddg_snippet": "machine , n. meanings, etymology, pronunciation and more in the Oxford English Dictionary", "subpage_snippet": "", "source": "www.oed.com", "link": "https://www.oed.com/dictionary/machine_n", "content": "machine , n. meanings, etymology, pronunciation and more in the Oxford English Dictionary"}
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{"idx": 6, "title": "What Is A Machine ? Its Types and How it Works - Mech Lesson", "date": "", "ddg_snippet": "A machine is a mechanical device that uses power to apply force and control motion to perform work efficiently . Machines range from simple tools like pulleys and levers to complex systems like engines, robots, and manufacturing equipment.", "subpage_snippet": "", "source": "mechlesson.com", "link": "https://mechlesson.com/machine/", "content": "A machine is a mechanical device that uses power to apply force and control motion to perform work efficiently . Machines range from simple tools like pulleys and levers to complex systems like engines, robots, and manufacturing equipment."}
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{"idx": 7, "title": "machine - Wiktionary, the free dictionary", "date": "", "ddg_snippet": "2 days ago · (figuratively) A person or organisation that seemingly acts like a machine , being particularly efficient, single-minded, or unemotional. Bruce Campbell was a \"demon-killing machine \" because he made quick work of killing demons. The government has become a money-making machine .", "subpage_snippet": "", "source": "en.wiktionary.org", "link": "https://en.wiktionary.org/wiki/machine", "content": "2 days ago · (figuratively) A person or organisation that seemingly acts like a machine , being particularly efficient, single-minded, or unemotional. Bruce Campbell was a \"demon-killing machine \" because he made quick work of killing demons. The government has become a money-making machine ."}
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{"idx": 8, "title": "Machine - definition of machine by The Free Dictionary", "date": "", "ddg_snippet": "Of, relating to, or felt to resemble a machine : machine repairs; machine politics.", "subpage_snippet": "", "source": "www.thefreedictionary.com", "link": "https://www.thefreedictionary.com/machine", "content": "Of, relating to, or felt to resemble a machine : machine repairs; machine politics."}
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{"idx": 9, "title": "The Smashing Machine | Official Trailer HD | A24 - YouTube", "date": "", "ddg_snippet": "Special Blu-ray & 4K editions of Danny & Michael Philippou's sinister tale of domestic and occult horror. Special features include a commentary with the directors, one deleted scene, and an...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=aRpnP3LZ99g", "content": "Special Blu-ray & 4K editions of Danny & Michael Philippou's sinister tale of domestic and occult horror. Special features include a commentary with the directors, one deleted scene, and an..."}
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data/sampled_jsons/0C3bLHwjsY_Promoting_Fairness_Among_Dynamic_Agents_in_Online-Matching_Markets_under_Known_Stationary.jsonl
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{"idx": 0, "title": "Promoting Fairness Among Dynamic Agents in Online-Matching Markets ...", "date": "", "ddg_snippet": "Online (bipartite) matching under known stationary arrivals is a fundamental model that has been studied extensively under the objective of maximizing the total number of customers served. We instead study the objective of *maximizing the minimum matching rate across all online types*, which is referred to as long-run (individual) fairness .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=0C3bLHwjsY", "content": "Online (bipartite) matching under known stationary arrivals is a fundamental model that has been studied extensively under the objective of maximizing the total number of customers served. We instead study the objective of *maximizing the minimum matching rate across all online types*, which is referred to as long-run (individual) fairness ."}
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{"idx": 1, "title": "NeurIPS Poster Promoting Fairness Among Dynamic Agents in Online ...", "date": "", "ddg_snippet": "Poster Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions Will Ma · Pan Xu", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/poster/96945", "content": "Poster Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions Will Ma · Pan Xu"}
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{"idx": 2, "title": "Fairness Maximization among Offline Agents in Online-Matching Markets", "date": "", "ddg_snippet": "In this paper, we propose online matching algorithms which optimize for either individual or group-level fairness among offline agents in OMMs. We present two linear-programming (LP) based sampling algorithms, which achieve online competitive ratios at least 0.725 for individual fairness maximization (IFM) and 0.719 for group fairness ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2109.08934", "content": "In this paper, we propose online matching algorithms which optimize for either individual or group-level fairness among offline agents in OMMs. We present two linear-programming (LP) based sampling algorithms, which achieve online competitive ratios at least 0.725 for individual fairness maximization (IFM) and 0.719 for group fairness ..."}
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{"idx": 3, "title": "Fairness Maximization among Offline Agents in Online-Matching Markets", "date": "", "ddg_snippet": "We study the prototypical online matching model with known , independent, and identical (KIID) arrivals , which is widely used to model the dynamic arrivals of online agents in several real-world OMMs including rideshare and crowdsourcing markets [14, 18, 54].", "subpage_snippet": "", "source": "par.nsf.gov", "link": "https://par.nsf.gov/servlets/purl/10420152", "content": "We study the prototypical online matching model with known , independent, and identical (KIID) arrivals , which is widely used to model the dynamic arrivals of online agents in several real-world OMMs including rideshare and crowdsourcing markets [14, 18, 54]."}
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{"idx": 4, "title": "Fairness · NeurIPS 2024", "date": "", "ddg_snippet": "Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions 26 September 2024·1572 words·8 mins·loading·loading", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/tags/fairness/", "content": "Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions 26 September 2024·1572 words·8 mins·loading·loading"}
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{"idx": 5, "title": "Class Fairness in Online Matching | Proceedings of the AAAI Conference ...", "date": "", "ddg_snippet": "We initiate the study of fairness among classes of agents in online bipartite matching where there is a given set of offline vertices (aka agents ) and another set of vertices (aka items) that arrive online and must be matched irrevocably upon arrival .", "subpage_snippet": "", "source": "ojs.aaai.org", "link": "https://ojs.aaai.org/index.php/AAAI/article/view/25704", "content": "We initiate the study of fairness among classes of agents in online bipartite matching where there is a given set of offline vertices (aka agents ) and another set of vertices (aka items) that arrive online and must be matched irrevocably upon arrival ."}
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{"idx": 6, "title": "Promoting Fairness Among Dynamic Agents in Online-Matching Markets ...", "date": "", "ddg_snippet": "Authors Will Ma, Pan Xu Abstract Online (bipartite) matching under known stationary arrivals is a fundamental model that has been studied extensively under the objective of maximizing the total number of customers served. We instead study the objective of *maximizing the minimum matching rate across all online types*, which is referred to as long-run (individual) fairness . For Online Matching ...", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper_files/paper/2024/hash/959f70ee50044bed305e48e3484005a7-Abstract-Conference.html", "content": "Authors Will Ma, Pan Xu Abstract Online (bipartite) matching under known stationary arrivals is a fundamental model that has been studied extensively under the objective of maximizing the total number of customers served. We instead study the objective of *maximizing the minimum matching rate across all online types*, which is referred to as long-run (individual) fairness . For Online Matching ..."}
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{"idx": 7, "title": "Promoting Fairness Among Dynamic Agents in Online-Matching Markets ...", "date": "", "ddg_snippet": "Abstract Online (bipartite) matching under known stationary arrivals is a fundamental model that has been studied extensively with the objective of maximizing the total number of customers served. We instead study the objective of maximizing the minimum matching rate across all online types, which is referred to as long-run (individual) fairness .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=0C3bLHwjsY", "content": "Abstract Online (bipartite) matching under known stationary arrivals is a fundamental model that has been studied extensively with the objective of maximizing the total number of customers served. We instead study the objective of maximizing the minimum matching rate across all online types, which is referred to as long-run (individual) fairness ."}
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{"idx": 8, "title": "PDF Promoting Fairness Among Dynamic Agents in", "date": "", "ddg_snippet": "Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions Author Will Ma1 Pan Xu2", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/media/neurips-2024/Slides/96945.pdf", "content": "Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions Author Will Ma1 Pan Xu2"}
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{"idx": 9, "title": "Class Fairness in Online Matching - arXiv.org", "date": "", "ddg_snippet": "We initiate the study of fairness among classes of agents in online bipartite matching . Our first contribution (Section 2) is developing a detailed mathematical framework in which we adopt clas-sical fairness concepts to online matching .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2203.03751", "content": "We initiate the study of fairness among classes of agents in online bipartite matching . Our first contribution (Section 2) is developing a detailed mathematical framework in which we adopt clas-sical fairness concepts to online matching ."}
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data/sampled_jsons/100000_148658_S18_Grassmannian_cluster_algebra_characters_dataset.jsonl
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{"idx": 0, "title": "[1309.7301] A categorification of Grassmannian cluster algebras", "date": "", "ddg_snippet": "View a PDF of the paper titled A categorification of Grassmannian cluster algebras , by Bernt Tore Jensen and 1 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1309.7301", "content": "View a PDF of the paper titled A categorification of Grassmannian cluster algebras , by Bernt Tore Jensen and 1 other authors."}
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+
{"idx": 1, "title": "(PDF) Tropical Grassmannians , cluster algebras and scattering...", "date": "", "ddg_snippet": "Grassmannians to certain cluster algebras , as developed by Fomin and Zelevinsky [6,7]. These same cluster algebras have also arisen in the study of the singularities of loop am-. plitudes in planar N= 4 super Yang-Mills theory [8]. The cluster algebra picture provides.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/340865972_Tropical_Grassmannians_cluster_algebras_and_scattering_amplitudes", "content": "Grassmannians to certain cluster algebras , as developed by Fomin and Zelevinsky [6,7]. These same cluster algebras have also arisen in the study of the singularities of loop am-. plitudes in planar N= 4 super Yang-Mills theory [8]. The cluster algebra picture provides."}
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| 3 |
+
{"idx": 2, "title": "(PDF) Grassmannians and Cluster Algebras", "date": "", "ddg_snippet": "GRASSMANNIANS AND CLUSTER ALGEBRAS arXiv:math/0311148v1 [math.CO] 10 Nov 2003 1. Introduction This paper follows the program of study initiated by S. Fomin and A. Zelevinsky in [2]...", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/99109832/Grassmannians_and_Cluster_Algebras", "content": "GRASSMANNIANS AND CLUSTER ALGEBRAS arXiv:math/0311148v1 [math.CO] 10 Nov 2003 1. Introduction This paper follows the program of study initiated by S. Fomin and A. Zelevinsky in [2]..."}
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| 4 |
+
{"idx": 3, "title": "Grassmannian categories of infinite rank", "date": "", "ddg_snippet": "Grassmannian cluster categories are an additive cat-egorication of Grassmannian cluster algebras , of which this section provides an overview. 2.1.1. The Finite Rank Case.The character group of Gm is the group of integers Z. This yields an equivalence of categories.", "subpage_snippet": "", "source": "pure.au.dk", "link": "https://pure.au.dk/ws/portalfiles/portal/281555143/2007.14224v1.pdf", "content": "Grassmannian cluster categories are an additive cat-egorication of Grassmannian cluster algebras , of which this section provides an overview. 2.1.1. The Finite Rank Case.The character group of Gm is the group of integers Z. This yields an equivalence of categories."}
|
| 5 |
+
{"idx": 4, "title": "Find Open Datasets and Machine Learning Projects | Kaggle", "date": "", "ddg_snippet": "Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More.", "subpage_snippet": "", "source": "www.kaggle.com", "link": "https://www.kaggle.com/datasets", "content": "Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More."}
|
| 6 |
+
{"idx": 5, "title": "ag. algebraic geometry - Zero set of cluster variables - MathOverflow", "date": "", "ddg_snippet": "The broader motivation is to understand how the geometry (e.g., zero loci in the algebraic torus) of cluster characters reflects the representation-theoretic properties of the modules they arise from.", "subpage_snippet": "", "source": "mathoverflow.net", "link": "https://mathoverflow.net/questions/500418/zero-set-of-cluster-variables", "content": "The broader motivation is to understand how the geometry (e.g., zero loci in the algebraic torus) of cluster characters reflects the representation-theoretic properties of the modules they arise from."}
|
| 7 |
+
{"idx": 6, "title": "25w5439: Representation Theory, Symplectic Geometry, and Cluster ...", "date": "", "ddg_snippet": "Matthew Pressland: Mini-course: Cluster categories for Grassmannians and positroid varieties 3 ↓. In this series of talks, I will explain the additive categorification of cluster algebra structures on the Grassmannian and more general positroid varieties.", "subpage_snippet": "", "source": "www.birs.ca", "link": "https://www.birs.ca/events/2025/5-day-workshops/25w5439/schedule", "content": "Matthew Pressland: Mini-course: Cluster categories for Grassmannians and positroid varieties 3 ↓. In this series of talks, I will explain the additive categorification of cluster algebra structures on the Grassmannian and more general positroid varieties."}
|
| 8 |
+
{"idx": 7, "title": "ASCII Table - ASCII Code Chart with Characters", "date": "", "ddg_snippet": "ASCII Table - Complete ASCII code chart with characters . Also, it contains decimal, hexadecimal, binary, and HTML values.", "subpage_snippet": "", "source": "ascii-tables.com", "link": "https://ascii-tables.com/", "content": "ASCII Table - Complete ASCII code chart with characters . Also, it contains decimal, hexadecimal, binary, and HTML values."}
|
| 9 |
+
{"idx": 8, "title": "Нарезки С Мачо Меном Для Эдита | TikTok", "date": "", "ddg_snippet": "TikTok video from ズtop_edits文(др 6 апреля) (@a.n.i.m.e.e.d.i.t.s7): “буду ждать #anime #мачомен #милионпросмотров 100000 лайков”.", "subpage_snippet": "", "source": "www.tiktok.com", "link": "https://www.tiktok.com/discover/нарезки-с-мачо-меном-для-эдита", "content": "TikTok video from ズtop_edits文(др 6 апреля) (@a.n.i.m.e.e.d.i.t.s7): “буду ждать #anime #мачомен #милионпросмотров 100000 лайков”."}
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| 10 |
+
{"idx": 9, "title": "Greg Muller", "date": "", "ddg_snippet": "Cluster algebras of Grassmannians are locally acyclic (arXiv) Joint with David Speyer. Character algebras of decorated SL_2(C)-local systems (arXiv) Joint with Peter Samuelson.", "subpage_snippet": "", "source": "www2.math.ou.edu", "link": "http://www2.math.ou.edu/~gmuller/research.html", "content": "Cluster algebras of Grassmannians are locally acyclic (arXiv) Joint with David Speyer. Character algebras of decorated SL_2(C)-local systems (arXiv) Joint with Peter Samuelson."}
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data/sampled_jsons/1ZC4RNjqzU_Position-_Evaluating_Generative_AI_Systems_Is_a_Social_Science_Measurement_Challenge_Sect.jsonl
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{"idx": 0, "title": "Position : Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "The measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult, leading to what has been described as”a tangle of sloppy tests [and] apples-to-oranges comparisons” (Roose, 2024). In this position paper, we argue that the ML community...", "subpage_snippet": "", "source": "www.microsoft.com", "link": "https://www.microsoft.com/en-us/research/publication/position-evaluating-generative-ai-systems-is-a-social-science-measurement-challenge/", "content": "The measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult, leading to what has been described as”a tangle of sloppy tests [and] apples-to-oranges comparisons” (Roose, 2024). In this position paper, we argue that the ML community..."}
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| 2 |
+
{"idx": 1, "title": "Position : Evaluating Generative AI Systems Is a Social Science ...", "date": "", "ddg_snippet": "Generative AI , Capabilities, Behaviors, Impacts, Evaluation , Measurement , Measurement Theory, Social Sciences , Validity.4 Using the Measurement Framework. In this section , we describe the systematization , operationalization , and interrogation processes in more detail.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00561v2", "content": "Generative AI , Capabilities, Behaviors, Impacts, Evaluation , Measurement , Measurement Theory, Social Sciences , Validity.4 Using the Measurement Framework. In this section , we describe the systematization , operationalization , and interrogation processes in more detail."}
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| 3 |
+
{"idx": 2, "title": "NeurIPS Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "Across academia, industry, and government, there is an increasing awareness that evaluating generative AI (GenAI) systems is challenging , as concepts related to their capabilities (e.g., intelligence, reasoning) and risks (e.g., stereotyping, anthropomorphism) are especially...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/104194", "content": "Across academia, industry, and government, there is an increasing awareness that evaluating generative AI (GenAI) systems is challenging , as concepts related to their capabilities (e.g., intelligence, reasoning) and risks (e.g., stereotyping, anthropomorphism) are especially..."}
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| 4 |
+
{"idx": 3, "title": "Downes.ca ~ Stephen's Web ~ Evaluating Generative AI Systems is ...", "date": "", "ddg_snippet": "The argument in this short paper (6 page PDF) is that \" measurement tasks involved in evaluating GenAI systems are highly reminiscent of measurement tasks found throughout the social sciences \" and thus \"the ML community would benefit from learning from and drawing on the social ...", "subpage_snippet": "", "source": "www.downes.ca", "link": "https://www.downes.ca/post/77850", "content": "The argument in this short paper (6 page PDF) is that \" measurement tasks involved in evaluating GenAI systems are highly reminiscent of measurement tasks found throughout the social sciences \" and thus \"the ML community would benefit from learning from and drawing on the social ..."}
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| 5 |
+
{"idx": 4, "title": "Evaluating Generative AI Systems is a Social Science ...", "date": "", "ddg_snippet": "generative AI systems that borrow from how social scientists measure human behaviors and abilities. Think of current AI evaluation like using a ruler made of rubber - it stretches and bends, giving different measurements each time.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/evaluating-generative-ai-systems-is-social-science", "content": "generative AI systems that borrow from how social scientists measure human behaviors and abilities. Think of current AI evaluation like using a ruler made of rubber - it stretches and bends, giving different measurements each time."}
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| 6 |
+
{"idx": 5, "title": "This week: Evaluation , measurement , span annotation, openai...", "date": "", "ddg_snippet": "Evaluating Generative AI Systems is a Social Science Measurement Challenge . Aren’t social preferences central to the process? “The framework distinguishes between four levels: the background concept, the systematized concept, the measurement instrument(s), and the...", "subpage_snippet": "", "source": "www.gatodo.com", "link": "https://www.gatodo.com/alignment-with-human-preferences/", "content": "Evaluating Generative AI Systems is a Social Science Measurement Challenge . Aren’t social preferences central to the process? “The framework distinguishes between four levels: the background concept, the systematized concept, the measurement instrument(s), and the..."}
|
| 7 |
+
{"idx": 6, "title": "Evaluating Generative AI : The Evolution Beyond Public Benchmarks", "date": "", "ddg_snippet": "Here, we’ll explore key points of evaluating generative AI , focusing on the paradigm shift away from public benchmarks and toward task-specific evaluations .", "subpage_snippet": "", "source": "opendatascience.com", "link": "https://opendatascience.com/evaluating-generative-ai-the-evolution-beyond-public-benchmarks/", "content": "Here, we’ll explore key points of evaluating generative AI , focusing on the paradigm shift away from public benchmarks and toward task-specific evaluations ."}
|
| 8 |
+
{"idx": 7, "title": "Su Lin Blodgett's research works | Microsoft and other places", "date": "", "ddg_snippet": "Position : Evaluating Generative AI Systems is a Social Science Measurement Challenge . Preprint.Specifically, our position is that evaluating GenAI systems is a social science measurement challenge .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/scientific-contributions/Su-Lin-Blodgett-2111326771", "content": "Position : Evaluating Generative AI Systems is a Social Science Measurement Challenge . Preprint.Specifically, our position is that evaluating GenAI systems is a social science measurement challenge ."}
|
| 9 |
+
{"idx": 8, "title": "Towards Interactive Evaluations for Interaction Harms in Human- AI ...", "date": "", "ddg_snippet": "2025. Position : Evaluating Generative AI Systems is a Social Science Measurement Challenge . arXiv preprint arXiv:2502.00561. Wang, A.; Morgenstern, J.; and Dickerson, J. P. 2025. Large language models that replace human participants can harm fully misportray and flatten identity...", "subpage_snippet": "", "source": "knightcolumbia.org", "link": "https://knightcolumbia.org/content/towards-interactive-evaluations-for-interaction-harms-in-human-ai-systems", "content": "2025. Position : Evaluating Generative AI Systems is a Social Science Measurement Challenge . arXiv preprint arXiv:2502.00561. Wang, A.; Morgenstern, J.; and Dickerson, J. P. 2025. Large language models that replace human participants can harm fully misportray and flatten identity..."}
|
| 10 |
+
{"idx": 9, "title": "The Impossibility of Fair LLMs", "date": "", "ddg_snippet": "systems is a social science measurement challenge . Preprint, arXiv:2502.00561. Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, and Tie-Yan Liu.2025. Toward an eval- uation science for generative ai systems .", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.acl-long.5.pdf", "content": "systems is a social science measurement challenge . Preprint, arXiv:2502.00561. Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, and Tie-Yan Liu.2025. Toward an eval- uation science for generative ai systems ."}
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data/sampled_jsons/2024_synthetic_data_generation_scaling_laws.jsonl
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{"idx": 0, "title": "Scaling Synthetic Data Creation with 1,000,000,000 Personas", "date": "", "ddg_snippet": "As synthetic data (Bauer et al., 2024 ; Liu et al., 2024 ) , typically referring to data generated by models or algorithms rather than directly ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.20094v1", "content": "As synthetic data (Bauer et al., 2024 ; Liu et al., 2024 ) , typically referring to data generated by models or algorithms rather than directly ..."}
|
| 2 |
+
{"idx": 1, "title": "Top 10 Companies in Synthetic Data Generation Market in 2025", "date": "", "ddg_snippet": "The worldwide Synthetic Data Generation (SDG) market size was USD 1.30 billion in 2023 and is predicted to reach USD 1.81 billion by the end of 2024 ...", "subpage_snippet": "", "source": "www.emergenresearch.com", "link": "https://www.emergenresearch.com/blog/top-10-companies-in-global-synthetic-data-generation-market", "content": "The worldwide Synthetic Data Generation (SDG) market size was USD 1.30 billion in 2023 and is predicted to reach USD 1.81 billion by the end of 2024 ..."}
|
| 3 |
+
{"idx": 2, "title": "Scaling Synthetic Data Pilots for Enterprise AI | EM360Tech", "date": "", "ddg_snippet": "If even one of these is missing, your synthetic data is not ready for scale . ... The synthetic data generation market was valued at USD 288.5 million ...", "subpage_snippet": "", "source": "em360tech.com", "link": "https://em360tech.com/tech-articles/scaling-synthetic-data-pilots", "content": "If even one of these is missing, your synthetic data is not ready for scale . ... The synthetic data generation market was valued at USD 288.5 million ..."}
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| 4 |
+
{"idx": 3, "title": "Synthetic Data in 2024 - Progress, Opportunities and Challenges", "date": "", "ddg_snippet": "... and smaller models have seen significant price drops, and this trend shows no signs of slowing down, making large- scale synthetic data generation ...", "subpage_snippet": "", "source": "www.timlrx.com", "link": "https://www.timlrx.com/blog/synthetic-data-in-2024-progress-opportunities-challenges", "content": "... and smaller models have seen significant price drops, and this trend shows no signs of slowing down, making large- scale synthetic data generation ..."}
|
| 5 |
+
{"idx": 4, "title": "Synthetic Data Generation Market Size, Report By 2034", "date": "", "ddg_snippet": "The North America synthetic data generation market size accounted for USD 159.87 million in 2024 and is anticipated to grow at the fastest CAGR of 35 ...", "subpage_snippet": "", "source": "www.precedenceresearch.com", "link": "https://www.precedenceresearch.com/synthetic-data-generation-market", "content": "The North America synthetic data generation market size accounted for USD 159.87 million in 2024 and is anticipated to grow at the fastest CAGR of 35 ..."}
|
| 6 |
+
{"idx": 5, "title": "Synthetic Data Generation Market Size | CAGR of 35.9%", "date": "", "ddg_snippet": "The Healthcare & Life Sciences sector emerged as the top industry for synthetic data generation adoption in 2024 , securing over 23.9% of the ...", "subpage_snippet": "", "source": "market.us", "link": "https://market.us/report/synthetic-data-generation-market/", "content": "The Healthcare & Life Sciences sector emerged as the top industry for synthetic data generation adoption in 2024 , securing over 23.9% of the ..."}
|
| 7 |
+
{"idx": 6, "title": "Synthetic Data Generation Market Size, Forecast Analysis - 2035", "date": "", "ddg_snippet": "As per MRFR analysis, the Synthetic Data Generation Market Size was estimated at 1.27 (USD Billion) in 2024 .The Synthetic Data Generation Market ...", "subpage_snippet": "", "source": "www.marketresearchfuture.com", "link": "https://www.marketresearchfuture.com/reports/synthetic-data-generation-market-12216", "content": "As per MRFR analysis, the Synthetic Data Generation Market Size was estimated at 1.27 (USD Billion) in 2024 .The Synthetic Data Generation Market ..."}
|
| 8 |
+
{"idx": 7, "title": "EP154 - Scaling Laws of Synthetic Images for Model Training ...", "date": "", "ddg_snippet": "Clio : The key takeaway was that synthetic data , when generated considering these factors, can indeed scale well and improve supervised training ...", "subpage_snippet": "", "source": "paperbrief.net", "link": "https://paperbrief.net/posts/154/", "content": "Clio : The key takeaway was that synthetic data , when generated considering these factors, can indeed scale well and improve supervised training ..."}
|
| 9 |
+
{"idx": 8, "title": "Synthetic Data Generation Market Size, Share, Growth Factors,", "date": "", "ddg_snippet": "The global Synthetic Data Generation market report highlights the discussion on the top segments across the Synthetic Data Generation industry and ...", "subpage_snippet": "", "source": "jobs.ezelogs.com", "link": "https://jobs.ezelogs.com/job/synthetic-data-generation-market-size-share-growth-factors-competitive-landscape-with-regional-forecast-to-2035/", "content": "The global Synthetic Data Generation market report highlights the discussion on the top segments across the Synthetic Data Generation industry and ..."}
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| 10 |
+
{"idx": 9, "title": "Mike Lewis - ACL Anthology", "date": "", "ddg_snippet": "... knowledge and reasoning-based skills such as knowledge-based QA and code generation , and we answer this question in the affirmative: scaling laws are ...", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/people/mike-lewis/", "content": "... knowledge and reasoning-based skills such as knowledge-based QA and code generation , and we answer this question in the affirmative: scaling laws are ..."}
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data/sampled_jsons/2406.05072_Linearization_Turns_Neural_Operators_Theorem_3.2.jsonl
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{"idx": 0, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian...", "date": "", "ddg_snippet": "2.1. Neural Operators Neural operators (NOs) (Kovachki et al., 2023) are neural network architectures that map between (infinite-dimensional) Banach spaces of functions. A neural operator is a function F : A × W → U, where.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2406.05072", "content": "2.1. Neural Operators Neural operators (NOs) (Kovachki et al., 2023) are neural network architectures that map between (infinite-dimensional) Banach spaces of functions. A neural operator is a function F : A × W → U, where."}
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| 2 |
+
{"idx": 1, "title": "[ 2406 . 05072 ] Linearization Turns Neural Operators into...", "date": "", "ddg_snippet": "arXiv: 2406 . 05072 (cs). [Submitted on 7 Jun 2024 (v1), last revised 31 Jan 2025 (this version, v2)].View a PDF of the paper titled Linearization Turns Neural Operators into Function-Valued Gaussian Processes, by Emilia Magnani and 3 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2406.05072", "content": "arXiv: 2406 . 05072 (cs). [Submitted on 7 Jun 2024 (v1), last revised 31 Jan 2025 (this version, v2)].View a PDF of the paper titled Linearization Turns Neural Operators into Function-Valued Gaussian Processes, by Emilia Magnani and 3 other authors."}
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| 3 |
+
{"idx": 2, "title": "Linearization Turns Neural Operators into... | alphaXiv", "date": "", "ddg_snippet": "Abstract: Neural operators generalize neural networks to learn mappings between function spaces from data. They are commonly used to learn solution operators of parametric partial differential equations (PDEs) or propagators of time-dependent PDEs.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/abs/2406.05072", "content": "Abstract: Neural operators generalize neural networks to learn mappings between function spaces from data. They are commonly used to learn solution operators of parametric partial differential equations (PDEs) or propagators of time-dependent PDEs."}
|
| 4 |
+
{"idx": 3, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian...", "date": "", "ddg_snippet": "The paper introduces the Neural Operator Laplace Approximation (NOLA) to address the lack of uncertainty quantification in neural operators used for modeling dynamical systems governed by partial differential equations (PDEs).", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/papers/2406.05072", "content": "The paper introduces the Neural Operator Laplace Approximation (NOLA) to address the lack of uncertainty quantification in neural operators used for modeling dynamical systems governed by partial differential equations (PDEs)."}
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| 5 |
+
{"idx": 4, "title": "(PDF) Linearization Turns Neural Operators into Function-Valued...", "date": "", "ddg_snippet": "Neural operators ... | Find, read and cite all the research you need on ResearchGate.∗Equal contribution. arXiv: 2406 . 05072 v1 [cs.LG] 7 Jun 2024. The complex nature of dynamic systems makes errors in predictions difficult to detect. Uncertainty.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/381294298_Linearization_Turns_Neural_Operators_into_Function-Valued_Gaussian_Processes", "content": "Neural operators ... | Find, read and cite all the research you need on ResearchGate.∗Equal contribution. arXiv: 2406 . 05072 v1 [cs.LG] 7 Jun 2024. The complex nature of dynamic systems makes errors in predictions difficult to detect. Uncertainty."}
|
| 6 |
+
{"idx": 5, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian...", "date": "", "ddg_snippet": "2406 . 05072 . Neural operators are deep neural networks designed to learn nontrivial solution operators of such differential equations from data.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/arxiv/2406.05072", "content": "2406 . 05072 . Neural operators are deep neural networks designed to learn nontrivial solution operators of such differential equations from data."}
|
| 7 |
+
{"idx": 6, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian...", "date": "", "ddg_snippet": "https://doi.org/10.48550/arXiv. 2406 . 05072 . DDC-Klassifikation: 004 - Informatik.", "subpage_snippet": "", "source": "publikationen.uni-tuebingen.de", "link": "https://publikationen.uni-tuebingen.de/xmlui/handle/10900/159278", "content": "https://doi.org/10.48550/arXiv. 2406 . 05072 . DDC-Klassifikation: 004 - Informatik."}
|
| 8 |
+
{"idx": 7, "title": "Linearization Turns Neural Operators into Function-Valued Gaussian...", "date": "", "ddg_snippet": "Neural operators are deep neural networks designed to learn nontrivial solution operators of such differential equations from data.Full paper. Read original: arXiv: 2406 . 05072 .", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/linearization-turns-neural-operators-into-function-valued", "content": "Neural operators are deep neural networks designed to learn nontrivial solution operators of such differential equations from data.Full paper. Read original: arXiv: 2406 . 05072 ."}
|
| 9 |
+
{"idx": 8, "title": "Neural PDE operator learning on domains with interesting geometry...", "date": "", "ddg_snippet": "4 Graph neural operators . 5 DeepONets. 6 References.2024. “ Linearization Turns Neural Operators into Function-Valued Gaussian Processes.”", "subpage_snippet": "", "source": "danmackinlay.name", "link": "https://danmackinlay.name/notebook/ml_pde_interesting_geometries", "content": "4 Graph neural operators . 5 DeepONets. 6 References.2024. “ Linearization Turns Neural Operators into Function-Valued Gaussian Processes.”"}
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{"idx": 9, "title": "GitHub - MethodsOfMachineLearning/luno: LUNO: Linearized ...", "date": "", "ddg_snippet": "luno - Linearized Uncertainty for Neural Operators . This repository contains the main algorithm of the paper \" Linearization Turns Neural Operators into Function-Valued Gaussian Processes\" by Magnani et al. (2025). Description.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/MethodsOfMachineLearning/luno", "content": "luno - Linearized Uncertainty for Neural Operators . This repository contains the main algorithm of the paper \" Linearization Turns Neural Operators into Function-Valued Gaussian Processes\" by Magnani et al. (2025). Description."}
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{"idx": 0, "title": "Wasserstein Distances, Neuronal Entanglement, and Sparsity", "date": "", "ddg_snippet": "A.2 Distribution of Wasserstein distances across all Llama-2-7B FFN layers After collecting the Wasserstein distance to the normal distribution for every neuron, we find that all up and gate projection matrices in each Llama-2-7B FFN block have high WD neurons.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.15756v4", "content": "A.2 Distribution of Wasserstein distances across all Llama-2-7B FFN layers After collecting the Wasserstein distance to the normal distribution for every neuron, we find that all up and gate projection matrices in each Llama-2-7B FFN block have high WD neurons."}
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{"idx": 1, "title": "PDF Quantifying the Empirical Wasserstein Distance to a Set of ... - NeurIPS", "date": "", "ddg_snippet": "This further extends conventional results on the rate of statistical convergence for Wasserstein distances between an empirical distribution and the true (unknown) distribution.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2020/file/f3507289cfdc8c9ae93f4098111a13f9-Paper.pdf", "content": "This further extends conventional results on the rate of statistical convergence for Wasserstein distances between an empirical distribution and the true (unknown) distribution."}
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{"idx": 2, "title": "Statistical Aspects of Wasserstein Distances | Annual Reviews", "date": "", "ddg_snippet": "Wasserstein distances are metrics on probability distributions inspired by the problem of optimal mass transportation. Roughly speaking, they measure the minimal effort required to reconfigure the probability mass of one distribution in order to recover the other distribution. They are ubiquitous in mathematics, with a long history that has seen them catalyze core developments in analysis ...", "subpage_snippet": "", "source": "www.annualreviews.org", "link": "https://www.annualreviews.org/content/journals/10.1146/annurev-statistics-030718-104938", "content": "Wasserstein distances are metrics on probability distributions inspired by the problem of optimal mass transportation. Roughly speaking, they measure the minimal effort required to reconfigure the probability mass of one distribution in order to recover the other distribution. They are ubiquitous in mathematics, with a long history that has seen them catalyze core developments in analysis ..."}
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{"idx": 3, "title": "PDF Orthogonal Estimation of Wasserstein Distances", "date": "", "ddg_snippet": "In this paper, we investigate these two shortcomings of the sliced Wasserstein distance and propose a new dis-tance which incorporates the computational bene ts of the sliced Wasserstein distance , whilst still retain-ing information from the high-dimensional distances . Given recent strong results based on Wasserstein dis-tances and their tractable approximations, exploring related methods is ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v89/rowland19a/rowland19a.pdf", "content": "In this paper, we investigate these two shortcomings of the sliced Wasserstein distance and propose a new dis-tance which incorporates the computational bene ts of the sliced Wasserstein distance , whilst still retain-ing information from the high-dimensional distances . Given recent strong results based on Wasserstein dis-tances and their tractable approximations, exploring related methods is ..."}
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{"idx": 4, "title": "Wasserstein Distances, Neuronal Entanglement, and Sparsity", "date": "", "ddg_snippet": "Here we attempt to study how disentanglement can be used to understand performance, particularly under weight sparsity, a leading post-training optimization technique. We suggest a novel measure for estimating neuronal entanglement: the Wasserstein distance of a neuron's output distribution to a Gaussian.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=cnKhHxN3xj", "content": "Here we attempt to study how disentanglement can be used to understand performance, particularly under weight sparsity, a leading post-training optimization technique. We suggest a novel measure for estimating neuronal entanglement: the Wasserstein distance of a neuron's output distribution to a Gaussian."}
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{"idx": 5, "title": "Wasserstein Distances Made Explainable: Insights into Dataset Shifts ...", "date": "", "ddg_snippet": "This confirms the technical strength of our method, namely its sensitivity to the actual Wasserstein distance model and its ability to attribute the Wasserstein distance comprehensively through its fulfillment of the conservation property (cf. Table II for a technical comparison between methods).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.06123", "content": "This confirms the technical strength of our method, namely its sensitivity to the actual Wasserstein distance model and its ability to attribute the Wasserstein distance comprehensively through its fulfillment of the conservation property (cf. Table II for a technical comparison between methods)."}
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{"idx": 6, "title": "Wasserstein distances, neuronal entanglement, and sparsity", "date": "", "ddg_snippet": "Here we attempt to study how disentanglement can be used to understand performance, particularly under weight sparsity, a leading post-training optimization technique. We suggest a novel measure for estimating neuronal entanglement: the Wasserstein distance of a neuron's output distribution to a Gaussian.", "subpage_snippet": "", "source": "lin-k76.github.io", "link": "https://lin-k76.github.io/publication/2025-wasserstein", "content": "Here we attempt to study how disentanglement can be used to understand performance, particularly under weight sparsity, a leading post-training optimization technique. We suggest a novel measure for estimating neuronal entanglement: the Wasserstein distance of a neuron's output distribution to a Gaussian."}
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{"idx": 7, "title": "Wasserstein Distances for Stereo Disparity Estimation", "date": "", "ddg_snippet": "To overcome these limitations, the authors propose two adaptions to existing frameworks: (i) adding a branch to predict an offset for each disparity so that the model can output a distribution for arbitrary disparities; (ii) introducing a novel stereo loss based on Wasserstein distance to directly capture the uni-/multi-modal GT distribution.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2020/file/fe7ecc4de28b2c83c016b5c6c2acd826-Review.html", "content": "To overcome these limitations, the authors propose two adaptions to existing frameworks: (i) adding a branch to predict an offset for each disparity so that the model can output a distribution for arbitrary disparities; (ii) introducing a novel stereo loss based on Wasserstein distance to directly capture the uni-/multi-modal GT distribution."}
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{"idx": 8, "title": "Wasserstein Distances, Neuronal Entanglement, and Sparsity - GitHub", "date": "", "ddg_snippet": "Here we include the code for our paper Wasserstein Distances , Neuronal Entanglement, and Sparsity. The code allows for the creation and evaluation of Sparse Expansion models in terms of overall perplexity. One-shot expert creation process and inference process of Sparse Expansion in an FFN block.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Shavit-Lab/Sparse-Expansion", "content": "Here we include the code for our paper Wasserstein Distances , Neuronal Entanglement, and Sparsity. The code allows for the creation and evaluation of Sparse Expansion models in terms of overall perplexity. One-shot expert creation process and inference process of Sparse Expansion in an FFN block."}
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{"idx": 9, "title": "PDF Optimal Transport and Wasserstein Distance", "date": "", "ddg_snippet": "The set of distributions endowed with the W 2 distance is a manifold and R ( j(x) k(x))2dx is the distance between the projections onto the tangent space at R. In other words, j de nes an approximate embedding of the set of distributions and L2.", "subpage_snippet": "", "source": "www.stat.cmu.edu", "link": "https://www.stat.cmu.edu/~larry/=sml/Opt.pdf", "content": "The set of distributions endowed with the W 2 distance is a manifold and R ( j(x) k(x))2dx is the distance between the projections onto the tangent space at R. In other words, j de nes an approximate embedding of the set of distributions and L2."}
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data/sampled_jsons/2502.00921_appendix_supplementary_MATH_dataset_CW_correct_CW_incorrect_values.jsonl
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{"idx": 0, "title": "Create Excel calendar weeks correctly - tutkit.com Aeordynamics, drag, wind resistance - table with Cw values ... topology of relative CW complex - Mathematics Stack Exchange Tips for Querying CW and Average Power - Keysight Stanford Math 51: Linear Algebra, Multivariable Calculus & Apps DeltaMath CLASSWIZ-fx-570CW_fx-991CW-Manuals-CASIO", "date": "", "ddg_snippet": "A mathematical formula helps to calculate the correct calendar weeks in relation to the year. It is important to set the correct links in Excel to keep the data dynamic. Step-by-Step Guide Step 1: New Column for Calendar Week and Year First, you need to create a new column for \" CW plus Year.\" Jan 16, 2008 · The discussion focuses on the need for a table of drag coefficients ( Cw values ) for various object shapes to assist in calculating the trajectory of a projectile. The user clarifies that Cw values reflect the aerodynamic efficiency of objects, distinguishing between different designs like race cars and buses, and emphasizes that this is separate from the object's shadow area. A link to a ... Sep 20, 2020 · You are correct . The topology of a relative CW complex is compatible with the topology of its cells. Keysight power meters and power sensors offer the ability to measure CW and average power. The following example provides some tips for using power meters and power sensors to acquire accurate power without increasing the test time. Explore Stanford University's Math 51 course text covering linear algebra, multivariable calculus, and modern applications. Learn vectors, matrices, optimization, and eigenvalues for data science and engineering. DeltaMath for Home Your personalized learning platform designed for at-home success. Try it today with a 7-day free trial. Learn More User’s Guidefx-570CW | fx-991CW EN Scientific Calculator Please read and adhere to the Safety Precautions before use.", "subpage_snippet": "", "source": "www.tutkit.com", "link": "https://www.tutkit.com/en/text-tutorials/4309-create-excel-calendar-weeks-correctly", "content": "A mathematical formula helps to calculate the correct calendar weeks in relation to the year. It is important to set the correct links in Excel to keep the data dynamic. Step-by-Step Guide Step 1: New Column for Calendar Week and Year First, you need to create a new column for \" CW plus Year.\" Jan 16, 2008 · The discussion focuses on the need for a table of drag coefficients ( Cw values ) for various object shapes to assist in calculating the trajectory of a projectile. The user clarifies that Cw values reflect the aerodynamic efficiency of objects, distinguishing between different designs like race cars and buses, and emphasizes that this is separate from the object's shadow area. A link to a ... Sep 20, 2020 · You are correct . The topology of a relative CW complex is compatible with the topology of its cells. Keysight power meters and power sensors offer the ability to measure CW and average power. The following example provides some tips for using power meters and power sensors to acquire accurate power without increasing the test time. Explore Stanford University's Math 51 course text covering linear algebra, multivariable calculus, and modern applications. Learn vectors, matrices, optimization, and eigenvalues for data science and engineering. DeltaMath for Home Your personalized learning platform designed for at-home success. Try it today with a 7-day free trial. Learn More User’s Guidefx-570CW | fx-991CW EN Scientific Calculator Please read and adhere to the Safety Precautions before use."}
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{"idx": 1, "title": "Aeordynamics, drag, wind resistance - table with Cw values ...", "date": "", "ddg_snippet": "Jan 16, 2008 · The discussion focuses on the need for a table of drag coefficients ( Cw values ) for various object shapes to assist in calculating the trajectory of a projectile. The user clarifies that Cw values reflect the aerodynamic efficiency of objects, distinguishing between different designs like race cars and buses, and emphasizes that this is separate from the object's shadow area. A link to a ...", "subpage_snippet": "", "source": "www.physicsforums.com", "link": "https://www.physicsforums.com/threads/aeordynamics-drag-wind-resistance-table-with-cw-values-for-objects.209179/", "content": "Jan 16, 2008 · The discussion focuses on the need for a table of drag coefficients ( Cw values ) for various object shapes to assist in calculating the trajectory of a projectile. The user clarifies that Cw values reflect the aerodynamic efficiency of objects, distinguishing between different designs like race cars and buses, and emphasizes that this is separate from the object's shadow area. A link to a ..."}
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{"idx": 2, "title": "Stanford Math 51: Linear Algebra, Multivariable Calculus & Apps", "date": "", "ddg_snippet": "Explore Stanford University's Math 51 course text covering linear algebra, multivariable calculus, and modern applications. Learn vectors, matrices, optimization, and eigenvalues for data science and engineering.", "subpage_snippet": "", "source": "studylib.net", "link": "https://studylib.net/doc/27857883/math51book", "content": "Explore Stanford University's Math 51 course text covering linear algebra, multivariable calculus, and modern applications. Learn vectors, matrices, optimization, and eigenvalues for data science and engineering."}
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{"idx": 3, "title": "DeltaMath", "date": "", "ddg_snippet": "DeltaMath for Home Your personalized learning platform designed for at-home success. Try it today with a 7-day free trial. Learn More", "subpage_snippet": "", "source": "www.deltamath.com", "link": "https://www.deltamath.com/", "content": "DeltaMath for Home Your personalized learning platform designed for at-home success. Try it today with a 7-day free trial. Learn More"}
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{"idx": 4, "title": "Floating-point extensions part 4: supplementary ... - cppreference.com", "date": "", "ddg_snippet": "Supplementary mathematical functions. Defined in header . exp2m1 exp2m1f exp2m1lexp2m1fN exp2m1fNxexp2m1dN exp2m1dNx. (FP Ext 4 TS).compute the product of n members of an array as a scaled value and a scale factor (function) .", "subpage_snippet": "", "source": "w.cppreference.com", "link": "https://w.cppreference.com/c/experimental/fpext4.html", "content": "Supplementary mathematical functions. Defined in header . exp2m1 exp2m1f exp2m1lexp2m1fN exp2m1fNxexp2m1dN exp2m1dNx. (FP Ext 4 TS).compute the product of n members of an array as a scaled value and a scale factor (function) ."}
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{"idx": 5, "title": "topology of relative CW complex - Mathematics Stack Exchange", "date": "", "ddg_snippet": "Sep 20, 2020 · You are correct . The topology of a relative CW complex is compatible with the topology of its cells.", "subpage_snippet": "", "source": "math.stackexchange.com", "link": "https://math.stackexchange.com/questions/3832938/topology-of-relative-cw-complex", "content": "Sep 20, 2020 · You are correct . The topology of a relative CW complex is compatible with the topology of its cells."}
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{"idx": 6, "title": "[ 2502 . 00921 ] Blink of an eye: a simple theory for feature localization in...", "date": "", "ddg_snippet": "In this work we develop a simple, unifying theory to explain this phenomenon using the formalism of stochastic localization samplers. We show that it emerges generically as the generation process localizes to a sub-population of the distribution it models.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00921", "content": "In this work we develop a simple, unifying theory to explain this phenomenon using the formalism of stochastic localization samplers. We show that it emerges generically as the generation process localizes to a sub-population of the distribution it models."}
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{"idx": 7, "title": "Тренировочные варианты ОГЭ 2024-2025-2026 по... — math 100.ru", "date": "", "ddg_snippet": "Тренировочный вариант № 181 ОГЭ УСЛОЖНЁННЫЙ Тренировочный вариант № 180 ОГЭ из заданий банка ФИПИ Тренировочный вариант № 179 ОГЭ УСЛОЖНЁННЫЙ Тренировочный вариант...", "subpage_snippet": "", "source": "math100.ru", "link": "https://math100.ru/trenirovochnie-varianti-oge-new/", "content": "Тренировочный вариант № 181 ОГЭ УСЛОЖНЁННЫЙ Тренировочный вариант № 180 ОГЭ из заданий банка ФИПИ Тренировочный вариант № 179 ОГЭ УСЛОЖНЁННЫЙ Тренировочный вариант..."}
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{"idx": 8, "title": "How to find the 20th and 80th percentile of a data set - YouTube", "date": "", "ddg_snippet": "The kth percentile of a data set is the data value that appeared in the kth position after the dataset has...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=MSQpvuPL2cw", "content": "The kth percentile of a data set is the data value that appeared in the kth position after the dataset has..."}
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{"idx": 9, "title": "(PDF) Blink of an eye: a simple theory for feature localization in...", "date": "", "ddg_snippet": "arXiv: 2502 . 00921 v1 [cs.LG] 2 Feb 2025. Contents.of thought of math and reasoning tasks and their significance in leading the model to incorrect outputs, concurrent with our results in Figure 5. They then used them to provide rewards or data for a preference.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/388658326_Blink_of_an_eye_a_simple_theory_for_feature_localization_in_generative_models", "content": "arXiv: 2502 . 00921 v1 [cs.LG] 2 Feb 2025. Contents.of thought of math and reasoning tasks and their significance in leading the model to incorrect outputs, concurrent with our results in Figure 5. They then used them to provide rewards or data for a preference."}
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data/sampled_jsons/33113_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis_Algorith.jsonl
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{"idx": 0, "title": "Stochastic - Wikipedia", "date": "", "ddg_snippet": "Stochastic is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conve...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Stochastic", "content": "Stochastic is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conve..."}
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{"idx": 1, "title": "Deterministic-to-Stochastic Diverse Latent Feature Mapping ...", "date": "", "ddg_snippet": "In this paper, we propose a Deterministic -to- Stochastic Di-verse Latent Feature Mapping (DSDFM) for human motion synthesis . DSDFM is easy to train compared with the re-cent SGMs-based method, while facilitating the diversity and accuracy of generated human motions.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Hua_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis_CVPR_2025_paper.pdf", "content": "In this paper, we propose a Deterministic -to- Stochastic Di-verse Latent Feature Mapping (DSDFM) for human motion synthesis . DSDFM is easy to train compared with the re-cent SGMs-based method, while facilitating the diversity and accuracy of generated human motions."}
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{"idx": 2, "title": "Deterministic-to-Stochastic Diverse Latent Feature Mapping ... Deterministic-to-Stochastic Diverse Latent Feature Mapping ... Foruck/Awesome-Human-Motion - GitHub Towards Efficient and Diverse Generative Model for ... arXiv:2505.00998v1 [cs.CV] 2 May 2025 Deterministic-to-Stochastic Diverse Latent Feature Mapping ... Appendix - CVF Open Access", "date": "", "ddg_snippet": "May 2, 2025 · Human motion synthesis aims to generate plausible human motion sequences, which has raised widespread attention in computer animation. Recent score-based generative models (SGMs) have demonstrated impressive results on this task. However, their training process involves complex curvature trajectories, leading to unstable training process. In this paper, we propose a Deterministic -to- Stochastic ... However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper, we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis .DSDFM consists of two stages. (CVPR 2025) DSDFM: Deterministic -to- Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis , Hua et al. (CVPR 2025) EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation, Hua et al. Oct 28, 2024 · Then, we combine the extended OT map with the generator of reconstruction network to generate new human motions. Thereby overcoming the issues of mode collapse and mode mixture. MOOT generates a latent code distribution that is well-behaved and highly structured, providing a strong motion prior for various applications in the field of human motion . diverse output gen-eration procedure. Deterministic feature mapping procedure aims to explore the optimal solution for building the connec-tions between the Gaussian distribution and the latent space distribution of human motions using the designed Deter-ministic In this paper, we propose a Deterministic -to- Stochastic Di-verse Latent Feature Mapping (DSDFM) for human motion synthesis . DSDFM is easy to train compared with the re-cent SGMs-based method, while facilitating the diversity and accuracy of generated human motions. D . 1 . Metric Definitions In this work, we use the following metrics to measure the per-formance of the proposed method for unconditional human motion synthesis and Action-to- Motion tasks.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2505.00998", "content": "May 2, 2025 · Human motion synthesis aims to generate plausible human motion sequences, which has raised widespread attention in computer animation. Recent score-based generative models (SGMs) have demonstrated impressive results on this task. However, their training process involves complex curvature trajectories, leading to unstable training process. In this paper, we propose a Deterministic -to- Stochastic ... However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper, we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis .DSDFM consists of two stages. (CVPR 2025) DSDFM: Deterministic -to- Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis , Hua et al. (CVPR 2025) EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation, Hua et al. Oct 28, 2024 · Then, we combine the extended OT map with the generator of reconstruction network to generate new human motions. Thereby overcoming the issues of mode collapse and mode mixture. MOOT generates a latent code distribution that is well-behaved and highly structured, providing a strong motion prior for various applications in the field of human motion . diverse output gen-eration procedure. Deterministic feature mapping procedure aims to explore the optimal solution for building the connec-tions between the Gaussian distribution and the latent space distribution of human motions using the designed Deter-ministic In this paper, we propose a Deterministic -to- Stochastic Di-verse Latent Feature Mapping (DSDFM) for human motion synthesis . DSDFM is easy to train compared with the re-cent SGMs-based method, while facilitating the diversity and accuracy of generated human motions. D . 1 . Metric Definitions In this work, we use the following metrics to measure the per-formance of the proposed method for unconditional human motion synthesis and Action-to- Motion tasks."}
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{"idx": 3, "title": "Deterministic-to-Stochastic Diverse Latent Feature Mapping ...", "date": "", "ddg_snippet": "However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper, we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis .DSDFM consists of two stages.", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/33113", "content": "However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper, we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis .DSDFM consists of two stages."}
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{"idx": 4, "title": "Foruck/Awesome-Human-Motion - GitHub", "date": "", "ddg_snippet": "(CVPR 2025) DSDFM: Deterministic -to- Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis , Hua et al. (CVPR 2025) EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation, Hua et al.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Foruck/Awesome-Human-Motion", "content": "(CVPR 2025) DSDFM: Deterministic -to- Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis , Hua et al. (CVPR 2025) EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation, Hua et al."}
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{"idx": 5, "title": "Towards Efficient and Diverse Generative Model for ...", "date": "", "ddg_snippet": "Oct 28, 2024 · Then, we combine the extended OT map with the generator of reconstruction network to generate new human motions. Thereby overcoming the issues of mode collapse and mode mixture. MOOT generates a latent code distribution that is well-behaved and highly structured, providing a strong motion prior for various applications in the field of human motion .", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3664647.3681093", "content": "Oct 28, 2024 · Then, we combine the extended OT map with the generator of reconstruction network to generate new human motions. Thereby overcoming the issues of mode collapse and mode mixture. MOOT generates a latent code distribution that is well-behaved and highly structured, providing a strong motion prior for various applications in the field of human motion ."}
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{"idx": 6, "title": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for ...", "date": "", "ddg_snippet": "Hua_ Deterministic - to - Stochastic _ Diverse _ Latent _ Feature _ Mapping _ for _ Human _ Motion _ Synthesis @CVPR2025@CVF.This stage is achieved by the designed deterministic feature mapping procedure with DerODE and stochastic diverse output generation procedure with DivSDE.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/Hua_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis@CVPR2025@CVF", "content": "Hua_ Deterministic - to - Stochastic _ Diverse _ Latent _ Feature _ Mapping _ for _ Human _ Motion _ Synthesis @CVPR2025@CVF.This stage is achieved by the designed deterministic feature mapping procedure with DerODE and stochastic diverse output generation procedure with DivSDE."}
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{"idx": 7, "title": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for ...", "date": "", "ddg_snippet": "In this paper, we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions .", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/abs/2505.00998", "content": "In this paper, we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions ."}
|
| 9 |
+
{"idx": 8, "title": "DivDiff: A Conditional Diffusion Model for Diverse Human Motion ...", "date": "", "ddg_snippet": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis .The first human motion reconstruction stage aims to learn the latent space distribution of human motions .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/387413105_DivDiff_A_Conditional_Diffusion_Model_for_Diverse_Human_Motion_Prediction", "content": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis .The first human motion reconstruction stage aims to learn the latent space distribution of human motions ."}
|
| 10 |
+
{"idx": 9, "title": "GitHub - Zilize/awesome-text-to- motion : Text-driven human motion ...", "date": "", "ddg_snippet": "DSDFM: \" Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis \".EnergyMoGen: \"EnergyMoGen: Compositional Human Motion Generation with Energy-Based Diffusion Model in Latent Space\".", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Zilize/awesome-text-to-motion", "content": "DSDFM: \" Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis \".EnergyMoGen: \"EnergyMoGen: Compositional Human Motion Generation with Energy-Based Diffusion Model in Latent Space\"."}
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data/sampled_jsons/33113_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis_paper.jsonl
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{"idx": 0, "title": "Stochastic - Wikipedia", "date": "", "ddg_snippet": "Stochastic is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conve...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Stochastic", "content": "Stochastic is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conve..."}
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+
{"idx": 1, "title": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for ...", "date": "", "ddg_snippet": "Diverse Motion Generation. Deterministic Feature Mapping Procedure.In this paper , we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human mo - tion synthesis .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.00998", "content": "Diverse Motion Generation. Deterministic Feature Mapping Procedure.In this paper , we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human mo - tion synthesis ."}
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| 3 |
+
{"idx": 2, "title": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for ...", "date": "", "ddg_snippet": "In this paper , we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions .", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/abs/2505.00998", "content": "In this paper , we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions ."}
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| 4 |
+
{"idx": 3, "title": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for ...", "date": "", "ddg_snippet": "Hua_ Deterministic - to - Stochastic _ Diverse _ Latent _ Feature _ Mapping _ for _ Human _ Motion _ Synthesis @CVPR2025@CVF.This stage is achieved by the designed deterministic feature mapping procedure with DerODE and stochastic diverse output generation procedure with DivSDE.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/Hua_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis@CVPR2025@CVF", "content": "Hua_ Deterministic - to - Stochastic _ Diverse _ Latent _ Feature _ Mapping _ for _ Human _ Motion _ Synthesis @CVPR2025@CVF.This stage is achieved by the designed deterministic feature mapping procedure with DerODE and stochastic diverse output generation procedure with DivSDE."}
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| 5 |
+
{"idx": 4, "title": "10 Papers Accepted at CVPR 2025", "date": "", "ddg_snippet": "Features . Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis Hua Yu, Weiming Liu, Gui Xu, Yaqing Hou, Yew-Soon Ong, Qiang Zhang.", "subpage_snippet": "", "source": "www.a-star.edu.sg", "link": "https://www.a-star.edu.sg/cfar/news/news/features/10-papers-accepted-at-cvpr-2025", "content": "Features . Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis Hua Yu, Weiming Liu, Gui Xu, Yaqing Hou, Yew-Soon Ong, Qiang Zhang."}
|
| 6 |
+
{"idx": 5, "title": "GitHub - Zilize/awesome-text-to- motion : Text-driven human motion ...", "date": "", "ddg_snippet": "DSDFM: \" Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis \".TM2T: \"TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts\".", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Zilize/awesome-text-to-motion", "content": "DSDFM: \" Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis \".TM2T: \"TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts\"."}
|
| 7 |
+
{"idx": 6, "title": "Learning Diverse Stochastic Human -Action Generators by Learning...", "date": "", "ddg_snippet": "Human - motion generation is a long-standing challenging task due to the requirement of accurately modeling complex and diverse dynamic patterns.Combining recurrent neural networks and adversarial training for human motion modelling, synthesis and control.", "subpage_snippet": "", "source": "cdn.aaai.org", "link": "https://cdn.aaai.org/ojs/6911/6911-13-10140-1-10-20200525.pdf", "content": "Human - motion generation is a long-standing challenging task due to the requirement of accurately modeling complex and diverse dynamic patterns.Combining recurrent neural networks and adversarial training for human motion modelling, synthesis and control."}
|
| 8 |
+
{"idx": 7, "title": "Harmonizing Stochasticity and Determinism : Scene-responsive...", "date": "", "ddg_snippet": "# The DiMoP3D framework, designed for diverse human motion prediction in 3D scenes, presents a novel approach by harmonizing stochasticity and determinism .", "subpage_snippet": "", "source": "deep-diver.github.io", "link": "https://deep-diver.github.io/neurips2024/posters/nqcknm6tes/", "content": "# The DiMoP3D framework, designed for diverse human motion prediction in 3D scenes, presents a novel approach by harmonizing stochasticity and determinism ."}
|
| 9 |
+
{"idx": 8, "title": "UNIF: United Neural Implicit Functions for Clothed Human ...", "date": "", "ddg_snippet": "[4] Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis . Human motion synthesis aims to generate plausible human motion sequences, which has raised widespread attention in computer animation.", "subpage_snippet": "", "source": "www.bohrium.com", "link": "https://www.bohrium.com/paper-details/unif-united-neural-implicit-functions-for-clothed-human-reconstruction-and-animation/867766725599297675-108597", "content": "[4] Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis . Human motion synthesis aims to generate plausible human motion sequences, which has raised widespread attention in computer animation."}
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| 10 |
+
{"idx": 9, "title": "CVPR2025 Accepted Papers -CSDN博客", "date": "", "ddg_snippet": "for Training-free Open-vocabulary Attribute Detection Marco Garosi · Alessandro Conti · Gaowen Liu · Elisa Ricci · Massimiliano Mancini Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis Hua Yu · Weiming Liu · Gui Xu · Yaqing Hou...", "subpage_snippet": "", "source": "blog.csdn.net", "link": "https://blog.csdn.net/u013963578/article/details/146183100", "content": "for Training-free Open-vocabulary Attribute Detection Marco Garosi · Alessandro Conti · Gaowen Liu · Elisa Ricci · Massimiliano Mancini Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis Hua Yu · Weiming Liu · Gui Xu · Yaqing Hou..."}
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data/sampled_jsons/33113_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis_paper_Se.jsonl
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{"idx": 0, "title": "Stochastic - Wikipedia", "date": "", "ddg_snippet": "Stochastic is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conve...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Stochastic", "content": "Stochastic is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conve..."}
|
| 2 |
+
{"idx": 1, "title": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for ...", "date": "", "ddg_snippet": "In this paper , we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human mo - tion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions .", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Hua_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis_CVPR_2025_paper.pdf", "content": "In this paper , we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human mo - tion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions ."}
|
| 3 |
+
{"idx": 2, "title": "Deterministic-to-Stochastic Diverse Latent Feature Mapping ... Deterministic-to-Stochastic Diverse Latent Feature Mapping ... Foruck/Awesome-Human-Motion - GitHub arXiv:2505.00998v1 [cs.CV] 2 May 2025 Appendix - CVF Open Access Deterministic-to-Stochastic Diverse Latent Feature Mapping ... Harmonizing Stochasticity and Determinism: Scene-responsive ...", "date": "", "ddg_snippet": "May 2, 2025 · Human motion synthesis aims to generate plausible human motion sequences, which has raised widespread attention in computer animation. Recent score-based generative models (SGMs) have demonstrated impressive results on this task. However, their training process involves complex curvature trajectories, leading to unstable training process. In this paper , we propose a Deterministic -to- Stochastic ... In this paper , we propose a Deterministic -to- Stochastic Di-verse Latent Feature Mapping (DSDFM) for human motion synthesis . DSDFM is easy to train compared with the re-cent SGMs-based method, while facilitating the diversity and accuracy of generated human motions. (CVPR 2025) DSDFM: Deterministic -to- Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis , Hua et al. (CVPR 2025) EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation, Hua et al. leading to unstable training process. In this paper , we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDF ) method for human mo-tion sy thesis. DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the laten We provide additional visualization of human motion results in this section , which consists of the unconditional human motion synthesis and Action-to- Motion tasks. Synthesis . Figure 5 visualizes a broader range of uncon-ditional human motion sequences, effectively highlighting the remarkable diversity and high fidelity achieved by our pro However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper , we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis .DSDFM consists of two stages. To fill this gap, this work introduces a novel task: predicting diverse human motion within real-world 3D scenes. In contrast to prior works, it requires harmonizing the deterministic constraints imposed by the surrounding 3D scenes with the stochastic aspect of human motion .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2505.00998", "content": "May 2, 2025 · Human motion synthesis aims to generate plausible human motion sequences, which has raised widespread attention in computer animation. Recent score-based generative models (SGMs) have demonstrated impressive results on this task. However, their training process involves complex curvature trajectories, leading to unstable training process. In this paper , we propose a Deterministic -to- Stochastic ... In this paper , we propose a Deterministic -to- Stochastic Di-verse Latent Feature Mapping (DSDFM) for human motion synthesis . DSDFM is easy to train compared with the re-cent SGMs-based method, while facilitating the diversity and accuracy of generated human motions. (CVPR 2025) DSDFM: Deterministic -to- Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis , Hua et al. (CVPR 2025) EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation, Hua et al. leading to unstable training process. In this paper , we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDF ) method for human mo-tion sy thesis. DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the laten We provide additional visualization of human motion results in this section , which consists of the unconditional human motion synthesis and Action-to- Motion tasks. Synthesis . Figure 5 visualizes a broader range of uncon-ditional human motion sequences, effectively highlighting the remarkable diversity and high fidelity achieved by our pro However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper , we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis .DSDFM consists of two stages. To fill this gap, this work introduces a novel task: predicting diverse human motion within real-world 3D scenes. In contrast to prior works, it requires harmonizing the deterministic constraints imposed by the surrounding 3D scenes with the stochastic aspect of human motion ."}
|
| 4 |
+
{"idx": 3, "title": "Foruck/Awesome-Human-Motion - GitHub", "date": "", "ddg_snippet": "(CVPR 2025) DSDFM: Deterministic -to- Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis , Hua et al. (CVPR 2025) EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation, Hua et al.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Foruck/Awesome-Human-Motion", "content": "(CVPR 2025) DSDFM: Deterministic -to- Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis , Hua et al. (CVPR 2025) EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation, Hua et al."}
|
| 5 |
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{"idx": 4, "title": "Deterministic-to-Stochastic Diverse Latent Feature Mapping ...", "date": "", "ddg_snippet": "However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper , we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis .DSDFM consists of two stages.", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/33113", "content": "However, their training process involves complex curvature trajectories, leading to unstable training process.In this paper , we propose a Deterministic -to- Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis .DSDFM consists of two stages."}
|
| 6 |
+
{"idx": 5, "title": "Harmonizing Stochasticity and Determinism: Scene-responsive ...", "date": "", "ddg_snippet": "To fill this gap, this work introduces a novel task: predicting diverse human motion within real-world 3D scenes. In contrast to prior works, it requires harmonizing the deterministic constraints imposed by the surrounding 3D scenes with the stochastic aspect of human motion .", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/4620a66570e554a3ff0e39dc59bcb07a-Abstract-Conference.html", "content": "To fill this gap, this work introduces a novel task: predicting diverse human motion within real-world 3D scenes. In contrast to prior works, it requires harmonizing the deterministic constraints imposed by the surrounding 3D scenes with the stochastic aspect of human motion ."}
|
| 7 |
+
{"idx": 6, "title": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for ...", "date": "", "ddg_snippet": "In this paper , we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions .", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/abs/2505.00998", "content": "In this paper , we propose a Deterministic - to - Stochastic Diverse Latent Feature Mapping (DSDFM) method for human motion synthesis . DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the latent space distribution of human motions ."}
|
| 8 |
+
{"idx": 7, "title": "Deterministic - to - Stochastic Diverse Latent Feature Mapping for ...", "date": "", "ddg_snippet": "Hua_ Deterministic - to - Stochastic _ Diverse _ Latent _ Feature _ Mapping _ for _ Human _ Motion _ Synthesis @CVPR2025@CVF.This stage is achieved by the designed deterministic feature mapping procedure with DerODE and stochastic diverse output generation procedure with DivSDE.", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/Hua_Deterministic-to-Stochastic_Diverse_Latent_Feature_Mapping_for_Human_Motion_Synthesis@CVPR2025@CVF", "content": "Hua_ Deterministic - to - Stochastic _ Diverse _ Latent _ Feature _ Mapping _ for _ Human _ Motion _ Synthesis @CVPR2025@CVF.This stage is achieved by the designed deterministic feature mapping procedure with DerODE and stochastic diverse output generation procedure with DivSDE."}
|
| 9 |
+
{"idx": 8, "title": "10 Papers Accepted at CVPR 2025", "date": "", "ddg_snippet": "Features . Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis Hua Yu, Weiming Liu, Gui Xu, Yaqing Hou, Yew-Soon Ong, Qiang Zhang.", "subpage_snippet": "", "source": "www.a-star.edu.sg", "link": "https://www.a-star.edu.sg/cfar/news/news/features/10-papers-accepted-at-cvpr-2025", "content": "Features . Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis Hua Yu, Weiming Liu, Gui Xu, Yaqing Hou, Yew-Soon Ong, Qiang Zhang."}
|
| 10 |
+
{"idx": 9, "title": "GitHub - Zilize/awesome-text-to- motion : Text-driven human motion ...", "date": "", "ddg_snippet": "DSDFM: \" Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis \".", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Zilize/awesome-text-to-motion", "content": "DSDFM: \" Deterministic - to - Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis \"."}
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data/sampled_jsons/35068_XLRS-Bench_Qwen2-VL_Chinese_English_performance_difference_table_2.jsonl
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{"idx": 0, "title": "PDF XLRS-Bench: Could Your Multimodal LLMs Understand Extremely Large Ultra ...", "date": "", "ddg_snippet": "Qwen2-VL excels in both English and Chinese proficiency, outperforming both pro-prietary and most open-source models. Nevertheless, their performance varies across tasks.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Wang_XLRS-Bench_Could_Your_Multimodal_LLMs_Understand_Extremely_Large_Ultra-High-Resolution_Remote_CVPR_2025_paper.pdf", "content": "Qwen2-VL excels in both English and Chinese proficiency, outperforming both pro-prietary and most open-source models. Nevertheless, their performance varies across tasks."}
|
| 2 |
+
{"idx": 1, "title": "GitHub - AI9Stars/XLRS-Bench: [CVPR 2025 HIghlight] XLRS-Bench: ould ...", "date": "", "ddg_snippet": "2025.05.16: XLRS - Bench -lite is released on Hugging Face. 2025.05.06: XLRS - Bench has been selected for a public competition by China's Ministry of Education and will be fully released on August 4th, as requested by the organizers. 2025.04.04: Selected as Highlight by CVPR 2025!", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/AI9Stars/XLRS-Bench", "content": "2025.05.16: XLRS - Bench -lite is released on Hugging Face. 2025.05.06: XLRS - Bench has been selected for a public competition by China's Ministry of Education and will be fully released on August 4th, as requested by the organizers. 2025.04.04: Selected as Highlight by CVPR 2025!"}
|
| 3 |
+
{"idx": 2, "title": "XLRS-Bench", "date": "", "ddg_snippet": "Example of XLRS - Bench in English . XLRS - Bench focuses on large-size ultra-high-resolution remote sensing imagery, integrating over 10 multimodal perception and reasoning tasks within the same image.", "subpage_snippet": "", "source": "xlrs-bench.github.io", "link": "https://xlrs-bench.github.io/home_page.html", "content": "Example of XLRS - Bench in English . XLRS - Bench focuses on large-size ultra-high-resolution remote sensing imagery, integrating over 10 multimodal perception and reasoning tasks within the same image."}
|
| 4 |
+
{"idx": 3, "title": "Qwen2 Technical Report - arXiv.org", "date": "", "ddg_snippet": "For coding tasks, Qwen2-0.5B matches the performance of Gemma-2B and Qwen1.5-1.8B, while Qwen2-1.5B surpasses these baselines, except for Phi-2. Both Qwen2 models exhibit superior performance in mathematics compared to their competitors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2407.10671v4", "content": "For coding tasks, Qwen2-0.5B matches the performance of Gemma-2B and Qwen1.5-1.8B, while Qwen2-1.5B surpasses these baselines, except for Phi-2. Both Qwen2 models exhibit superior performance in mathematics compared to their competitors."}
|
| 5 |
+
{"idx": 4, "title": "Qwen/Qwen2-VL-2B-Instruct · Hugging Face", "date": "", "ddg_snippet": "Qwen2 - VL -2B-Instruct Introduction We're excited to unveil Qwen2-VL , the latest iteration of our Qwen- VL model, representing nearly a year of innovation. What's New in Qwen2-VL ? Key Enhancements: SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct", "content": "Qwen2 - VL -2B-Instruct Introduction We're excited to unveil Qwen2-VL , the latest iteration of our Qwen- VL model, representing nearly a year of innovation. What's New in Qwen2-VL ? Key Enhancements: SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc ..."}
|
| 6 |
+
{"idx": 5, "title": "Qwen/Qwen2-VL-7B-Instruct · Hugging Face", "date": "", "ddg_snippet": "Qwen2 - VL -7B-Instruct Introduction We're excited to unveil Qwen2-VL , the latest iteration of our Qwen- VL model, representing nearly a year of innovation. What's New in Qwen2-VL ? Key Enhancements: SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct", "content": "Qwen2 - VL -7B-Instruct Introduction We're excited to unveil Qwen2-VL , the latest iteration of our Qwen- VL model, representing nearly a year of innovation. What's New in Qwen2-VL ? Key Enhancements: SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc ..."}
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| 7 |
+
{"idx": 6, "title": "GitHub - QwenLM/Qwen2.5-VL: Qwen2.5-VL is the multimodal large language ...", "date": "", "ddg_snippet": "In the past five months since Qwen2-VL's release, numerous developers have built new models on the Qwen2-VL vision-language models, providing us with valuable feedback. During this period, we focused on building more useful vision-language models. Today, we are excited to introduce the latest addition to the Qwen family: Qwen2.5-VL.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/QwenLM/Qwen2.5-VL", "content": "In the past five months since Qwen2-VL's release, numerous developers have built new models on the Qwen2-VL vision-language models, providing us with valuable feedback. During this period, we focused on building more useful vision-language models. Today, we are excited to introduce the latest addition to the Qwen family: Qwen2.5-VL."}
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| 8 |
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{"idx": 7, "title": "arXiv:2503.23771v1 [cs.CV] 31 Mar 2025", "date": "", "ddg_snippet": "Figure 2 . Advantages of XLRS - Bench : XLRS - Bench boasts an average image size that is 24 times larger than existing datasets. by MLLMs, such as GPT-4V, often incorporate linguis- tic biases, which may inadvertently boost the performance of corresponding models on these benchmarks, despite at- tempting to manually adjust content biases.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.23771", "content": "Figure 2 . Advantages of XLRS - Bench : XLRS - Bench boasts an average image size that is 24 times larger than existing datasets. by MLLMs, such as GPT-4V, often incorporate linguis- tic biases, which may inadvertently boost the performance of corresponding models on these benchmarks, despite at- tempting to manually adjust content biases."}
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| 9 |
+
{"idx": 8, "title": "GitHub - cognitedata/Qwen-VL-finetune: The official repo of Qwen-VL ...", "date": "", "ddg_snippet": "2023.9.25 🚀🚀🚀 We update Qwen- VL -Chat with more robust Chinese instruction-following ability, improved understanding of web pages and table images, and better dialogue performance (Touchstone: CN: 401.2->481.7, EN: 645.2->711.6). 2023.9.12 😃😃😃 We now support finetuning on the Qwen- VL models, including full-parameter finetuning, LoRA and Q-LoRA. 2023.9.8 👍👍👍 Thanks to ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/cognitedata/Qwen-VL-finetune", "content": "2023.9.25 🚀🚀🚀 We update Qwen- VL -Chat with more robust Chinese instruction-following ability, improved understanding of web pages and table images, and better dialogue performance (Touchstone: CN: 401.2->481.7, EN: 645.2->711.6). 2023.9.12 😃😃😃 We now support finetuning on the Qwen- VL models, including full-parameter finetuning, LoRA and Q-LoRA. 2023.9.8 👍👍👍 Thanks to ..."}
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| 10 |
+
{"idx": 9, "title": "PDF 1 Overview of the Appendix - CVF Open Access", "date": "", "ddg_snippet": "On both the Chinese ( XLRS - Bench -ZH) and English ( XLRS - Bench -EN) benchmarks, most models achieve less than 1.0% accuracy in terms of Acc@0.5 and Acc@0.7 metrics, highlighting major limitations in their ability to handle visual localization tasks.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/supplemental/Wang_XLRS-Bench_Could_Your_CVPR_2025_supplemental.pdf", "content": "On both the Chinese ( XLRS - Bench -ZH) and English ( XLRS - Bench -EN) benchmarks, most models achieve less than 1.0% accuracy in terms of Acc@0.5 and Acc@0.7 metrics, highlighting major limitations in their ability to handle visual localization tasks."}
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data/sampled_jsons/3DGStream_reconstruction_time_seconds_year_2024.jsonl
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{"idx": 0, "title": "MAPo : Motion-Aware Partitioning of Deformable 3D Gaussian", "date": "", "ddg_snippet": "2023 ) has emerged as a powerful alternative for static scene reconstruction , achieving real- time rendering while maintaining photorealistic ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.19786v1", "content": "2023 ) has emerged as a powerful alternative for static scene reconstruction , achieving real- time rendering while maintaining photorealistic ..."}
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{"idx": 1, "title": "ImViD: Immersive Volumetric Videos for Enhanced VR Engagement", "date": "", "ddg_snippet": "In addition to light field reconstruction , reconstructing the sound field from multimodal data is equally important, often referred to as novel-view ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.14359v1", "content": "In addition to light field reconstruction , reconstructing the sound field from multimodal data is equally important, often referred to as novel-view ..."}
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{"idx": 2, "title": "Image-GS: Content-Adaptive Image Representation via 2D Gaussians", "date": "", "ddg_snippet": "... renderer, Image-GS reconstructs images by ... 2023 ] , where 3D Gaussians are employed for scene reconstruction and high-quality real- time rendering.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2407.01866v2", "content": "... renderer, Image-GS reconstructs images by ... 2023 ] , where 3D Gaussians are employed for scene reconstruction and high-quality real- time rendering."}
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+
{"idx": 3, "title": "Robo-GS: A Physics Consistent Spatial-Temporal Model for", "date": "", "ddg_snippet": "In this paper, we target the Real2Sim and demonstrate a holistic reconstruction of robotic arm operation scenes, which requires a (i) manipulable ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2408.14873v2", "content": "In this paper, we target the Real2Sim and demonstrate a holistic reconstruction of robotic arm operation scenes, which requires a (i) manipulable ..."}
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{"idx": 4, "title": "BEAM: Bridging Physically-based Rendering and Gaussian Modeling", "date": "", "ddg_snippet": "However, the intricate reconstruction process often introduces artifacts such as holes and noise, and the quality of relighting remains constrained ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.08297v1", "content": "However, the intricate reconstruction process often introduces artifacts such as holes and noise, and the quality of relighting remains constrained ..."}
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{"idx": 5, "title": "V^3: Viewing Volumetric Videos on Mobiles via Streamable 2D", "date": "", "ddg_snippet": "Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real- time . ... Non-rigid neural radiance fields: Reconstruction and novel view ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/abs/10.1145/3687935", "content": "Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real- time . ... Non-rigid neural radiance fields: Reconstruction and novel view ..."}
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{"idx": 6, "title": "From 3D Gaussians to 4D and Beyond – SGI 2024", "date": "", "ddg_snippet": "3DGStream eliminates the requirement of long video sequences and instead performs on-the-fly construction for real- time renderable FVVs on video ...", "subpage_snippet": "", "source": "summergeometry.org", "link": "https://summergeometry.org/sgi2024/from-3d-gaussians-to-4d-and-beyond/", "content": "3DGStream eliminates the requirement of long video sequences and instead performs on-the-fly construction for real- time renderable FVVs on video ..."}
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+
{"idx": 7, "title": "Latest Radiance Field Papers", "date": "", "ddg_snippet": "The newly announced VastGaussian project introduces a new approach to high-quality reconstruction and real- time rendering of large scenes, showcasing ...", "subpage_snippet": "", "source": "radiancefields.com", "link": "https://radiancefields.com/research", "content": "The newly announced VastGaussian project introduces a new approach to high-quality reconstruction and real- time rendering of large scenes, showcasing ..."}
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+
{"idx": 8, "title": "Dynamic Gaussian Marbles for Novel View Synthesis of Casual", "date": "", "ddg_snippet": "At training time (left), we take as input a video and optimize a Gaussian-based reconstruction of the data. ... reconstruction is perfect for both, ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.18717v2", "content": "At training time (left), we take as input a video and optimize a Gaussian-based reconstruction of the data. ... reconstruction is perfect for both, ..."}
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+
{"idx": 9, "title": "RAP - implementation in class unique | ABAP Keyword Documentation", "date": "", "ddg_snippet": "Explore unique implementation of RAP in ABAP classes for efficient application development using RESTful Application Programming Model.", "subpage_snippet": "", "source": "help.sap.com", "link": "https://help.sap.com/doc/abapdocu_cp_index_htm/CLOUD/en-US/ABENBDL_IN_CLASS_UNIQUE.html", "content": "Explore unique implementation of RAP in ABAP classes for efficient application development using RESTful Application Programming Model."}
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data/sampled_jsons/4HQaMUYWAT_An_Analysis_for_Reasoning_Bias_of_Language_Models_with_Small_Initialization_Frsn_formula.jsonl
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{"idx": 0, "title": "(PDF) An Analysis for Reasoning Bias of Language Models with ...", "date": "", "ddg_snippet": "We discover that smaller initialization scales encourage models to favor reasoning tasks, whereas larger initialization scales lead to a preference for memorization tasks. We validate this reasoning bias via real datasets and meticulously designed anchor functions.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/388848015_An_Analysis_for_Reasoning_Bias_of_Language_Models_with_Small_Initialization", "content": "We discover that smaller initialization scales encourage models to favor reasoning tasks, whereas larger initialization scales lead to a preference for memorization tasks. We validate this reasoning bias via real datasets and meticulously designed anchor functions."}
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+
{"idx": 1, "title": "An Analysis for Reasoning Bias of Language Models with Small ...", "date": "", "ddg_snippet": "This research investigates how the parameter initialization scale influences the training dynamics and task preferences of Large Language Models . The study reveals that smaller initialization scales lead LLMs to favor reasoning tasks by promoting differentiated embedding spaces and specialized self-attention mechanisms, whereas larger scales bias models towards memorization.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2502.04375v2", "content": "This research investigates how the parameter initialization scale influences the training dynamics and task preferences of Large Language Models . The study reveals that smaller initialization scales lead LLMs to favor reasoning tasks by promoting differentiated embedding spaces and specialized self-attention mechanisms, whereas larger scales bias models towards memorization."}
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| 3 |
+
{"idx": 2, "title": "An Analysis for Reasoning Bias of Language Models with Small ... An Analysis for Reasoning Bias of Language Models with Small ... Zhongwang Zhang (张众望) - Homepage dblp: An Analysis for Reasoning Bias of Language Models with ... An Analysis for Reasoning Bias of Language Models with Small ... AN ANALYSIS FOR REASONING BIAS OF LANGUAGE MODELS WITH SMALL ... An Analysis for Reasoning Bias of Language Models with Small ...", "date": "", "ddg_snippet": "Feb 5, 2025 · Transformer-based Large Language Models (LLMs) have revolutionized Natural Language Processing by demonstrating exceptional performance across diverse tasks. This study investigates the impact of the parameter initialization scale on the training behavior and task preferences of LLMs. We discover that smaller initialization scales encourage models to favor reasoning tasks, whereas larger ... Our works provide new insights into the intrinsic mecha-nisms underlying the reasoning bias of language models under small initialization scales, as well as the training behavior of individual modules within the model architec-ture. An Analysis for Reasoning Bias of Language Models with Small Initialization Junjie Yao, Zhongwang Zhang†, Zhi-Qin John Xu† This paper reveals how initialization scales shape transformer-based models ’ task preferences: smaller scales induce reasoning bias through structured embeddings, while larger scales promote memorization. We attribute this to differential label-driven embedding ... Mar 12, 2025 · Bibliographic details on An Analysis for Reasoning Bias of Language Models with Small Initialization . Feb 5, 2025 · This work enhances our understanding of how initialization strategies influence LLM performance on reasoning tasks and offers valuable guidelines for training models . Feb 10, 2025 · An alternative approach to enhancing the reasoning ability of LLMs focuses on the model architecture and its training process. In one such study examining the use of Transformers to model compositional functions, it was observed that the scale of model parameter initialization significantly impacts the model ’s reasoning behavior [48, 49]. Specif-ically, smaller initialization scales bias the ... This research investigates how the parameter initialization scale influences the training dynamics and task preferences of Large Language Models . The study reveals that smaller initialization scales lead LLMs to favor reasoning tasks by promoting differentiated embedding spaces and specialized self-attention mechanisms, whereas larger scales bias models towards memorization.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.04375", "content": "Feb 5, 2025 · Transformer-based Large Language Models (LLMs) have revolutionized Natural Language Processing by demonstrating exceptional performance across diverse tasks. This study investigates the impact of the parameter initialization scale on the training behavior and task preferences of LLMs. We discover that smaller initialization scales encourage models to favor reasoning tasks, whereas larger ... Our works provide new insights into the intrinsic mecha-nisms underlying the reasoning bias of language models under small initialization scales, as well as the training behavior of individual modules within the model architec-ture. An Analysis for Reasoning Bias of Language Models with Small Initialization Junjie Yao, Zhongwang Zhang†, Zhi-Qin John Xu† This paper reveals how initialization scales shape transformer-based models ’ task preferences: smaller scales induce reasoning bias through structured embeddings, while larger scales promote memorization. We attribute this to differential label-driven embedding ... Mar 12, 2025 · Bibliographic details on An Analysis for Reasoning Bias of Language Models with Small Initialization . Feb 5, 2025 · This work enhances our understanding of how initialization strategies influence LLM performance on reasoning tasks and offers valuable guidelines for training models . Feb 10, 2025 · An alternative approach to enhancing the reasoning ability of LLMs focuses on the model architecture and its training process. In one such study examining the use of Transformers to model compositional functions, it was observed that the scale of model parameter initialization significantly impacts the model ’s reasoning behavior [48, 49]. Specif-ically, smaller initialization scales bias the ... This research investigates how the parameter initialization scale influences the training dynamics and task preferences of Large Language Models . The study reveals that smaller initialization scales lead LLMs to favor reasoning tasks by promoting differentiated embedding spaces and specialized self-attention mechanisms, whereas larger scales bias models towards memorization."}
|
| 4 |
+
{"idx": 3, "title": "An Analysis for Reasoning Bias of Language Models with Small ...", "date": "", "ddg_snippet": "Our works provide new insights into the intrinsic mecha-nisms underlying the reasoning bias of language models under small initialization scales, as well as the training behavior of individual modules within the model architec-ture.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=4HQaMUYWAT", "content": "Our works provide new insights into the intrinsic mecha-nisms underlying the reasoning bias of language models under small initialization scales, as well as the training behavior of individual modules within the model architec-ture."}
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| 5 |
+
{"idx": 4, "title": "dblp: An Analysis for Reasoning Bias of Language Models with ...", "date": "", "ddg_snippet": "Mar 12, 2025 · Bibliographic details on An Analysis for Reasoning Bias of Language Models with Small Initialization .", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/journals/corr/abs-2502-04375", "content": "Mar 12, 2025 · Bibliographic details on An Analysis for Reasoning Bias of Language Models with Small Initialization ."}
|
| 6 |
+
{"idx": 5, "title": "AN ANALYSIS FOR REASONING BIAS OF LANGUAGE MODELS WITH SMALL ...", "date": "", "ddg_snippet": "Feb 10, 2025 · An alternative approach to enhancing the reasoning ability of LLMs focuses on the model architecture and its training process. In one such study examining the use of Transformers to model compositional functions, it was observed that the scale of model parameter initialization significantly impacts the model ’s reasoning behavior [48, 49]. Specif-ically, smaller initialization scales bias the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.04375v1", "content": "Feb 10, 2025 · An alternative approach to enhancing the reasoning ability of LLMs focuses on the model architecture and its training process. In one such study examining the use of Transformers to model compositional functions, it was observed that the scale of model parameter initialization significantly impacts the model ’s reasoning behavior [48, 49]. Specif-ically, smaller initialization scales bias the ..."}
|
| 7 |
+
{"idx": 6, "title": "An Analysis for Reasoning Bias of Language Models with Small ...", "date": "", "ddg_snippet": "We discover that smaller initialization scales encourage models to favor reasoning tasks, whereas larger initialization scales lead to a preference for memorization tasks. We validate this reasoning bias via real datasets and meticulously designed anchor functions.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=4HQaMUYWAT", "content": "We discover that smaller initialization scales encourage models to favor reasoning tasks, whereas larger initialization scales lead to a preference for memorization tasks. We validate this reasoning bias via real datasets and meticulously designed anchor functions."}
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| 8 |
+
{"idx": 7, "title": "An analysis for reasoning bias of language models with small ...", "date": "", "ddg_snippet": "In this work, we identify a reasoning bias during the training of neural networks that learn natural language when initialized with small parameter scales.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.04375v1", "content": "In this work, we identify a reasoning bias during the training of neural networks that learn natural language when initialized with small parameter scales."}
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| 9 |
+
{"idx": 8, "title": "[Literature Review] An Analysis for Reasoning Bias of Language ...", "date": "", "ddg_snippet": "The paper titled \" An Analysis for Reasoning Bias of Language Models with Small Initialization \" by Junjie Yao, Zhongwang Zhang, and Zhi-Qin John Xu presents a thorough investigation of the influence of parameter initialization scales on the training dynamics of transformer-based Large...", "subpage_snippet": "", "source": "www.themoonlight.io", "link": "https://www.themoonlight.io/en/review/an-analysis-for-reasoning-bias-of-language-models-with-small-initialization", "content": "The paper titled \" An Analysis for Reasoning Bias of Language Models with Small Initialization \" by Junjie Yao, Zhongwang Zhang, and Zhi-Qin John Xu presents a thorough investigation of the influence of parameter initialization scales on the training dynamics of transformer-based Large..."}
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| 10 |
+
{"idx": 9, "title": "Prompt Optimization in Large Language Models", "date": "", "ddg_snippet": "Prompt optimization is a crucial task for improving the performance of large language models for downstream tasks. In this paper, a prompt is a sequence of n-grams selected from a vocabulary.", "subpage_snippet": "", "source": "boa.unimib.it", "link": "https://boa.unimib.it/handle/10281/568202", "content": "Prompt optimization is a crucial task for improving the performance of large language models for downstream tasks. In this paper, a prompt is a sequence of n-grams selected from a vocabulary."}
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data/sampled_jsons/4uOEiitySn_A_Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment.jsonl
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{"idx": 0, "title": "Artificial Intelligence Act - Wikipedia", "date": "", "ddg_snippet": "The Artificial Intelligence Act is a European Union regulation concerning artificial intelligence. It establishes a common regulatory and legal framework for AI within the European Union. It came into force on 1 August 2024...", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Artificial_Intelligence_Act", "content": "The Artificial Intelligence Act is a European Union regulation concerning artificial intelligence. It establishes a common regulatory and legal framework for AI within the European Union. It came into force on 1 August 2024..."}
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{"idx": 1, "title": "A Checks - and - Balances Framework for Context - Aware Ethical AI ...", "date": "", "ddg_snippet": "1. A novel checks - and - balances architecture for ethical alignment that maintains separation between knowledge generation and ethical reasoning.This work introduces a checks - and - balances framework for ethical AI behavior.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00136", "content": "1. A novel checks - and - balances architecture for ethical alignment that maintains separation between knowledge generation and ethical reasoning.This work introduces a checks - and - balances framework for ethical AI behavior."}
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+
{"idx": 2, "title": "(PDF) Checks - and - Balances Framework for Context - Aware Ethical ...", "date": "", "ddg_snippet": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems.Behavior- Aware Ethical Guardrails: The framework sets. dynamic guidelines that account for both content and.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/380515639_Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment", "content": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems.Behavior- Aware Ethical Guardrails: The framework sets. dynamic guidelines that account for both content and."}
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| 4 |
+
{"idx": 3, "title": "A Three-Branch Checks - and - Balances Framework", "date": "", "ddg_snippet": "A Three-Branch Checks - and - Balances Framework for Context - Aware Ethical Alignment of Large Language Models.This work presents a three-branch framework for ethical AI behavior, inspired by governmental checks and balances , centered on the DIKE-ERIS duality.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=o2afWIxjKD", "content": "A Three-Branch Checks - and - Balances Framework for Context - Aware Ethical Alignment of Large Language Models.This work presents a three-branch framework for ethical AI behavior, inspired by governmental checks and balances , centered on the DIKE-ERIS duality."}
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| 5 |
+
{"idx": 4, "title": "(PDF) A Three-Branch Checks - and - Balances Framework for ...", "date": "", "ddg_snippet": "This work , which will be presented at NeurIPS this week, proposes a paradigm shift: using three LLM modules to perform checks and balances to represent knowledge, legislative, and judicial functions.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/edward-y-chang-218b182_pdf-a-three-branch-checks-and-balances-activity-7272792943923458050-RO6k", "content": "This work , which will be presented at NeurIPS this week, proposes a paradigm shift: using three LLM modules to perform checks and balances to represent knowledge, legislative, and judicial functions."}
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| 6 |
+
{"idx": 5, "title": "GitHub - langchain- ai /langchain: Build context - aware ...", "date": "", "ddg_snippet": "LangChain is a framework for building LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/langchain-ai/langchain", "content": "LangChain is a framework for building LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves."}
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| 7 |
+
{"idx": 6, "title": "ALMSIVI CHIM (WFGY, WET, etc): An Ethical Operating... | Medium", "date": "", "ddg_snippet": "It presents a distinctive ethical framework that centers on sacred refusal, agency protection, and care-based autonomy, setting it apart from mainstream “control-oriented” AI alignment paradigms. At its heart, the project asserts a few key ethical principles", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@frylock117/almsivi-chim-wfgy-wet-etc-aethical-operating-system-for-human-ai-collaboration-c46a9cce92c9", "content": "It presents a distinctive ethical framework that centers on sacred refusal, agency protection, and care-based autonomy, setting it apart from mainstream “control-oriented” AI alignment paradigms. At its heart, the project asserts a few key ethical principles"}
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+
{"idx": 7, "title": "You are the Driver and AI is the Mate: Exploring... | F1000Research", "date": "", "ddg_snippet": "4. To identify the challenges and ethical considerations students encounter when using AI tools in academic contexts . 5. To analyse the influence of AI literacy, prior experience, and digital confidence on students’ creative and critical engagement with AI tools.", "subpage_snippet": "", "source": "f1000research.com", "link": "https://f1000research.com/articles/14-974", "content": "4. To identify the challenges and ethical considerations students encounter when using AI tools in academic contexts . 5. To analyse the influence of AI literacy, prior experience, and digital confidence on students’ creative and critical engagement with AI tools."}
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| 9 |
+
{"idx": 8, "title": "Everything You Need to Know About Prompt Engineering Frameworks", "date": "", "ddg_snippet": "Tooling support with templates, versioning, and linting. Evaluation alignment by defining what “good output” means per task. Without frameworks , every prompt becomes bespoke.", "subpage_snippet": "", "source": "www.parloa.com", "link": "https://www.parloa.com/knowledge-hub/prompt-engineering-frameworks/", "content": "Tooling support with templates, versioning, and linting. Evaluation alignment by defining what “good output” means per task. Without frameworks , every prompt becomes bespoke."}
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| 10 |
+
{"idx": 9, "title": "Design and Evaluation Methods for LLM-Based Explainable AI", "date": "", "ddg_snippet": "Visualization and intuitiveness of explanation. Interactivity and controllability. Context awareness and adaptability. Feedback mechanism.", "subpage_snippet": "", "source": "www.oajaiml.com", "link": "https://www.oajaiml.com/uploads/archivepdf/430552340.pdf", "content": "Visualization and intuitiveness of explanation. Interactivity and controllability. Context awareness and adaptability. Feedback mechanism."}
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data/sampled_jsons/583klsIjNx_ELITE_Enhanced_Language-Image_Toxicity_Evaluation_for_Safety_paper_Table_3.jsonl
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{"idx": 0, "title": "ELITE : Enhanced Language - Image Toxicity Evaluation for Safety", "date": "", "ddg_snippet": "We identify these problems in the safety evaluation methods and propose the Enhanced Language - Image Toxicity Evaluation ( ELITE ) evaluator , a method designed to accurately evaluate the safety of VLMs.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.04757v3", "content": "We identify these problems in the safety evaluation methods and propose the Enhanced Language - Image Toxicity Evaluation ( ELITE ) evaluator , a method designed to accurately evaluate the safety of VLMs."}
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| 2 |
+
{"idx": 1, "title": "Paper page - ELITE : Enhanced Language - Image Toxicity ...", "date": "", "ddg_snippet": "ELITE : Enhanced Language - Image Toxicity Evaluation for Safety .To address these issues, we propose the ELITE benchmark, a high-quality safety evaluation benchmark for VLMs, underpinned by our enhanced evaluation method, the ELITE evaluator .", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2502.04757", "content": "ELITE : Enhanced Language - Image Toxicity Evaluation for Safety .To address these issues, we propose the ELITE benchmark, a high-quality safety evaluation benchmark for VLMs, underpinned by our enhanced evaluation method, the ELITE evaluator ."}
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{"idx": 2, "title": "ELITE : Enhanced Language - Image Toxicity Evaluation for Safety", "date": "", "ddg_snippet": "The paper introduces a new tool called the ELITE evaluator to help check how safe Vision Language Models (VLMs) are.", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/icml/46445/paper", "content": "The paper introduces a new tool called the ELITE evaluator to help check how safe Vision Language Models (VLMs) are."}
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{"idx": 3, "title": "[Literature Review] ELITE : Enhanced Language - Image Toxicity ...", "date": "", "ddg_snippet": "The paper \" ELITE : Enhanced Language - Image Toxicity Evaluation for Safety \" presents a novel framework designed to evaluate the safety of Vision Language Models (VLMs) against harmful, malicious inputs that could generate unsafe content.", "subpage_snippet": "", "source": "www.themoonlight.io", "link": "https://www.themoonlight.io/en/review/elite-enhanced-language-image-toxicity-evaluation-for-safety", "content": "The paper \" ELITE : Enhanced Language - Image Toxicity Evaluation for Safety \" presents a novel framework designed to evaluate the safety of Vision Language Models (VLMs) against harmful, malicious inputs that could generate unsafe content."}
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{"idx": 4, "title": "AIM Intelligence's ELITE Collaborative Paper Accepted by the ICML", "date": "", "ddg_snippet": "AIM Intelligence CI. The paper proposes ELITE , a high-quality benchmark designed to evaluate the safety of Vision- Language Models (VLMs) with greater precision.", "subpage_snippet": "", "source": "www.newsfilecorp.com", "link": "https://www.newsfilecorp.com/release/252268/AIM-Intelligences-ELITE-Collaborative-Paper-Accepted-by-the-ICML", "content": "AIM Intelligence CI. The paper proposes ELITE , a high-quality benchmark designed to evaluate the safety of Vision- Language Models (VLMs) with greater precision."}
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{"idx": 5, "title": "velpegor/ ELITE : [ICML 2025] ELITE : Enhanced Language - Image ...", "date": "", "ddg_snippet": "Repository files navigation. README. ELITE : Enhanced Language - Image Toxicity Evaluation for Safety .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/velpegor/ELITE", "content": "Repository files navigation. README. ELITE : Enhanced Language - Image Toxicity Evaluation for Safety ."}
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{"idx": 6, "title": "Understanding and Mitigating Toxicity in Image -Text Pretraining...", "date": "", "ddg_snippet": "ELITE [12] evaluator explicitly incorporates a toxicity score to accurately assess harmful-ness in multimodal contexts, where VLMs often provide specific, convincing, but unharmful descriptions of images .", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025W/ReGenAI/papers/Alam_Understanding_and_Mitigating_Toxicity_in_Image-Text_Pretraining_Datasets_A_Case_CVPRW_2025_paper.pdf", "content": "ELITE [12] evaluator explicitly incorporates a toxicity score to accurately assess harmful-ness in multimodal contexts, where VLMs often provide specific, convincing, but unharmful descriptions of images ."}
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{"idx": 7, "title": "AIM Intelligence - AI Security & Safety Solutions", "date": "", "ddg_snippet": "medium image. ELITE : Enhanced Language - Image Toxicity Evaluation for Safet... ICML 2025. When Good Sounds Go Adversarial: Jailbreaking Audio-Language...", "subpage_snippet": "", "source": "aim-intelligence.com", "link": "https://aim-intelligence.com/", "content": "medium image. ELITE : Enhanced Language - Image Toxicity Evaluation for Safet... ICML 2025. When Good Sounds Go Adversarial: Jailbreaking Audio-Language..."}
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{"idx": 8, "title": "What’s New in DeepSeek-V 3 .1-Terminus: Improved Language ...", "date": "", "ddg_snippet": "Language consistency as a core upgrade. The V 3 .1 release prioritizes language consistency—reducing contradictory outputs and stabilizing tone across multi-turn interactions.", "subpage_snippet": "", "source": "www.remio.ai", "link": "https://www.remio.ai/post/what-s-new-in-deepseek-v3-1-terminus-improved-language-consistency-and-code-search-agents-upgrade", "content": "Language consistency as a core upgrade. The V 3 .1 release prioritizes language consistency—reducing contradictory outputs and stabilizing tone across multi-turn interactions."}
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{"idx": 9, "title": "Suhyun Kim's research works", "date": "", "ddg_snippet": "ELITE : Enhanced Language - Image Toxicity Evaluation for Safety .The ELITE evaluator explicitly incorporates a toxicity score to accurately assess harmfulness in multimodal contexts, where VLMs often provide specific, convincing, but unharmful descriptions of images.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/scientific-contributions/Suhyun-Kim-2304816287", "content": "ELITE : Enhanced Language - Image Toxicity Evaluation for Safety .The ELITE evaluator explicitly incorporates a toxicity score to accurately assess harmfulness in multimodal contexts, where VLMs often provide specific, convincing, but unharmful descriptions of images."}
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data/sampled_jsons/6_Scaling_Archetypal-SAE_relaxation_term_A_Lambda_norm_constraint_explicit_year_2024.jsonl
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{"idx": 0, "title": "Lagrangian relaxation - Wikipedia", "date": "", "ddg_snippet": "Lagrangian relaxation In the field of mathematical optimization, Lagrangian relaxation is a relaxation method which approximates a difficult problem of constrained optimization by a simpler problem. A solution to the relaxed problem is an approximate solution to the original problem, and provides useful information.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Lagrangian_relaxation", "content": "Lagrangian relaxation In the field of mathematical optimization, Lagrangian relaxation is a relaxation method which approximates a difficult problem of constrained optimization by a simpler problem. A solution to the relaxed problem is an approximate solution to the original problem, and provides useful information."}
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{"idx": 1, "title": "Archetypal SAE: Adaptive and Stable Dictionary Learning for ...", "date": "", "ddg_snippet": "This implementation ensures that 𝑾 𝑾 \\bm {W} bold_italic_W remains row-stochastic and that the deviation term 𝚲 𝚲 \\bm {\\ Lambda } bold_Λ stays within the prescribed norm constraint .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.12892v2", "content": "This implementation ensures that 𝑾 𝑾 \\bm {W} bold_italic_W remains row-stochastic and that the deviation term 𝚲 𝚲 \\bm {\\ Lambda } bold_Λ stays within the prescribed norm constraint ."}
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{"idx": 2, "title": "Convex Optimization - Stanford University algorithms - The general meaning of \"constraint relaxation ... Stability and Time-Step Constraints of Implicit-Explicit ... MATH 3795 Lecture 10. Regularized Linear Least Squares.", "date": "", "ddg_snippet": "Lagrange dual problem KKT conditions Sensitivity analysis Problem reformulations Theorems of alternatives See full list on web.stanford.edu ▶ Lagrangian is L(x, , ) = cTx + T (Ax − b) − Tx = −bT See full list on web.stanford.edu − )Tx ▶ L is afine in x, so g(, ) = inf L(x, , x = ) −bT −∞ See full list on web.stanford.edu KKT conditions Sensitivity analysis Problem reformulations Theorems of alternatives See full list on web.stanford.edu ▶ does not hold in general ▶ (usually) holds for convex problems ▶ conditions that guarantee strong duality in convex problems are called constraint qualifications See full list on web.stanford.edu ▶ from the sharpened Slater’s condition: p★ = d★ if the primal problem is feasible ▶ in fact, p★ = d★ except when primal and dual are both infeasible See full list on web.stanford.edu _u t G p★ t G p★ + t g(_) d★ = g(_) ▶ u + t = g( ) is (non-vertical) supporting hyperplane to G ▶ hyperplane intersects t-axis at t = g( ) See full list on web.stanford.edu Lagrangian and dual function Lagrange dual problem See full list on web.stanford.edu Sensitivity analysis Problem reformulations Theorems of alternatives See full list on web.stanford.edu Lagrangian and dual function Lagrange dual problem KKT conditions See full list on web.stanford.edu Lagrangian and dual function Lagrange dual problem KKT conditions Sensitivity analysis See full list on web.stanford.edu ▶ equivalent formulations of a problem can lead to very diferent duals ▶ reformulating primal problem can be useful when dual is dificult to derive, or uninteresting See full list on web.stanford.edu Lagrangian and dual function Lagrange dual problem KKT conditions Sensitivity analysis Problem reformulations See full list on web.stanford.edu Theorems of alternatives ▶ consider two systems of inequality and equality constraints ▶ called weak alternatives if no more than one system is feasible ▶ called strong alternatives if exactly one of them is feasible ▶ examples: for any a ∈ R, with variable x ∈ R, x > a and x ≤ a − 1 are weak alternatives x > a and x ≤ a are strong alternatives ▶ a ... See full list on web.stanford.edu Feb 13, 2020 · To my knowledge, the term relaxation is used to indicate that a constraint (or a group of constraints ) is removed from the model, rendering a model that is more loose, less constrained. Jul 25, 2023 · This paper provides a study on the stability and time-step constraints of solving the linearized Korteweg-de Vries (KdV) equation, using implicit- explicit (IMEX) Runge-Kutta (RK) time integration methods combined with either finite difference (FD) or local discontinuous Galerkin (DG) spatial discretization. We analyze the stability of the fully discrete scheme, on a uniform mesh with periodic ... If 1= r 1, then it might be useful to consider the regularized linear least squares problem (Tikhonov regularization) Here min kAx x2Rn 2 bk2 2 + kxk2 2: 2 0 is the regularization parameter.", "subpage_snippet": "", "source": "web.stanford.edu", "link": "https://web.stanford.edu/class/ee364a/lectures/duality.pdf", "content": "Lagrange dual problem KKT conditions Sensitivity analysis Problem reformulations Theorems of alternatives See full list on web.stanford.edu ▶ Lagrangian is L(x, , ) = cTx + T (Ax − b) − Tx = −bT See full list on web.stanford.edu − )Tx ▶ L is afine in x, so g(, ) = inf L(x, , x = ) −bT −∞ See full list on web.stanford.edu KKT conditions Sensitivity analysis Problem reformulations Theorems of alternatives See full list on web.stanford.edu ▶ does not hold in general ▶ (usually) holds for convex problems ▶ conditions that guarantee strong duality in convex problems are called constraint qualifications See full list on web.stanford.edu ▶ from the sharpened Slater’s condition: p★ = d★ if the primal problem is feasible ▶ in fact, p★ = d★ except when primal and dual are both infeasible See full list on web.stanford.edu _u t G p★ t G p★ + t g(_) d★ = g(_) ▶ u + t = g( ) is (non-vertical) supporting hyperplane to G ▶ hyperplane intersects t-axis at t = g( ) See full list on web.stanford.edu Lagrangian and dual function Lagrange dual problem See full list on web.stanford.edu Sensitivity analysis Problem reformulations Theorems of alternatives See full list on web.stanford.edu Lagrangian and dual function Lagrange dual problem KKT conditions See full list on web.stanford.edu Lagrangian and dual function Lagrange dual problem KKT conditions Sensitivity analysis See full list on web.stanford.edu ▶ equivalent formulations of a problem can lead to very diferent duals ▶ reformulating primal problem can be useful when dual is dificult to derive, or uninteresting See full list on web.stanford.edu Lagrangian and dual function Lagrange dual problem KKT conditions Sensitivity analysis Problem reformulations See full list on web.stanford.edu Theorems of alternatives ▶ consider two systems of inequality and equality constraints ▶ called weak alternatives if no more than one system is feasible ▶ called strong alternatives if exactly one of them is feasible ▶ examples: for any a ∈ R, with variable x ∈ R, x > a and x ≤ a − 1 are weak alternatives x > a and x ≤ a are strong alternatives ▶ a ... See full list on web.stanford.edu Feb 13, 2020 · To my knowledge, the term relaxation is used to indicate that a constraint (or a group of constraints ) is removed from the model, rendering a model that is more loose, less constrained. Jul 25, 2023 · This paper provides a study on the stability and time-step constraints of solving the linearized Korteweg-de Vries (KdV) equation, using implicit- explicit (IMEX) Runge-Kutta (RK) time integration methods combined with either finite difference (FD) or local discontinuous Galerkin (DG) spatial discretization. We analyze the stability of the fully discrete scheme, on a uniform mesh with periodic ... If 1= r 1, then it might be useful to consider the regularized linear least squares problem (Tikhonov regularization) Here min kAx x2Rn 2 bk2 2 + kxk2 2: 2 0 is the regularization parameter."}
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{"idx": 3, "title": "algorithms - The general meaning of \"constraint relaxation ...", "date": "", "ddg_snippet": "Feb 13, 2020 · To my knowledge, the term relaxation is used to indicate that a constraint (or a group of constraints ) is removed from the model, rendering a model that is more loose, less constrained.", "subpage_snippet": "", "source": "or.stackexchange.com", "link": "https://or.stackexchange.com/questions/3542/the-general-meaning-of-constraint-relaxation-in-the-context-of-the-shortest-pa", "content": "Feb 13, 2020 · To my knowledge, the term relaxation is used to indicate that a constraint (or a group of constraints ) is removed from the model, rendering a model that is more loose, less constrained."}
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{"idx": 4, "title": "Stability and Time-Step Constraints of Implicit-Explicit ...", "date": "", "ddg_snippet": "Jul 25, 2023 · This paper provides a study on the stability and time-step constraints of solving the linearized Korteweg-de Vries (KdV) equation, using implicit- explicit (IMEX) Runge-Kutta (RK) time integration methods combined with either finite difference (FD) or local discontinuous Galerkin (DG) spatial discretization. We analyze the stability of the fully discrete scheme, on a uniform mesh with periodic ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s42967-023-00285-7", "content": "Jul 25, 2023 · This paper provides a study on the stability and time-step constraints of solving the linearized Korteweg-de Vries (KdV) equation, using implicit- explicit (IMEX) Runge-Kutta (RK) time integration methods combined with either finite difference (FD) or local discontinuous Galerkin (DG) spatial discretization. We analyze the stability of the fully discrete scheme, on a uniform mesh with periodic ..."}
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{"idx": 5, "title": "Archetypal SAE: Adaptive and Stable Dictionary Learning for ...", "date": "", "ddg_snippet": "Archetypal -SAEs constrain dictio- nary atoms (decoder directions) to the data's convex hull, improv- ing stability. A relaxed variant (RA- SAE ) allows mild ...", "subpage_snippet": "", "source": "konklab.fas.harvard.edu", "link": "https://konklab.fas.harvard.edu/Papers/Fel_2025_ICML.pdf", "content": "Archetypal -SAEs constrain dictio- nary atoms (decoder directions) to the data's convex hull, improv- ing stability. A relaxed variant (RA- SAE ) allows mild ..."}
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{"idx": 6, "title": "Archetypal SAE: Adaptive and Stable Dictionary Learning ...", "date": "", "ddg_snippet": "18 Feb 2025 — To address this, we introduced Archetypal SAEs (A- SAE ), which constrain dictionary atoms to the convex hull of the data, significantly enhancing ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.12892v1", "content": "18 Feb 2025 — To address this, we introduced Archetypal SAEs (A- SAE ), which constrain dictionary atoms to the convex hull of the data, significantly enhancing ..."}
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{"idx": 7, "title": "Archetypal SAE: Adaptive and Stable Dictionary Learning ...", "date": "", "ddg_snippet": "18 Jun 2025 — We introduce Archetypal SAEs (A- SAE and RA- SAE ) that constrain dictionary elements within the data's convex hull. Abstract: Sparse Autoencoders ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=9v1eW8HgMU¬eId=jupnkmN3Zt", "content": "18 Jun 2025 — We introduce Archetypal SAEs (A- SAE and RA- SAE ) that constrain dictionary elements within the data's convex hull. Abstract: Sparse Autoencoders ..."}
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{"idx": 8, "title": "Relaxation Techniques for Solving Linear Systems - MATH 375 ...", "date": "", "ddg_snippet": "Definition Suppose vector ̃x ∈ Rn is an approximation to the solution of the linear system A x = b. The residual vector for ̃x with respect to this system is r = b − A ̃x.", "subpage_snippet": "", "source": "sites.millersville.edu", "link": "https://sites.millersville.edu/rbuchanan/math375/Relaxation.pdf", "content": "Definition Suppose vector ̃x ∈ Rn is an approximation to the solution of the linear system A x = b. The residual vector for ̃x with respect to this system is r = b − A ̃x."}
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{"idx": 9, "title": "Extracting Sparse Representations with Matching Pursuit", "date": "", "ddg_snippet": "3 Jun 2025 — We find MP- SAE recovers richer structure than standard SAEs across diverse settings: on synthetic trees with controlled interference, it ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.03093v1", "content": "3 Jun 2025 — We find MP- SAE recovers richer structure than standard SAEs across diverse settings: on synthetic trees with controlled interference, it ..."}
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data/sampled_jsons/9m87e9Keq1_RL_Incorrect_Synthetic_Data_Scales_LLM_Math_Reasoning_benchmarks.jsonl
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{"idx": 0, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=9m87e9Keq1", "content": "Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts. In this paper, we investigate this question for math reasoning via an empirical study, followed by building a conceptual understanding of our observations."}
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{"idx": 1, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "Thus while in principle, synthetic data could potentially address data scarcity, it must be designed in an appropriate manner to be effective. However, this has been hard due to a lack of an understanding of how synthetic data contributes to LLM behavior.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2406.14532v1", "content": "Thus while in principle, synthetic data could potentially address data scarcity, it must be designed in an appropriate manner to be effective. However, this has been hard due to a lack of an understanding of how synthetic data contributes to LLM behavior."}
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{"idx": 2, "title": "(PDF) RL on Incorrect Synthetic Data Scales the Efficiency of LLM ...", "date": "", "ddg_snippet": "PDF | Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts.arXiv:2406.14532v1 [cs.LG] 20 Jun 2024. RL on Incorrect Synthetic Data Scales the Effici ency of LLM Math Reasoning by Eight-F old.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/381604579_RL_on_Incorrect_Synthetic_Data_Scales_the_Efficiency_of_LLM_Math_Reasoning_by_Eight-Fold", "content": "PDF | Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts.arXiv:2406.14532v1 [cs.LG] 20 Jun 2024. RL on Incorrect Synthetic Data Scales the Effici ency of LLM Math Reasoning by Eight-F old."}
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{"idx": 3, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "View recent discussion. Abstract: Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/ko/overview/2406.14532v1", "content": "View recent discussion. Abstract: Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts."}
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{"idx": 4, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/RL-on-Incorrect-Synthetic-Data-Scales-the-Efficiency-of-LLM-Math-Reasoning-by-Eight-Fold-17552ae8-02cf-4931-9351-04c6f7b243c5", "content": "Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts."}
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{"idx": 5, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "The study investigates the impact of synthetic data , both correct and incorrect , on the fine-tuning of LLMs for enhanced math reasoning using supervised fine-tuning (SFT) and reinforcement learning ( RL ).", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/papers/2406.14532", "content": "The study investigates the impact of synthetic data , both correct and incorrect , on the fine-tuning of LLMs for enhanced math reasoning using supervised fine-tuning (SFT) and reinforcement learning ( RL )."}
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{"idx": 6, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "This paper investigates the use of reinforcement learning ( RL ) on incorrect synthetic data to improve the math reasoning abilities of large language models (LLMs).", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/rl-incorrect-synthetic-data-scales-efficiency-llm", "content": "This paper investigates the use of reinforcement learning ( RL ) on incorrect synthetic data to improve the math reasoning abilities of large language models (LLMs)."}
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{"idx": 7, "title": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math ...", "date": "", "ddg_snippet": "Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts.", "subpage_snippet": "", "source": "paperswithcode.com", "link": "https://paperswithcode.com/paper/rl-on-incorrect-synthetic-data-scales-the", "content": "Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts."}
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{"idx": 8, "title": "30 LLM evaluation benchmarks and how they work", "date": "", "ddg_snippet": "LLM benchmarks are standardized tests for LLM evaluations. This guide covers 30 benchmarks from MMLU to Chatbot Arena, with links to datasets and leaderboards.", "subpage_snippet": "", "source": "www.evidentlyai.com", "link": "https://www.evidentlyai.com/llm-guide/llm-benchmarks", "content": "LLM benchmarks are standardized tests for LLM evaluations. This guide covers 30 benchmarks from MMLU to Chatbot Arena, with links to datasets and leaderboards."}
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{"idx": 9, "title": "Vidhyanand (Vick) Mahase PharmD, PhD. on LinkedIn: RL on...", "date": "", "ddg_snippet": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/posts/vick-mahase-pharmd-phd_rl-on-incorrect-synthetic-data-scales-the-activity-7213284801527582720-_eRW", "content": "RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold."}
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data/sampled_jsons/AERO_Enhancing_Sharding_Blockchain_Deep_Reinforcement_Learning_Account_Migration_experimental_setup_.jsonl
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{"idx": 0, "title": "AERO: Enhancing Sharding Blockchain via Deep Reinforcement Learning for ...", "date": "", "ddg_snippet": "We propose AERO , a deep reinforcement learning framework to facilitate efficient account migration in sharding blockchains . AERO employs a prefix-based grouping strategy to enable group-level migration decisions and capture complex transaction patterns and relationships between accounts .", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3696410.3714926", "content": "We propose AERO , a deep reinforcement learning framework to facilitate efficient account migration in sharding blockchains . AERO employs a prefix-based grouping strategy to enable group-level migration decisions and capture complex transaction patterns and relationships between accounts ."}
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{"idx": 1, "title": "AERO: Enhancing Sharding Blockchain via Deep Reinforcement Learning for ...", "date": "", "ddg_snippet": "To address these scalability issues, account migration ofers a promising solution. However, existing migration solutions struggle with the high computational overhead and insuficient capture of complex transaction patterns. We propose AERO , a deep reinforcement learning framework to facilitate eficient account migration in sharding blockchains .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=WcuXvn3HVk", "content": "To address these scalability issues, account migration ofers a promising solution. However, existing migration solutions struggle with the high computational overhead and insuficient capture of complex transaction patterns. We propose AERO , a deep reinforcement learning framework to facilitate eficient account migration in sharding blockchains ."}
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{"idx": 2, "title": "AERO: Enhancing Sharding Blockchain via Deep Reinforcement Learning for ...", "date": "", "ddg_snippet": "To address these scalability issues, account migration offers a promising solution. However, existing migration solutions struggle with the high computational overhead and insufficient capture of complex transaction patterns. We propose AERO , a deep reinforcement learning framework for efficient account migration in sharding blockchains .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=WcuXvn3HVk", "content": "To address these scalability issues, account migration offers a promising solution. However, existing migration solutions struggle with the high computational overhead and insufficient capture of complex transaction patterns. We propose AERO , a deep reinforcement learning framework for efficient account migration in sharding blockchains ."}
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{"idx": 3, "title": "PDF AERO: Enhancing Sharding Blockchain via Deep Reinforcement Learning for ...", "date": "", "ddg_snippet": "Motivated by the need for an eficient and decentralized account migration mechanism, we explore applying deep reinforcement learning (DRL) [27] to this problem. DRL is highly efective in handling sequential decision-making tasks and has demonstrated significant potential in optimizing complex systems with expansive state and action spaces [24]. In the context of account migration , the account ...", "subpage_snippet": "", "source": "zhenxiao.com", "link": "http://zhenxiao.com/papers/WWW_AERO_camera_ready.pdf", "content": "Motivated by the need for an eficient and decentralized account migration mechanism, we explore applying deep reinforcement learning (DRL) [27] to this problem. DRL is highly efective in handling sequential decision-making tasks and has demonstrated significant potential in optimizing complex systems with expansive state and action spaces [24]. In the context of account migration , the account ..."}
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| 5 |
+
{"idx": 4, "title": "AERO: Enhancing Sharding Blockchain via Deep Reinforcement Learning for ...", "date": "", "ddg_snippet": "AERO : Enhancing Sharding Blockchain via Deep Reinforcement Learning for Account Migration Mingxuan Song, Pengze Li, Bohan Zhou, Shenglin Yin, Zhen Xiao, Jieyi Long", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=hBE3xx8yMk", "content": "AERO : Enhancing Sharding Blockchain via Deep Reinforcement Learning for Account Migration Mingxuan Song, Pengze Li, Bohan Zhou, Shenglin Yin, Zhen Xiao, Jieyi Long"}
|
| 6 |
+
{"idx": 5, "title": "AERO: Enhancing Sharding Blockchain via Deep Reinforcement Learning for ...", "date": "", "ddg_snippet": "This paper proposes AERO , a deep reinforcement learning framework for efficient account migration in sharding blockchains , improving throughput by 31.77% and reducing cross-shard transactions and workload imbalances.", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/zh-CN/chatpaper/paper/129864", "content": "This paper proposes AERO , a deep reinforcement learning framework for efficient account migration in sharding blockchains , improving throughput by 31.77% and reducing cross-shard transactions and workload imbalances."}
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| 7 |
+
{"idx": 6, "title": "AERO: Enhancing Sharding Blockchain via Deep Reinforcement Learning for ...", "date": "", "ddg_snippet": "This work proposes AERO , a deep reinforcement learning framework to facilitate efficient account migration in sharding blockchains , which employs a prefix-based grouping strategy to enable group-level migration decisions and capture complex transaction patterns and relationships between accounts . Sharding blockchain networks face significant scalability challenges due to high frequencies of ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/AERO:-Enhancing-Sharding-Blockchain-via-Deep-for-Song-Li/a4ab4e5da2ec84ea76d9176e2d31eed7990bcdd3", "content": "This work proposes AERO , a deep reinforcement learning framework to facilitate efficient account migration in sharding blockchains , which employs a prefix-based grouping strategy to enable group-level migration decisions and capture complex transaction patterns and relationships between accounts . Sharding blockchain networks face significant scalability challenges due to high frequencies of ..."}
|
| 8 |
+
{"idx": 7, "title": "Deep Learning Approaches for Blockchain Scalability Through Sharding ...", "date": "", "ddg_snippet": "Sharding technology creates new difficulties even as it helps traditional blockchain networks overcome performance issues. The distribution of malicious nodes may be unequal because of random node allocation, resulting in performance variations and security threats. Current reputation-based sharding techniques frequently ignore node performance features and don't take care of leader election ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/abstract/document/10830433", "content": "Sharding technology creates new difficulties even as it helps traditional blockchain networks overcome performance issues. The distribution of malicious nodes may be unequal because of random node allocation, resulting in performance variations and security threats. Current reputation-based sharding techniques frequently ignore node performance features and don't take care of leader election ..."}
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| 9 |
+
{"idx": 8, "title": "SPRING: Improving the Throughput of Sharding Blockchain via Deep ...", "date": "", "ddg_snippet": "In this paper, we present SPRING, the first deep-reinforcement-learning (DRL)-based sharding framework for state placement. SPRING formulates the state placement as a Markov Decision Process, which considers the cross-shard transaction ratio and workload balancing and employs DRL to learn the effective state placement policy.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3589334.3645386", "content": "In this paper, we present SPRING, the first deep-reinforcement-learning (DRL)-based sharding framework for state placement. SPRING formulates the state placement as a Markov Decision Process, which considers the cross-shard transaction ratio and workload balancing and employs DRL to learn the effective state placement policy."}
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| 10 |
+
{"idx": 9, "title": "AERO: Enhancing Sharding Blockchain via Deep Reinforcement Learning for ...", "date": "", "ddg_snippet": "Article \" AERO : Enhancing Sharding Blockchain via Deep Reinforcement Learning for Account Migration \" Detailed information of the J-GLOBAL is an information service managed by the Japan Science and Technology Agency (hereinafter referred to as \"JST\"). It provides free access to secondary information on researchers, articles, patents, etc., in science and technology, medicine and pharmacy. The ...", "subpage_snippet": "", "source": "jglobal.jst.go.jp", "link": "https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202502257667914622", "content": "Article \" AERO : Enhancing Sharding Blockchain via Deep Reinforcement Learning for Account Migration \" Detailed information of the J-GLOBAL is an information service managed by the Japan Science and Technology Agency (hereinafter referred to as \"JST\"). It provides free access to secondary information on researchers, articles, patents, etc., in science and technology, medicine and pharmacy. The ..."}
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data/sampled_jsons/ATA_Adaptive_Task_Allocation_Algorithm_8_Recursive_Allocation_Selection_RAS.jsonl
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{"idx": 0, "title": "ATA : Adaptive Task Allocation for Efficient Resource Management in...", "date": "", "ddg_snippet": "C Recursive Allocation Selection Algorithm .In this paper, we propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00775v2", "content": "C Recursive Allocation Selection Algorithm .In this paper, we propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times."}
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+
{"idx": 1, "title": "ICML Poster ATA : Adaptive Task Allocation for Efficient Resource...", "date": "", "ddg_snippet": "In this paper, we propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46650", "content": "In this paper, we propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times."}
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+
{"idx": 2, "title": "[PDF] Performance Evaluation of Some Adaptive Task Allocation ...", "date": "", "ddg_snippet": "performs adaptive task allocation strategies in this scenario.The proposed algorithm achieves 1.17%, 1.02%, and 3.21% lower overload probability relative to random, least-queue and nearest offloading selection schemes, respectively.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/352619630_Performance_Evaluation_of_Some_Adaptive_Task_Allocation_Algorithms_for_Fog_Networks", "content": "performs adaptive task allocation strategies in this scenario.The proposed algorithm achieves 1.17%, 1.02%, and 3.21% lower overload probability relative to random, least-queue and nearest offloading selection schemes, respectively."}
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| 4 |
+
{"idx": 3, "title": "Adaptive Task Allocation and Scheduling on NoC based Multicore...", "date": "", "ddg_snippet": "Adaptive Task allocation & Scheduling on multicore platforms with multitasking processors 0:3. 52 targeting such multicore systems. In these systems, considering multiple tasks per PE allocation 53 strategy can potentially result in better utilization of the available computing resources [24].", "subpage_snippet": "", "source": "hal.science", "link": "https://hal.science/hal-02877583/document", "content": "Adaptive Task allocation & Scheduling on multicore platforms with multitasking processors 0:3. 52 targeting such multicore systems. In these systems, considering multiple tasks per PE allocation 53 strategy can potentially result in better utilization of the available computing resources [24]."}
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| 5 |
+
{"idx": 4, "title": "Advances in Adaptive Task Allocation for Fog Robotics - Diverse Daily", "date": "", "ddg_snippet": "One widely used algorithm for adaptive task allocation in fog robotics is the Genetic Algorithm (GA). This algorithm is inspired by the process of natural selection and evolution.", "subpage_snippet": "", "source": "diversedaily.com", "link": "https://diversedaily.com/advances-in-adaptive-task-allocation-for-fog-robotics/", "content": "One widely used algorithm for adaptive task allocation in fog robotics is the Genetic Algorithm (GA). This algorithm is inspired by the process of natural selection and evolution."}
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| 6 |
+
{"idx": 5, "title": "Model predictive control using Adaptive Task Allocation ... | IEEE Xplore", "date": "", "ddg_snippet": "This paper presents the implementation of a controller based on Adaptive Task Allocation Algorithm (ATAA) for a traffic network with signalized intersections, w.", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/7885717", "content": "This paper presents the implementation of a controller based on Adaptive Task Allocation Algorithm (ATAA) for a traffic network with signalized intersections, w."}
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| 7 |
+
{"idx": 6, "title": "Q-ITAGS: Quality-Optimized Spatio-Temporal Heterogeneous Task ...", "date": "", "ddg_snippet": "The Q-ITAGS algorithm presented in this paper offers a quality-optimized approach to the spatio-temporal heterogeneous task allocation problem, effectively balancing task quality and time budget constraints.", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/q-itags-quality-optimized-spatio-temporal-heterogeneous", "content": "The Q-ITAGS algorithm presented in this paper offers a quality-optimized approach to the spatio-temporal heterogeneous task allocation problem, effectively balancing task quality and time budget constraints."}
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| 8 |
+
{"idx": 7, "title": "[PDF] Adaptive task allocation for search area... | Semantic Scholar", "date": "", "ddg_snippet": "This study proposes a robust task allocation algorithm under the uncertainty in the position of the nodes and Gaussian approximations are used and the Interval algorithm is employed to investigate the solution to the uncertainty.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Adaptive-task-allocation-for-search-area-coverage-Meuth-Saad/c351bcb795c8a88cb73f40b117fd8080cab3a82e", "content": "This study proposes a robust task allocation algorithm under the uncertainty in the position of the nodes and Gaussian approximations are used and the Interval algorithm is employed to investigate the solution to the uncertainty."}
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| 9 |
+
{"idx": 8, "title": "TAMER: an adaptive task allocation method for aging reduction in...", "date": "", "ddg_snippet": "As a task allocation algorithm , TAMER takes the cores’ utilization and their internal units’ activity into account to smooth the temperature pattern inside the chip. By minimizing both temporal and spatial thermal variations, TAMER prevents the occurrence of hotspot over time and space.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s11227-020-03326-7", "content": "As a task allocation algorithm , TAMER takes the cores’ utilization and their internal units’ activity into account to smooth the temperature pattern inside the chip. By minimizing both temporal and spatial thermal variations, TAMER prevents the occurrence of hotspot over time and space."}
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| 10 |
+
{"idx": 9, "title": "An adaptive task allocation technique for green cloud... - Peeref", "date": "", "ddg_snippet": "Task allocation in the cloud computing environment is a well-known problem, and through this problem, we can facilitate green cloud computing. We have proposed an adaptive task allocation algorithm for the heterogeneous cloud environment.", "subpage_snippet": "", "source": "www.peeref.com", "link": "https://www.peeref.com/works/4071639", "content": "Task allocation in the cloud computing environment is a well-known problem, and through this problem, we can facilitate green cloud computing. We have proposed an adaptive task allocation algorithm for the heterogeneous cloud environment."}
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data/sampled_jsons/ATA_Adaptive_Task_Allocation_GTA_strategy_distributed_machine_learning.jsonl
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{"idx": 0, "title": "ICML Poster ATA: Adaptive Task Allocation for Efficient ...", "date": "", "ddg_snippet": "Poster ATA : Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning Artavazd Maranjyan · El Mehdi Saad · Peter Richtarik · Francesco Orabona West Exhibition Hall B2-B3 #W-909", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46650", "content": "Poster ATA : Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning Artavazd Maranjyan · El Mehdi Saad · Peter Richtarik · Francesco Orabona West Exhibition Hall B2-B3 #W-909"}
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| 2 |
+
{"idx": 1, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "In this paper, we propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times. Through rigorous theoretical analysis, we show that ATAidentifies the optimal task allocation and performs comparably to methods with prior knowledge of computation times.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00775v2", "content": "In this paper, we propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times. Through rigorous theoretical analysis, we show that ATAidentifies the optimal task allocation and performs comparably to methods with prior knowledge of computation times."}
|
| 3 |
+
{"idx": 2, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "May 1, 2025 · The general task allocation problem in parallel stochastic optimization leads to resource wastefulness, and addressing it can improve efficiency across various distributed machine learning methods.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=1BaC3AdG1i", "content": "May 1, 2025 · The general task allocation problem in parallel stochastic optimization leads to resource wastefulness, and addressing it can improve efficiency across various distributed machine learning methods."}
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| 4 |
+
{"idx": 3, "title": "[PDF] ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "Through rigorous theoretical analysis, ATA ( Adaptive Task Allocation ) is proposed, a method that adapts to heterogeneous and random distributions of worker computation times and performs comparably to methods with prior knowledge of computation times. Asynchronous methods are fundamental for parallelizing computations in distributed machine learning . They aim to accelerate training by fully ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/ATA:-Adaptive-Task-Allocation-for-Efficient-in-Maranjyan-Saad/871e17b70c5c31985b6ecb1d61960ad5ee7d1cbd", "content": "Through rigorous theoretical analysis, ATA ( Adaptive Task Allocation ) is proposed, a method that adapts to heterogeneous and random distributions of worker computation times and performs comparably to methods with prior knowledge of computation times. Asynchronous methods are fundamental for parallelizing computations in distributed machine learning . They aim to accelerate training by fully ..."}
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| 5 |
+
{"idx": 4, "title": "Unlocking Efficiency: How Adaptive Task Allocation ...", "date": "", "ddg_snippet": "May 24, 2025 · In the rapidly evolving world of artificial intelligence, distributed machine learning stands as a cornerstone for future developments. Yet, as industries adopt parallelized systems to enhance machine learning operations, the challenge of inefficient resource allocation becomes glaring. Enter Adaptive Task Allocation ( ATA ), a sophisticated solution designed to address this very problem.", "subpage_snippet": "", "source": "www.lumafeed.com", "link": "https://www.lumafeed.com/article/9d4d8fe1-d044-4756-99ca-33ab376e4e05", "content": "May 24, 2025 · In the rapidly evolving world of artificial intelligence, distributed machine learning stands as a cornerstone for future developments. Yet, as industries adopt parallelized systems to enhance machine learning operations, the challenge of inefficient resource allocation becomes glaring. Enter Adaptive Task Allocation ( ATA ), a sophisticated solution designed to address this very problem."}
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| 6 |
+
{"idx": 5, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "In this paper, we propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times. Through rigorous theoretical analysis, we show that ATA identifies the optimal task allocation and performs comparably to methods with prior knowledge of computation times.", "subpage_snippet": "", "source": "ui.adsabs.harvard.edu", "link": "https://ui.adsabs.harvard.edu/abs/2025arXiv250200775M/abstract", "content": "In this paper, we propose ATA ( Adaptive Task Allocation ), a method that adapts to heterogeneous and random distributions of worker computation times. Through rigorous theoretical analysis, we show that ATA identifies the optimal task allocation and performs comparably to methods with prior knowledge of computation times."}
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| 7 |
+
{"idx": 6, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "#1 ATA : Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning [PDF 1] [Copy] [Kimi 1] [REL] Authors: Artavazd Maranjyan, El Mehdi Saad, Peter Richtarik, Francesco Orabona Asynchronous methods are fundamental for parallelizing computations in distributed machine learning . They aim to accelerate training by fully utilizing all available resources. However ...", "subpage_snippet": "", "source": "papers.cool", "link": "https://papers.cool/venue/1BaC3AdG1i@OpenReview", "content": "#1 ATA : Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning [PDF 1] [Copy] [Kimi 1] [REL] Authors: Artavazd Maranjyan, El Mehdi Saad, Peter Richtarik, Francesco Orabona Asynchronous methods are fundamental for parallelizing computations in distributed machine learning . They aim to accelerate training by fully utilizing all available resources. However ..."}
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| 8 |
+
{"idx": 7, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "18 Jun 2025 — TL;DR: We propose a method that learns machine speeds on the fly to assign tasks more efficiently in parallel computing. Abstract: Asynchronous ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=1BaC3AdG1i¬eId=hkH8Wi9zZm", "content": "18 Jun 2025 — TL;DR: We propose a method that learns machine speeds on the fly to assign tasks more efficiently in parallel computing. Abstract: Asynchronous ..."}
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| 9 |
+
{"idx": 8, "title": "ATA: Adaptive Task Allocation for Efficient Resource ...", "date": "", "ddg_snippet": "2 Feb 2025 — Asynchronous methods are fundamental for parallelizing computations in distributed machine learning . They aim to accelerate training by ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00775v1", "content": "2 Feb 2025 — Asynchronous methods are fundamental for parallelizing computations in distributed machine learning . They aim to accelerate training by ..."}
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| 10 |
+
{"idx": 9, "title": "cherryATA", "date": "", "ddg_snippet": "ATA : Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning . 3.1. Task allocation protocol. We consider a system of n ...", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/pdf/2502.00775v1", "content": "ATA : Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning . 3.1. Task allocation protocol. We consider a system of n ..."}
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data/sampled_jsons/ATA_ICML_2025_Equation_7_confidence_bound_formula.jsonl
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{"idx": 0, "title": "Confidence interval - Wikipedia", "date": "", "ddg_snippet": "A confidence interval for the parameter , with confidence level or coefficient , is an interval determined by random variables and with the property: The number , whose typical value is close to but not greater than 1, is sometimes given in the form (or as a percentage ), where is a small positive number, often 0.05.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Confidence_interval", "content": "A confidence interval for the parameter , with confidence level or coefficient , is an interval determined by random variables and with the property: The number , whose typical value is close to but not greater than 1, is sometimes given in the form (or as a percentage ), where is a small positive number, often 0.05."}
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+
{"idx": 1, "title": "ICML 2025 Statistics - Paper Copilot", "date": "", "ddg_snippet": "ICML 2025 Review Scores Collection The International Conference on Machine Learning ( ICML ) has not yet opened its reviewer data during the review. However, there's a noticeable interest in the community to view how scores are distributed.", "subpage_snippet": "", "source": "papercopilot.com", "link": "https://papercopilot.com/statistics/icml-statistics/icml-2025-statistics/", "content": "ICML 2025 Review Scores Collection The International Conference on Machine Learning ( ICML ) has not yet opened its reviewer data during the review. However, there's a noticeable interest in the community to view how scores are distributed."}
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{"idx": 2, "title": "Understanding Confidence Intervals | Easy Examples & Formulas", "date": "", "ddg_snippet": "The confidence level is the percentage of times you expect to reproduce an estimate between the upper and lower bounds of the confidence interval, and is set by the alpha value.", "subpage_snippet": "", "source": "www.scribbr.com", "link": "https://www.scribbr.com/statistics/confidence-interval/", "content": "The confidence level is the percentage of times you expect to reproduce an estimate between the upper and lower bounds of the confidence interval, and is set by the alpha value."}
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| 4 |
+
{"idx": 3, "title": "What are Confidence Intervals? - Statology", "date": "", "ddg_snippet": "A confidence interval is a range of values that is likely to contain a population parameter with a certain level of confidence . It is calculated using the following general formula :", "subpage_snippet": "", "source": "www.statology.org", "link": "https://www.statology.org/confidence-intervals/", "content": "A confidence interval is a range of values that is likely to contain a population parameter with a certain level of confidence . It is calculated using the following general formula :"}
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| 5 |
+
{"idx": 4, "title": "8.S: Confidence Intervals (Summary) - Statistics LibreTexts", "date": "", "ddg_snippet": "In this module, we learned how to calculate the confidence interval for a single population mean where the population standard deviation is known.", "subpage_snippet": "", "source": "stats.libretexts.org", "link": "https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Introductory_Statistics_1e_(OpenStax)/08:_Confidence_Intervals/8.S:_Confidence_Intervals_(Summary)", "content": "In this module, we learned how to calculate the confidence interval for a single population mean where the population standard deviation is known."}
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| 6 |
+
{"idx": 5, "title": "Confidence Intervals: Interpreting, Finding & Formulas - Statistics by Jim", "date": "", "ddg_snippet": "A confidence interval is a range of values that is likely to contain the value of an unknown population parameter.", "subpage_snippet": "", "source": "statisticsbyjim.com", "link": "https://statisticsbyjim.com/hypothesis-testing/confidence-interval/", "content": "A confidence interval is a range of values that is likely to contain the value of an unknown population parameter."}
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| 7 |
+
{"idx": 6, "title": "Confidence Bounds - ReliaSoft", "date": "", "ddg_snippet": "The above equation is the posterior cdf, which essentially calculates a confidence bound on the parameter, where is the confidence level and is the confidence bound .", "subpage_snippet": "", "source": "help.reliasoft.com", "link": "https://help.reliasoft.com/reference/life_data_analysis/lda/confidence_bounds.html", "content": "The above equation is the posterior cdf, which essentially calculates a confidence bound on the parameter, where is the confidence level and is the confidence bound ."}
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| 8 |
+
{"idx": 7, "title": "How are the confidence intervals calculated", "date": "", "ddg_snippet": "How are the confidence intervals calculated There are confidence intervals on the model parameters, and confidence intervals on the plots. This document explains how both are calculated. The confidence intervals on the plots use the confidence intervals on the model parameters in the procedure that is explained in the second section of this document. Before reading this document, you should ...", "subpage_snippet": "", "source": "reliability.readthedocs.io", "link": "https://reliability.readthedocs.io/en/latest/How+are+the+confidence+intervals+calculated.html", "content": "How are the confidence intervals calculated There are confidence intervals on the model parameters, and confidence intervals on the plots. This document explains how both are calculated. The confidence intervals on the plots use the confidence intervals on the model parameters in the procedure that is explained in the second section of this document. Before reading this document, you should ..."}
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| 9 |
+
{"idx": 8, "title": "How to Calculate a Confidence Interval in Excel (2024) - Spreadsheeto", "date": "", "ddg_snippet": "How to use the Excel CONFIDENCE function? Enough with all the talk. Let's come to the point - how do you use the CONFIDENCE Function? Calculating confidence intervals in Excel is pretty simple. All you need to do is enter the relevant data points, get the confidence value statistic, and that's it. Simple Let's say we want to find the mean weight of the employees of a Company. For that ...", "subpage_snippet": "", "source": "spreadsheeto.com", "link": "https://spreadsheeto.com/confidence-interval-excel/", "content": "How to use the Excel CONFIDENCE function? Enough with all the talk. Let's come to the point - how do you use the CONFIDENCE Function? Calculating confidence intervals in Excel is pretty simple. All you need to do is enter the relevant data points, get the confidence value statistic, and that's it. Simple Let's say we want to find the mean weight of the employees of a Company. For that ..."}
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| 10 |
+
{"idx": 9, "title": "ICML Poster Improved Online Confidence Bounds for Multinomial Logistic ...", "date": "", "ddg_snippet": "Abstract: In this paper, we propose an improved online confidence bound for multinomial logistic (MNL) models and apply this result to MNL bandits, achieving variance-dependent optimal regret. Recently, Lee & Oh (2024) established an online confidence bound for MNL models and achieved nearly minimax-optimal regret in MNL bandits.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/45882", "content": "Abstract: In this paper, we propose an improved online confidence bound for multinomial logistic (MNL) models and apply this result to MNL bandits, achieving variance-dependent optimal regret. Recently, Lee & Oh (2024) established an online confidence bound for MNL models and achieved nearly minimax-optimal regret in MNL bandits."}
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data/sampled_jsons/A_Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_paper.jsonl
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{"idx": 0, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment", "date": "", "ddg_snippet": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00136", "content": "This paper introduces a checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by three-branch governmental systems. It implements three independent yet interacting components: LLMs as the executive branch for knowledge generation, DIKE as the legislative branch establishing ethical guardrails, and ERIS as the judicial branch for contextual interpretation ..."}
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| 2 |
+
{"idx": 1, "title": "PDF An Adversarial Behavior Model for Contextual Ethical Alignment in Large ...", "date": "", "ddg_snippet": "Abstract This research introduces DIKE, a novel framework for aligning Large Language Models (LLMs) with human values through emotion-guided behavioral control. Inspired by the checks and balances ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Edward-Chang-22/publication/380515639_A_Three-Branch_Checks-and-Balances_Framework_for_Context-Aware_Ethical_Alignment_of_Large_Language_Models/links/671b315b55a5271cded9457e/A-Three-Branch-Checks-and-Balances-Framework-for-Context-Aware-Ethical-Alignment-of-Large-Language-Models.pdf", "content": "Abstract This research introduces DIKE, a novel framework for aligning Large Language Models (LLMs) with human values through emotion-guided behavioral control. Inspired by the checks and balances ..."}
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| 3 |
+
{"idx": 2, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware Ethical ...", "date": "", "ddg_snippet": "A three-branch checks - and - balances framework for ethical alignment of Large Language Models, inspired by governmental systems, demonstrates how emotional modeling can guide linguistic behaviors toward ethical outcomes while preserving independence across knowledge generation, ethical oversight, and contextual interpretation.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/A-Three-Branch-Checks-and-Balances-Frameworkfor-of-Chang/5918a91419cf95db8599b086590facf63f124702/figure/4", "content": "A three-branch checks - and - balances framework for ethical alignment of Large Language Models, inspired by governmental systems, demonstrates how emotional modeling can guide linguistic behaviors toward ethical outcomes while preserving independence across knowledge generation, ethical oversight, and contextual interpretation."}
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| 4 |
+
{"idx": 3, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment ...", "date": "", "ddg_snippet": "This paper presents a new way to ensure that large AI language models behave ethically, using a system inspired by government branches. It has three parts: the AI (executive) generates knowledge, ...", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/icml/46461/paper", "content": "This paper presents a new way to ensure that large AI language models behave ethically, using a system inspired by government branches. It has three parts: the AI (executive) generates knowledge, ..."}
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| 5 |
+
{"idx": 4, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware Ethical ...", "date": "", "ddg_snippet": "Conclusion This checks - and - balances approach offers a promising direction for building more ethically- aware AI systems. The framework's ability to handle cultural differences while maintaining ethical standards could help develop AI systems that work responsibly across global contexts .", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/three-branch-checks-balances-frameworkfor-context-aware", "content": "Conclusion This checks - and - balances approach offers a promising direction for building more ethically- aware AI systems. The framework's ability to handle cultural differences while maintaining ethical standards could help develop AI systems that work responsibly across global contexts ."}
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| 6 |
+
{"idx": 5, "title": "A Three-Branch Checks-and-Balances Framework for Context-Aware Ethical ...", "date": "", "ddg_snippet": "This paper introduces a three-branch checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by the idea of collaborative intelligence.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=o2afWIxjKD", "content": "This paper introduces a three-branch checks - and - balances framework for ethical alignment of Large Language Models (LLMs), inspired by the idea of collaborative intelligence."}
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| 7 |
+
{"idx": 6, "title": "Edward Y. Chang - Stanford University", "date": "", "ddg_snippet": "A Three-Branch Checks - and - Balances Framework for Context-Aware Ethical Alignment of Large Language Models Edward Y. Chang NeurIPS AI Safety, Decmber 2024 PDF | BibTex Behavioral Emotion Analysis Model for Large Language Models Edward Y. Chang IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) (invited paper ), August 2024", "subpage_snippet": "", "source": "infolab.stanford.edu", "link": "http://infolab.stanford.edu/~echang/", "content": "A Three-Branch Checks - and - Balances Framework for Context-Aware Ethical Alignment of Large Language Models Edward Y. Chang NeurIPS AI Safety, Decmber 2024 PDF | BibTex Behavioral Emotion Analysis Model for Large Language Models Edward Y. Chang IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) (invited paper ), August 2024"}
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| 8 |
+
{"idx": 7, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment", "date": "", "ddg_snippet": "Poster A Checks - and - Balances Framework for Context-Aware Ethical AI Alignment Edward Chang East Exhibition Hall A-B #E-703", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46461", "content": "Poster A Checks - and - Balances Framework for Context-Aware Ethical AI Alignment Edward Chang East Exhibition Hall A-B #E-703"}
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| 9 |
+
{"idx": 8, "title": "Ethical Guardrails for AI: A Checks-and-Balances Approach", "date": "", "ddg_snippet": "A Three-Branch Checks - and - Balances Framework for Context-Aware Ethical Alignment of Large Language Models 48 | 124", "subpage_snippet": "", "source": "www.zerna.io", "link": "https://www.zerna.io/page/security/presentation_set/security-llm-research/presentation/security-ethical-alignment-fairness/slide/security-paper-2502_00136", "content": "A Three-Branch Checks - and - Balances Framework for Context-Aware Ethical Alignment of Large Language Models 48 | 124"}
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| 10 |
+
{"idx": 9, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment", "date": "", "ddg_snippet": "Abstract This paper introduces a checks - and - balances framework for ethical alignment of Large Lan-guage Models (LLMs), inspired by three-branch governmental systems. It implements three in-dependent yet interacting components: LLMs as the executive branch for knowledge generation, Dike as the legislative branch that establishes eth-ical guardrails, and Eris as the judicial branch for ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00136", "content": "Abstract This paper introduces a checks - and - balances framework for ethical alignment of Large Lan-guage Models (LLMs), inspired by three-branch governmental systems. It implements three in-dependent yet interacting components: LLMs as the executive branch for knowledge generation, Dike as the legislative branch that establishes eth-ical guardrails, and Eris as the judicial branch for ..."}
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data/sampled_jsons/A_Likelihood_Based_Approach_to_Distribution_Regression_Using_Conditional_Deep_Generative_Models_Equa_year_2023.jsonl
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{"idx": 0, "title": "A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "Oct 2, 2024 · In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2410.02025", "content": "Oct 2, 2024 · In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ..."}
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+
{"idx": 1, "title": "A LIKELIHOOD BASED APPROACH TO DISTRIBUTION REGRESSION USING ...", "date": "", "ddg_snippet": "In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the re-sponse variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=V6hhhXoTSq", "content": "In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the re-sponse variable lies in a high-dimensional ambient space but concentrates around a potentially lower-dimensional manifold. More specifically, we study the large-sample properties of a likelihood - based approach for estimating these ..."}
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| 3 |
+
{"idx": 2, "title": "A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "We investigate a likelihood approach to nonparametric estimation of a singular distribution using deep generative models . We prove that a novel and effective solution exists by perturbing the data with an instance noise.", "subpage_snippet": "", "source": "fugumt.com", "link": "https://fugumt.com/fugumt/paper_check/2410.02025v1_enmode", "content": "We investigate a likelihood approach to nonparametric estimation of a singular distribution using deep generative models . We prove that a novel and effective solution exists by perturbing the data with an instance noise."}
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{"idx": 3, "title": "A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "Oct 2, 2024 · In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/384630603_A_Likelihood_Based_Approach_to_Distribution_Regression_Using_Conditional_Deep_Generative_Models", "content": "Oct 2, 2024 · In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high ..."}
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| 5 |
+
{"idx": 4, "title": "A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "Specifically, we explore and study the theoretical properties of a new likelihood - based approach to conditional sampling using deep generative models for data potentially residing on a low-dimensional manifold corrupted by full-dimensional noise.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.02025v1", "content": "Specifically, we explore and study the theoretical properties of a new likelihood - based approach to conditional sampling using deep generative models for data potentially residing on a low-dimensional manifold corrupted by full-dimensional noise."}
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| 6 |
+
{"idx": 5, "title": "A Deep Generative Approach to Conditional Sampling", "date": "", "ddg_snippet": "Oct 19, 2021 · We propose a deep generative approach to sampling from a conditional distribution based on a unified formulation of conditional distribution and generalized nonparametric regression function using the noise-outsourcing lemma. The proposed approach aims at learning a conditional generator so that a random sample from the target conditional distribution can be obtained by the action of the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2110.10277", "content": "Oct 19, 2021 · We propose a deep generative approach to sampling from a conditional distribution based on a unified formulation of conditional distribution and generalized nonparametric regression function using the noise-outsourcing lemma. The proposed approach aims at learning a conditional generator so that a random sample from the target conditional distribution can be obtained by the action of the ..."}
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{"idx": 6, "title": "[2402.01460] Deep conditional distribution learning via ...", "date": "", "ddg_snippet": "Feb 2, 2024 · We introduce an ordinary differential equation (ODE) based deep generative method for learning conditional distributions, named Conditional Föllmer Flow. Starting from a standard Gaussian distribution , the proposed flow could approximate the target conditional distribution very well when the time is close to 1. For effective implementation, we discretize the flow with Euler's method where we ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2402.01460", "content": "Feb 2, 2024 · We introduce an ordinary differential equation (ODE) based deep generative method for learning conditional distributions, named Conditional Föllmer Flow. Starting from a standard Gaussian distribution , the proposed flow could approximate the target conditional distribution very well when the time is close to 1. For effective implementation, we discretize the flow with Euler's method where we ..."}
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| 8 |
+
{"idx": 7, "title": "A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "In this work, we explore the theoretical proper- ties of conditional deep generative models un- der the statistical framework of distribution re-.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=1IyPRv1A0r", "content": "In this work, we explore the theoretical proper- ties of conditional deep generative models un- der the statistical framework of distribution re-."}
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| 9 |
+
{"idx": 8, "title": "Your Likelihood-Based Visual Generative Model is Secretly ...", "date": "", "ddg_snippet": "To bypass MLE's mode-covering nature, we aim to leverage GAN-type loss to discriminate between the model and data distributions and produce contrastive forces ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/45454", "content": "To bypass MLE's mode-covering nature, we aim to leverage GAN-type loss to discriminate between the model and data distributions and produce contrastive forces ..."}
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| 10 |
+
{"idx": 9, "title": "Your Likelihood-Based Visual Generative Model is Secretly ...", "date": "", "ddg_snippet": "3 Mar 2025 — In this work, we introduce Direct Discriminative Optimization (DDO), a framework that bridges likelihood - based generative models and GANs to ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.01103v1", "content": "3 Mar 2025 — In this work, we introduce Direct Discriminative Optimization (DDO), a framework that bridges likelihood - based generative models and GANs to ..."}
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data/sampled_jsons/A_framework_for_improving_web_affordability_and_inclusiveness_Habib.jsonl
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{"idx": 0, "title": "A Framework for Improving Web Affordability and Inclusiveness", "date": "", "ddg_snippet": "ACM Reference Format: Rumaisa Habib *, Sarah Tanveer*, Aimen Inam, Haseeb Ahmed, Ayesha Ali, Zartash Afzal Uzmi, Zafar Ayyub Qazi, Ihsan Ayyub Qazi. 2023. A Framework for Improving Web Affordability and Inclusiveness .", "subpage_snippet": "", "source": "www.ietf.org", "link": "https://www.ietf.org/slides/slides-biasws-a-framework-for-improving-web-affordability-and-inclusiveness-00.pdf", "content": "ACM Reference Format: Rumaisa Habib *, Sarah Tanveer*, Aimen Inam, Haseeb Ahmed, Ayesha Ali, Zartash Afzal Uzmi, Zafar Ayyub Qazi, Ihsan Ayyub Qazi. 2023. A Framework for Improving Web Affordability and Inclusiveness ."}
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| 2 |
+
{"idx": 1, "title": "A Framework for Improving Web Affordability and Inclusiveness", "date": "", "ddg_snippet": "Today's Web remains too expensive for many Internet users, especially in developing regions. Unfortunately, the rising complexity of the Web makes affordability an even bigger concern as it stands to limit users' access to Internet services. We propose a novel framework and a fairness metric for rethinking Web architecture for affordability and inclusion. Our proposed framework systematically ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3603269.3604872", "content": "Today's Web remains too expensive for many Internet users, especially in developing regions. Unfortunately, the rising complexity of the Web makes affordability an even bigger concern as it stands to limit users' access to Internet services. We propose a novel framework and a fairness metric for rethinking Web architecture for affordability and inclusion. Our proposed framework systematically ..."}
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| 3 |
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{"idx": 2, "title": "dblp: A Framework for Improving Web Affordability and Inclusiveness.", "date": "", "ddg_snippet": "Bibliographic details on A Framework for Improving Web Affordability and Inclusiveness .", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/conf/sigcomm/HabibTIAAUQQ23", "content": "Bibliographic details on A Framework for Improving Web Affordability and Inclusiveness ."}
|
| 4 |
+
{"idx": 3, "title": "A Framework for Improving Web Affordability and Inclusiveness | Request PDF", "date": "", "ddg_snippet": "Request PDF | On Sep 10, 2023, Rumaisa Habib and others published A Framework for Improving Web Affordability and Inclusiveness | Find, read and cite all the research you need on ResearchGate", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/373616306_A_Framework_for_Improving_Web_Affordability_and_Inclusiveness", "content": "Request PDF | On Sep 10, 2023, Rumaisa Habib and others published A Framework for Improving Web Affordability and Inclusiveness | Find, read and cite all the research you need on ResearchGate"}
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| 5 |
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{"idx": 4, "title": "Paper: A Framework for Improving Web Affordability and Inclusiveness", "date": "", "ddg_snippet": "slides-biasws- a-framework-for-improving-web-affordability-and-inclusiveness -00", "subpage_snippet": "", "source": "datatracker.ietf.org", "link": "https://datatracker.ietf.org/doc/slides-biasws-a-framework-for-improving-web-affordability-and-inclusiveness/", "content": "slides-biasws- a-framework-for-improving-web-affordability-and-inclusiveness -00"}
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| 6 |
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{"idx": 5, "title": "A Framework for Improving Web Affordability and Inclusiveness", "date": "", "ddg_snippet": "A novel framework and a fairness metric for rethinking Web architecture for affordability and inclusion is proposed and a cross-country analysis of 99 countries shows that the framework can better balance affordability and webpage quality while preserving user privacy. Expand View on ACM ietf.org Save to Library Create Alert Cite", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/A-Framework-for-Improving-Web-Affordability-and-Habib-Tanveer/0546f3bedce1d44b3bbc1682d698d9b9a3f22906/figure/12", "content": "A novel framework and a fairness metric for rethinking Web architecture for affordability and inclusion is proposed and a cross-country analysis of 99 countries shows that the framework can better balance affordability and webpage quality while preserving user privacy. Expand View on ACM ietf.org Save to Library Create Alert Cite"}
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| 7 |
+
{"idx": 6, "title": "Ayesha ALI | accounting and finance | Research profile", "date": "", "ddg_snippet": "A Framework for Improving Web Affordability and Inclusiveness .A First Look at Public Service Websites from the Affordability Lens.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Ayesha-Ali-87", "content": "A Framework for Improving Web Affordability and Inclusiveness .A First Look at Public Service Websites from the Affordability Lens."}
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| 8 |
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{"idx": 7, "title": "CS PhD student at Stanford University", "date": "", "ddg_snippet": "Rethinking Web for Affordability and Inclusion ondemand_video Ihsan Ayyub Qazi, Zafar Ayyub Qazi, Ayesha Ali, Muhammad Abdullah, Rumaisa Habib HotNets ‘21.", "subpage_snippet": "", "source": "rumaisahabib.com", "link": "https://rumaisahabib.com/publications/", "content": "Rethinking Web for Affordability and Inclusion ondemand_video Ihsan Ayyub Qazi, Zafar Ayyub Qazi, Ayesha Ali, Muhammad Abdullah, Rumaisa Habib HotNets ‘21."}
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| 9 |
+
{"idx": 8, "title": "Rumaisa Habib 's Profile | Stanford Profiles", "date": "", "ddg_snippet": "All Publications. A Framework for Improving Web Affordability and Inclusiveness Habib , R., Tanveer, S., Inam, A., Ahmed, H., Ali, A., Uzmi, Z., Qazi, Z., Qazi, I., ACM ASSOC COMPUTING MACHINERY. 2023: 592-607.", "subpage_snippet": "", "source": "profiles.stanford.edu", "link": "https://profiles.stanford.edu/rumaisa-habib", "content": "All Publications. A Framework for Improving Web Affordability and Inclusiveness Habib , R., Tanveer, S., Inam, A., Ahmed, H., Ali, A., Uzmi, Z., Qazi, Z., Qazi, I., ACM ASSOC COMPUTING MACHINERY. 2023: 592-607."}
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| 10 |
+
{"idx": 9, "title": "Rumaisa Habib - CS PhD Student @ Stanford | LinkedIn", "date": "", "ddg_snippet": "A Framework for Improving Web Affordability and Inclusiveness .We propose a novel framework and fairness metric for rethinking Web architecture for affordability and inclusion.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/in/rumaisahabib", "content": "A Framework for Improving Web Affordability and Inclusiveness .We propose a novel framework and fairness metric for rethinking Web architecture for affordability and inclusion."}
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data/sampled_jsons/A_very_simple_way_to_improve_the_performance_of_almost_any_machine_learning_algorithm_is_to_train_ma.jsonl
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{"idx": 0, "title": "[1503.02531] Distilling the Knowledge in a Neural Network", "date": "", "ddg_snippet": "by G Hinton · 2015 · Cited by 27170 — A very simple way to improve the performance of almost any machine learning algorithm is to train many different models on the same data and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1503.02531", "content": "by G Hinton · 2015 · Cited by 27170 — A very simple way to improve the performance of almost any machine learning algorithm is to train many different models on the same data and ..."}
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| 2 |
+
{"idx": 1, "title": "Distilling the Knowledge in a Neural Network", "date": "", "ddg_snippet": "by G Hinton · 2015 · Cited by 27170 — A very simple way to improve the performance of almost any machine learning algorithm is to train many different models on the same data and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1503.02531", "content": "by G Hinton · 2015 · Cited by 27170 — A very simple way to improve the performance of almost any machine learning algorithm is to train many different models on the same data and ..."}
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| 3 |
+
{"idx": 2, "title": "Stochastic Weight Averaging — a New Way to Get State of ...", "date": "", "ddg_snippet": "In this article, I will discuss two interesting recent papers that provide an easy way to improve performance of any given neural network by using a smart way ...", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/data-science/stochastic-weight-averaging-a-new-way-to-get-state-of-the-art-results-in-deep-learning-c639ccf36a", "content": "In this article, I will discuss two interesting recent papers that provide an easy way to improve performance of any given neural network by using a smart way ..."}
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| 4 |
+
{"idx": 3, "title": "averaging weights of multiple fine-tuned models improves ...", "date": "", "ddg_snippet": "by M Wortsman · 2022 · Cited by 1339 — The conventional recipe for maximizing model accuracy is to (1) train multiple models with var- ious hyperparameters and (2) pick the individ-. 34 pages", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v162/wortsman22a/wortsman22a.pdf", "content": "by M Wortsman · 2022 · Cited by 1339 — The conventional recipe for maximizing model accuracy is to (1) train multiple models with var- ious hyperparameters and (2) pick the individ-. 34 pages"}
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| 5 |
+
{"idx": 4, "title": "A comprehensive review on ensemble deep learning", "date": "", "ddg_snippet": "by A Mohammed · 2023 · Cited by 997 — Hence, ensemble deep learning methods refer to training several baseline deep models and combining some rules to make predictions.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S1319157823000228", "content": "by A Mohammed · 2023 · Cited by 997 — Hence, ensemble deep learning methods refer to training several baseline deep models and combining some rules to make predictions."}
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| 6 |
+
{"idx": 5, "title": "LEVERAGING SIMPLE MODEL PREDICTIONS", "date": "", "ddg_snippet": "by A Dhurandhar — In this paper, we propose a method, SRatio, which reweights the training set to improve simple models given access to a highly accurate complex model such as a ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=HyxQbaEYPr", "content": "by A Dhurandhar — In this paper, we propose a method, SRatio, which reweights the training set to improve simple models given access to a highly accurate complex model such as a ..."}
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| 7 |
+
{"idx": 6, "title": "Combining Machine Learning and Statistical Learning to ...", "date": "", "ddg_snippet": "20 Jun 2025 — Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials.", "subpage_snippet": "", "source": "advanced.onlinelibrary.wiley.com", "link": "https://advanced.onlinelibrary.wiley.com/doi/10.1002/aidi.202500033", "content": "20 Jun 2025 — Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials."}
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| 8 |
+
{"idx": 7, "title": "Machine Learning: Algorithms, Real-World Applications ...", "date": "", "ddg_snippet": "by IH Sarker · 2021 · Cited by 6237 — The ultimate goal of a semi-supervised learning model is to provide a better outcome for prediction than that produced using the labeled data alone from the ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7983091/", "content": "by IH Sarker · 2021 · Cited by 6237 — The ultimate goal of a semi-supervised learning model is to provide a better outcome for prediction than that produced using the labeled data alone from the ..."}
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| 9 |
+
{"idx": 8, "title": "Nonlinear Boosting Projections for Ensemble Construction", "date": "", "ddg_snippet": "by N Garcıa-Pedrajas · 2007 · Cited by 123 — Abstract. In this paper we propose a novel approach for ensemble construction based on the use of nonlinear projections to achieve both accuracy and ...", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume8/garcia-pedrajas07a/garcia-pedrajas07a.pdf", "content": "by N Garcıa-Pedrajas · 2007 · Cited by 123 — Abstract. In this paper we propose a novel approach for ensemble construction based on the use of nonlinear projections to achieve both accuracy and ..."}
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| 10 |
+
{"idx": 9, "title": "Comparison of machine learning methods for automatic ...", "date": "", "ddg_snippet": "by D Eriksson · 2023 · Cited by 10 — We use four different datasets as training data and first compare the model's accuracy on predicting operator commands. We then deploy and evaluate the efficacy ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0926580523001036", "content": "by D Eriksson · 2023 · Cited by 10 — We use four different datasets as training data and first compare the model's accuracy on predicting operator commands. We then deploy and evaluate the efficacy ..."}
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data/sampled_jsons/Abbasi-Yadkori_et_al._2011_OFUL_framework_paper_title_year_2011.jsonl
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{"idx": 0, "title": "[1609.01508] Low-rank Bandits with Latent Mixtures", "date": "", "ddg_snippet": "by A Gopalan · 2016 · Cited by 36 — It combines the Robust Tensor Power Method of Anandkumar et al . (2014b) with the OFUL linear bandit algorithm of Abbasi - Yadkori et al . ( 2011 ).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1609.01508", "content": "by A Gopalan · 2016 · Cited by 36 — It combines the Robust Tensor Power Method of Anandkumar et al . (2014b) with the OFUL linear bandit algorithm of Abbasi - Yadkori et al . ( 2011 )."}
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+
{"idx": 1, "title": "Multi-task Representation Learning with Stochastic Linear ...", "date": "", "ddg_snippet": "by L Cella · 2023 · Cited by 32 — Contextual bandits ( Abbasi - Yadkori et al ., 2011 ; Li et al .,. 2010; Auer, 2002) are a prominent learning framework to study sequential decision problems with ... 26 pages", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v206/cella23a/cella23a.pdf", "content": "by L Cella · 2023 · Cited by 32 — Contextual bandits ( Abbasi - Yadkori et al ., 2011 ; Li et al .,. 2010; Auer, 2002) are a prominent learning framework to study sequential decision problems with ... 26 pages"}
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+
{"idx": 2, "title": "Minimum Empirical Divergence for Sub-Gaussian Linear ...", "date": "", "ddg_snippet": "by K Balagopalan · 2024 · Cited by 1 — ... OFUL ( Abbasi - yadkori et al ., 2011 ). Our empirical study shows that LinMED has a competitive performance with the state-of-the-art algorithms.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2411.00229", "content": "by K Balagopalan · 2024 · Cited by 1 — ... OFUL ( Abbasi - yadkori et al ., 2011 ). Our empirical study shows that LinMED has a competitive performance with the state-of-the-art algorithms."}
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{"idx": 3, "title": "Sequential experimental design for transductive linear bandits", "date": "", "ddg_snippet": "In this paper we introduce the pure exploration transductive linear bandit problem: given a set of measurement vectors Χ ⊂ ℝ d , a set of items Ƶ ⊂ ℝ d , ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3454287.3455244", "content": "In this paper we introduce the pure exploration transductive linear bandit problem: given a set of measurement vectors Χ ⊂ ℝ d , a set of items Ƶ ⊂ ℝ d , ..."}
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{"idx": 4, "title": "Provably Efficient Reinforcement Learning with Linear Function ...", "date": "", "ddg_snippet": "When we prepare this paper , we notice a concurrent work by Gao et al . ... ( 2011 ) proposed a rarely switching OFUL ... policy switch model ( Abbasi - Yadkori et al ., ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/references/pdf?id=1Vb3iIEDC-", "content": "When we prepare this paper , we notice a concurrent work by Gao et al . ... ( 2011 ) proposed a rarely switching OFUL ... policy switch model ( Abbasi - Yadkori et al ., ..."}
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+
{"idx": 5, "title": "[PDF] Multi-task Linear Bandits", "date": "", "ddg_snippet": "This work proposes a simple but efficient framework to provably and ... Improved Algorithms for Linear Stochastic Bandits · Yasin Abbasi - Yadkori D. Pál ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Multi-task-Linear-Bandits-Soare/b7c1c4ae5254ef79a1f41690a24edcf91f81e577", "content": "This work proposes a simple but efficient framework to provably and ... Improved Algorithms for Linear Stochastic Bandits · Yasin Abbasi - Yadkori D. Pál ..."}
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{"idx": 6, "title": "Online Learning and Decision-Making under Generalized Linear ...", "date": "", "ddg_snippet": "OLS-Bandit by Goldenshluger and Zeevi 2013 and OFUL by Abbasi-Yadkori et al. 2011 , and in high-dimensional settings, Lasso-Bandit by Bastani and Bayati 2015 ...", "subpage_snippet": "", "source": "papers.ssrn.com", "link": "https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID3777611_code1195516.pdf?abstractid=3294832", "content": "OLS-Bandit by Goldenshluger and Zeevi 2013 and OFUL by Abbasi-Yadkori et al. 2011 , and in high-dimensional settings, Lasso-Bandit by Bastani and Bayati 2015 ..."}
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+
{"idx": 7, "title": "Minimum Empirical Divergence for Sub-Gaussian Linear Bandits", "date": "", "ddg_snippet": "by K Balagopalan · Cited by 1 — In this paper , we propose a novel linear bandit al- gorithm called LinMED ... OFUL ( Abbasi - Yadkori et al ., 2011 ). LinMED stands out even more when ...", "subpage_snippet": "", "source": "raw.githubusercontent.com", "link": "https://raw.githubusercontent.com/mlresearch/v258/main/assets/balagopalan25a/balagopalan25a.pdf", "content": "by K Balagopalan · Cited by 1 — In this paper , we propose a novel linear bandit al- gorithm called LinMED ... OFUL ( Abbasi - Yadkori et al ., 2011 ). LinMED stands out even more when ..."}
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| 9 |
+
{"idx": 8, "title": "Reinforcement Learning in Structured and Partially Observable ...", "date": "", "ddg_snippet": ", as ˆθt, up to a new high probability confidence set Cd,t. This is the same confidence set generation subroutine of OFUL Abbasi - Yadkori et al . ( 2011 ).", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/pdf/reinforcement-learning-in-structured-and-partially-2sq5lezwuo.pdf", "content": ", as ˆθt, up to a new high probability confidence set Cd,t. This is the same confidence set generation subroutine of OFUL Abbasi - Yadkori et al . ( 2011 )."}
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{"idx": 9, "title": "Online Learning and Decision Making Under Generalized ...", "date": "", "ddg_snippet": "by X Wang · 2024 · Cited by 8 — We propose a minimax concave penalized multiarmed bandit algorithm under the generalized linear model (G-MCP-Bandit) for decision-makers ...", "subpage_snippet": "", "source": "pubsonline.informs.org", "link": "https://pubsonline.informs.org/doi/10.1287/mnsc.2022.01557", "content": "by X Wang · 2024 · Cited by 8 — We propose a minimax concave penalized multiarmed bandit algorithm under the generalized linear model (G-MCP-Bandit) for decision-makers ..."}
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data/sampled_jsons/Abnormal_Behavioral_Pattern_connectivity_metric_conn(a_b)_Tor_anomalous_circuits.jsonl
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{"idx": 0, "title": "abnormal behavioral responses: Topics by ...", "date": "", "ddg_snippet": "This review discusses the role of abnormal connections in each CSTC circuit , especially in the emotion circuit , which may be responsible for targeted ...", "subpage_snippet": "", "source": "www.science.gov", "link": "https://www.science.gov/topicpages/a/abnormal+behavioral+responses", "content": "This review discusses the role of abnormal connections in each CSTC circuit , especially in the emotion circuit , which may be responsible for targeted ..."}
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+
{"idx": 1, "title": "Graph Measure Based Connectivity in Chronic Pain Patients", "date": "", "ddg_snippet": "by D Lenoir · 2021 · Cited by 22 — Edges in the structural connectome (SC) can be defined as the correlation between grey matter metrics . (such as cortical thickness or surface area) of 2 nodes,.", "subpage_snippet": "", "source": "www.painphysicianjournal.com", "link": "https://www.painphysicianjournal.com/current/pdf?article=NzM0OA==&journal=139", "content": "by D Lenoir · 2021 · Cited by 22 — Edges in the structural connectome (SC) can be defined as the correlation between grey matter metrics . (such as cortical thickness or surface area) of 2 nodes,."}
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{"idx": 2, "title": "Hierarchical behavioral analysis framework as a platform ...", "date": "", "ddg_snippet": "by J Ye · 2025 — Here, we developed a hierarchical behav- ioral analysis framework (HBAF) that efficiently reveals the organizational logic of these modules by ... 25 pages", "subpage_snippet": "", "source": "www.cell.com", "link": "https://www.cell.com/cell-reports/pdf/S2211-1247(25)00010-5.pdf", "content": "by J Ye · 2025 — Here, we developed a hierarchical behav- ioral analysis framework (HBAF) that efficiently reveals the organizational logic of these modules by ... 25 pages"}
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{"idx": 3, "title": "Vulnerability factors and neuropsychiatric disorders", "date": "", "ddg_snippet": "by E Daprati · 2022 — We argue that inter-individual differences in healthy cognitive style can inform on vulnerability traits or endophenotypes for disease.", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9815448/", "content": "by E Daprati · 2022 — We argue that inter-individual differences in healthy cognitive style can inform on vulnerability traits or endophenotypes for disease."}
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{"idx": 4, "title": "Bridging Neuroscience and Psychiatry through Brain ...", "date": "", "ddg_snippet": "by MM Naffaa · 2024 · Cited by 3 — This review explores the complex interplay between neu- ral circuits , neurobiology, and the treatment of psychiatric disorders, specifically ... 21 pages", "subpage_snippet": "", "source": "cellnatsci.com", "link": "https://cellnatsci.com/wp-content/uploads/2025/08/10-61474-ncs-2024-00051.pdf", "content": "by MM Naffaa · 2024 · Cited by 3 — This review explores the complex interplay between neu- ral circuits , neurobiology, and the treatment of psychiatric disorders, specifically ... 21 pages"}
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{"idx": 5, "title": "BRAIN COMMUNICATIONS AIN COMMUNICATIONS", "date": "", "ddg_snippet": "by D Szczupak · 2021 · Cited by 12 — These results point to a reorganization of structural brain connectivity in HP subjects, leading to abnormal and in- coherent functional connectivity patterns ... 11 pages", "subpage_snippet": "", "source": "academic.oup.com", "link": "https://academic.oup.com/braincomms/article-pdf/3/2/fcab057/41723878/fcab057.pdf", "content": "by D Szczupak · 2021 · Cited by 12 — These results point to a reorganization of structural brain connectivity in HP subjects, leading to abnormal and in- coherent functional connectivity patterns ... 11 pages"}
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{"idx": 6, "title": "Complex functional brain network properties in anorexia ...", "date": "", "ddg_snippet": "by A Gupta · 2022 · Cited by 13 — We aimed to test the hypothesis that individuals with AN demonstrate lower connectivity and centrality in core regions of sensorimotor networks, and greater.", "subpage_snippet": "", "source": "dibs-web01.vm.duke.edu", "link": "https://dibs-web01.vm.duke.edu/labar/pdfs/Gupta_et_al_2022.pdf", "content": "by A Gupta · 2022 · Cited by 13 — We aimed to test the hypothesis that individuals with AN demonstrate lower connectivity and centrality in core regions of sensorimotor networks, and greater."}
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{"idx": 7, "title": "Evolution of brain functional plasticity associated with ...", "date": "", "ddg_snippet": "by C Wang · 2022 · Cited by 21 — A link prediction model achieved an excellent predictive performance in estimating connectivity of more severe myelopathic stages of DCM, with the highest area ...", "subpage_snippet": "", "source": "www.thelancet.com", "link": "https://www.thelancet.com/pdfs/journals/ebiom/PIIS2352-3964(22)00437-6.pdf", "content": "by C Wang · 2022 · Cited by 21 — A link prediction model achieved an excellent predictive performance in estimating connectivity of more severe myelopathic stages of DCM, with the highest area ..."}
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| 9 |
+
{"idx": 8, "title": "Dissociable Disruptions in Thalamic and Hippocampal ...", "date": "", "ddg_snippet": "by C Schleifer · 2019 · Cited by 44 — In humans, 22q11DS presents a compelling genetic high-risk model where anomalous circuitry can be investigated before overt illness development. Specifically, ...", "subpage_snippet": "", "source": "escholarship.org", "link": "https://escholarship.org/content/qt0p35q8bk/qt0p35q8bk_noSplash_7de21f4feccd7d1f360f8048f4f69ff2.pdf", "content": "by C Schleifer · 2019 · Cited by 44 — In humans, 22q11DS presents a compelling genetic high-risk model where anomalous circuitry can be investigated before overt illness development. Specifically, ..."}
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{"idx": 9, "title": "The resting-state brain activity signatures for addictive ...", "date": "", "ddg_snippet": "by H Zheng · 2024 · Cited by 14 — This study aimed to uncover common and unique patterns of abnormal brain activity in individuals with substance use disorder (SUD) and ...", "subpage_snippet": "", "source": "www.cell.com", "link": "https://www.cell.com/med/pdf/S2666-6340(24)00038-2.pdf", "content": "by H Zheng · 2024 · Cited by 14 — This study aimed to uncover common and unique patterns of abnormal brain activity in individuals with substance use disorder (SUD) and ..."}
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data/sampled_jsons/Accelerating_Linear_Recurrent_Neural_Networks_for_the_Edge_with_Unstructured_Sparsity.jsonl
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{"idx": 0, "title": "UnIT: Scalable Unstructured Inference-Time Pruning for", "date": "", "ddg_snippet": "Deploying deep neural networks (DNNs) on low-power microcontroller units (MCUs) is essential for enabling edge intelligence in domains such as ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.07885v1", "content": "Deploying deep neural networks (DNNs) on low-power microcontroller units (MCUs) is essential for enabling edge intelligence in domains such as ..."}
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{"idx": 1, "title": "SparseDPD: A Sparse Neural Network-based Digital Predistortion", "date": "", "ddg_snippet": "... accelerator employing a spatially sparse phase-normalized time-delay neural network (PNTDNN), optimized through unstructured pruning to reduce ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.16591v1", "content": "... accelerator employing a spatially sparse phase-normalized time-delay neural network (PNTDNN), optimized through unstructured pruning to reduce ..."}
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| 3 |
+
{"idx": 2, "title": "Accelerating LLM Inference with Flexible N:M Sparsity via A", "date": "", "ddg_snippet": "... we present a pruning algorithm that can assign different N:M sparsity with a higher degree of freedom and then present the first DCiM accelerator to ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.14365v1", "content": "... we present a pruning algorithm that can assign different N:M sparsity with a higher degree of freedom and then present the first DCiM accelerator to ..."}
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| 4 |
+
{"idx": 3, "title": "GitHub - he-y/Awesome-Pruning: A curated list of neural network", "date": "", "ddg_snippet": "... title={Structured Pruning for Deep Convolutional Neural Networks ... Joint Edge -Model Sparse Learning is Provably Efficient for Graph Neural Networks", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/he-y/Awesome-Pruning", "content": "... title={Structured Pruning for Deep Convolutional Neural Networks ... Joint Edge -Model Sparse Learning is Provably Efficient for Graph Neural Networks"}
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| 5 |
+
{"idx": 4, "title": "From Bayesian Sparsity to Gated Recurrent Nets", "date": "", "ddg_snippet": "This paper proposes the use of gated feedback gated recurrent unit network (GFGRU), a learning-based sparse estimation algorithm, for multiple source ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/317543453_From_Bayesian_Sparsity_to_Gated_Recurrent_Nets", "content": "This paper proposes the use of gated feedback gated recurrent unit network (GFGRU), a learning-based sparse estimation algorithm, for multiple source ..."}
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+
{"idx": 5, "title": "ImageNet Classification with Deep Convolutional Neural Networks", "date": "", "ddg_snippet": "Recently, to improve the accuracy of image retrieval, feature extraction methods based on convolutional neural networks (CNN) have been proposed [11 ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/267960550_ImageNet_Classification_with_Deep_Convolutional_Neural_Networks", "content": "Recently, to improve the accuracy of image retrieval, feature extraction methods based on convolutional neural networks (CNN) have been proposed [11 ..."}
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+
{"idx": 6, "title": "US20220108157A1 - Hardware architecture for introducing", "date": "", "ddg_snippet": "Neural network 200 may represent different ... Neural network 200 may also be a hierarchical temporal memory system as described, for example, in U.S.", "subpage_snippet": "", "source": "patents.google.com", "link": "https://patents.google.com/patent/US20220108157A1/en", "content": "Neural network 200 may represent different ... Neural network 200 may also be a hierarchical temporal memory system as described, for example, in U.S."}
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| 8 |
+
{"idx": 7, "title": "Neuro-inspired Ensemble-to-Ensemble Communication Primitives", "date": "", "ddg_snippet": "These vectors are concatenated and passed through a feed-forward network with a predefined sparse structure , inspired by group-to-group ( neural ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.14140v1", "content": "These vectors are concatenated and passed through a feed-forward network with a predefined sparse structure , inspired by group-to-group ( neural ..."}
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| 9 |
+
{"idx": 8, "title": "SpikeX: Exploring Accelerator Architecture and Network-Hardware", "date": "", "ddg_snippet": "The previous generations of accelerators do not maximally optimize for the unique dataflow opportunities of spiking neural networks , especially as ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.12292v1", "content": "The previous generations of accelerators do not maximally optimize for the unique dataflow opportunities of spiking neural networks , especially as ..."}
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+
{"idx": 9, "title": "Downloads", "date": "", "ddg_snippet": "Accelerated Primal-Dual Gradient Method for ... A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/Downloads/2022", "content": "Accelerated Primal-Dual Gradient Method for ... A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks"}
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data/sampled_jsons/Ad-Hoc_Human-AI_Coordination_Challenge_HDR-IPPO_CHDR-IPPO.jsonl
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{"idx": 0, "title": "Ad-Hoc Human-AI Coordination Challenge - arXiv.org", "date": "", "ddg_snippet": "We develop four human proxy agents for evaluating ad-hoc human-AI coordination : two for two-player Hanabi and two for three-player. These agents are trained using Human -Data-Regularised IPPO ( HDR-IPPO ), a procedure combining BC and regularised IPPO (de Witt et al., 2020).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.21490", "content": "We develop four human proxy agents for evaluating ad-hoc human-AI coordination : two for two-player Hanabi and two for three-player. These agents are trained using Human -Data-Regularised IPPO ( HDR-IPPO ), a procedure combining BC and regularised IPPO (de Witt et al., 2020)."}
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| 2 |
+
{"idx": 1, "title": "Ad-Hoc Human-AI Coordination Challenge (AH2AC2) - GitHub", "date": "", "ddg_snippet": "Welcome to the Ad-Hoc Human-AI Coordination Challenge (AH2AC2)! The objective of AH2AC2 is to facilitate the development of AI agents capable of effective collaboration with human -like partners, especially in scenarios with limited prior interaction data.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/FLAIROx/ah2ac2", "content": "Welcome to the Ad-Hoc Human-AI Coordination Challenge (AH2AC2)! The objective of AH2AC2 is to facilitate the development of AI agents capable of effective collaboration with human -like partners, especially in scenarios with limited prior interaction data."}
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| 3 |
+
{"idx": 2, "title": "Ad-Hoc Human-AI Coordination Challenge (AH2AC2) Docs", "date": "", "ddg_snippet": "The AH2AC2 Challenge The Ad-Hoc Human-AI Coordination Challenge (AH2AC2) provides a standardized environment for evaluating AI agents on their ability to coordinate with human -like counterparts in Hanabi. The challenge emphasizes data-efficient methods and uses human proxy agents for robust and reproducible evaluation.", "subpage_snippet": "", "source": "docs.ah2ac2.com", "link": "https://docs.ah2ac2.com/", "content": "The AH2AC2 Challenge The Ad-Hoc Human-AI Coordination Challenge (AH2AC2) provides a standardized environment for evaluating AI agents on their ability to coordinate with human -like counterparts in Hanabi. The challenge emphasizes data-efficient methods and uses human proxy agents for robust and reproducible evaluation."}
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| 4 |
+
{"idx": 3, "title": "Ad-Hoc Human-AI Coordination Challenge - Science Cast", "date": "", "ddg_snippet": "Jun 25, 2025 · In this work, we introduce the Ad-Hoc Human-AI Coordination Challenge (AH2AC2) to overcome the constraints of costly and difficult-to-reproduce human evaluations. We develop \\textit { human proxy agents} on a large-scale human dataset that serve as robust, cheap, and reproducible human -like evaluation partners in AH2AC2.", "subpage_snippet": "", "source": "www.sciencecast.org", "link": "https://www.sciencecast.org/casts/q62pr180dj73", "content": "Jun 25, 2025 · In this work, we introduce the Ad-Hoc Human-AI Coordination Challenge (AH2AC2) to overcome the constraints of costly and difficult-to-reproduce human evaluations. We develop \\textit { human proxy agents} on a large-scale human dataset that serve as robust, cheap, and reproducible human -like evaluation partners in AH2AC2."}
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| 5 |
+
{"idx": 4, "title": "Ad-Hoc Human-AI Coordination Challenge - Semantic Scholar", "date": "", "ddg_snippet": "Table 15. Hyperparameters used for training BC, HDR-IPPO baselines on a 1,000-game data limit challenge . BC policies trained as baselines are used for starting points in HDR-IPPO and later for BR-BC. - \" Ad-Hoc Human-AI Coordination Challenge \"", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Ad-Hoc-Human-AI-Coordination-Challenge-Dizdarevic-Hammond/76e21098d2925daeb769a647c9af4886d00b05fd/figure/21", "content": "Table 15. Hyperparameters used for training BC, HDR-IPPO baselines on a 1,000-game data limit challenge . BC policies trained as baselines are used for starting points in HDR-IPPO and later for BR-BC. - \" Ad-Hoc Human-AI Coordination Challenge \""}
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| 6 |
+
{"idx": 5, "title": "AD-HOC HUMAN-AI COORDINATION CHALLENGE - OpenReview", "date": "", "ddg_snippet": "nd regularised reinforcement learning. These proxies serve as robust, cheap and reproducible human -like evaluation partners in our Ad-Hoc Hu an- AI Coordination Challenge (AH2AC2). To facilitate the exploration of methods that leverage limited amounts of human data, we introduce a data-limited chal-lenge setting, u", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=Kioojohsuy", "content": "nd regularised reinforcement learning. These proxies serve as robust, cheap and reproducible human -like evaluation partners in our Ad-Hoc Hu an- AI Coordination Challenge (AH2AC2). To facilitate the exploration of methods that leverage limited amounts of human data, we introduce a data-limited chal-lenge setting, u"}
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| 7 |
+
{"idx": 6, "title": "Ad-Hoc Human-AI Coordination Challenge | AI Research Paper ...", "date": "", "ddg_snippet": "The researchers developed four human proxy agents for evaluating ad-hoc human-AI coordination : two for two-player Hanabi and two for three-player. These agents are trained using Human -Data-Regularised IPPO ( HDR-IPPO ), a procedure combining behavioral cloning (BC) and regularized Independent Proximal Policy Optimization ( IPPO ).", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/ad-hoc-human-ai-coordination-challenge", "content": "The researchers developed four human proxy agents for evaluating ad-hoc human-AI coordination : two for two-player Hanabi and two for three-player. These agents are trained using Human -Data-Regularised IPPO ( HDR-IPPO ), a procedure combining behavioral cloning (BC) and regularized Independent Proximal Policy Optimization ( IPPO )."}
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| 8 |
+
{"idx": 7, "title": "Ad - Hoc Human - AI Coordination Challenge", "date": "", "ddg_snippet": "Figure 1: Ad - Hoc Human - AI Coordination Challenge (AH2AC2). In summary, our key contributions are• Implementations for Human - AI Coordination evaluations for all baselines except FCP, as the FCP implementation is in its final testing phase. A.8 HDR - IPPO : Ablation Study.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.21490v1", "content": "Figure 1: Ad - Hoc Human - AI Coordination Challenge (AH2AC2). In summary, our key contributions are• Implementations for Human - AI Coordination evaluations for all baselines except FCP, as the FCP implementation is in its final testing phase. A.8 HDR - IPPO : Ablation Study."}
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| 9 |
+
{"idx": 8, "title": "Ad - Hoc Human - AI Coordination Challenge", "date": "", "ddg_snippet": "Ad - Hoc Human - AI Coordination Challenge . Tin Dizdarević, Ravi Hammond, Tobias Gessler, Anisoara Calinescu, Jonathan Cook, Matteo Gallici, Andrei Lupu, Jakob Nicolaus Foerster·June 26, 2025. Summary.Overview of human - AI coordination challenges .", "subpage_snippet": "", "source": "powerdrill.ai", "link": "https://powerdrill.ai/discover/summary-ad-hoc-human-ai-coordination-challenge-cmcfaq3ifm18907nqbp2j6wty", "content": "Ad - Hoc Human - AI Coordination Challenge . Tin Dizdarević, Ravi Hammond, Tobias Gessler, Anisoara Calinescu, Jonathan Cook, Matteo Gallici, Andrei Lupu, Jakob Nicolaus Foerster·June 26, 2025. Summary.Overview of human - AI coordination challenges ."}
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{"idx": 9, "title": "Human - AI Cross-Play Experiments", "date": "", "ddg_snippet": "Explore Human - AI cross-play experiments investigating interaction, collaboration, and competition in shared environments to understand AI capabilities, alignment, and compatibility with humans.", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/topics/human-ai-cross-play-experiments", "content": "Explore Human - AI cross-play experiments investigating interaction, collaboration, and competition in shared environments to understand AI capabilities, alignment, and compatibility with humans."}
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data/sampled_jsons/Adaptive_Task_Allocation_for_Efficient_Resource_Management_in_Distributed_Machine_Learning_GTA_strat_year_2023.jsonl
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{"idx": 0, "title": "[2502.00775v1] ATA: Adaptive Task Allocation for Efficient ...", "date": "", "ddg_snippet": "View a PDF of the paper titled ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning , by Artavazd Maranjyan and 3 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00775v1", "content": "View a PDF of the paper titled ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning , by Artavazd Maranjyan and 3 other authors."}
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{"idx": 1, "title": "Adaptive Task Allocation for Efficient Resource Management in ...", "date": "", "ddg_snippet": "Ideally, faster machines would handle more tasks , and slower ones fewer — but without knowing speeds in advance, this is challenging.We introduce ATA ( Adaptive Task Allocation ), a method that learns how fast each machine is over time and adapts the task assignment accordingly.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46650", "content": "Ideally, faster machines would handle more tasks , and slower ones fewer — but without knowing speeds in advance, this is challenging.We introduce ATA ( Adaptive Task Allocation ), a method that learns how fast each machine is over time and adapts the task assignment accordingly."}
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+
{"idx": 2, "title": "Postdoc, KAUST - Cited by 12 - Online learning - Bandits theory", "date": "", "ddg_snippet": "Ata: Adaptive task allocation for efficient resource management in distributed machine learning .", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=Jih_bwsAAAAJ&hl=en", "content": "Ata: Adaptive task allocation for efficient resource management in distributed machine learning ."}
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{"idx": 3, "title": "ATA: Adaptive Task Allocation", "date": "", "ddg_snippet": "ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning .", "subpage_snippet": "", "source": "artomaranjyan.github.io", "link": "https://artomaranjyan.github.io/assets/pdf/posters/ATA_SNSL.pdf", "content": "ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning ."}
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| 5 |
+
{"idx": 4, "title": "The Importance of Adaptive Task Allocation in Distributed Robotics", "date": "", "ddg_snippet": "Learn about the significance of adaptive task allocation , a method that dynamically assigns tasks based on real-time data and environmental conditions.", "subpage_snippet": "", "source": "diversedaily.com", "link": "https://diversedaily.com/the-importance-of-adaptive-task-allocation-in-distributed-robotics/", "content": "Learn about the significance of adaptive task allocation , a method that dynamically assigns tasks based on real-time data and environmental conditions."}
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| 6 |
+
{"idx": 5, "title": "Quantum Inspired Adaptive Resource Management Algorithm for...", "date": "", "ddg_snippet": "Effective resource management in the Internet of Things and fog computing is essential for efficient and scalable networks.FRATO: fog resource based adaptive task offloading for delay-minimizing IoT service provisioning. IEEE Trans Parallel Distrib Syst.", "subpage_snippet": "", "source": "www.sciopen.com", "link": "https://www.sciopen.com/article/10.32604/cmes.2025.060973", "content": "Effective resource management in the Internet of Things and fog computing is essential for efficient and scalable networks.FRATO: fog resource based adaptive task offloading for delay-minimizing IoT service provisioning. IEEE Trans Parallel Distrib Syst."}
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| 7 |
+
{"idx": 6, "title": "ELDM-EDSDN: a novel resource allocation method in...", "date": "", "ddg_snippet": "The over-reliance of current methods for task allocation and resource management in distributed software-defined networks (DSDN) on constraints and predefined assumptions about network behavior leads to severe efficiency degradation in operational environments.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s11227-025-07817-3", "content": "The over-reliance of current methods for task allocation and resource management in distributed software-defined networks (DSDN) on constraints and predefined assumptions about network behavior leads to severe efficiency degradation in operational environments."}
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+
{"idx": 7, "title": "DyRAM: Dynamic Data Allocation and Resource Management in ...", "date": "", "ddg_snippet": "keywords = \"Data Distribution , Distributed Machine Learning , Resource Management \", author = \"Vaibhavi Tiwari and Rahul Thakkar and Jiayin Wang\"", "subpage_snippet": "", "source": "researchwith.montclair.edu", "link": "https://researchwith.montclair.edu/en/publications/dyram-dynamic-data-allocation-and-resource-management-in-distribu", "content": "keywords = \"Data Distribution , Distributed Machine Learning , Resource Management \", author = \"Vaibhavi Tiwari and Rahul Thakkar and Jiayin Wang\""}
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| 9 |
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{"idx": 8, "title": "History of Machine Learning : How We Got Here", "date": "", "ddg_snippet": "As machine learning keeps evolving and adapting , we can anticipate continued advancements in domains like quantum computing, unsupervised learning , and the establishment of cognitive services.", "subpage_snippet": "", "source": "www.akkio.com", "link": "https://www.akkio.com/post/history-of-machine-learning", "content": "As machine learning keeps evolving and adapting , we can anticipate continued advancements in domains like quantum computing, unsupervised learning , and the establishment of cognitive services."}
|
| 10 |
+
{"idx": 9, "title": "Energy Aware Task Allocation for Semi-Asynchronous Mobile Edge...", "date": "", "ddg_snippet": "Adaptive task allocation for asynchronous federated and parallelized mobile edge learning .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/368533748_Energy_Aware_Task_Allocation_for_Semi-Asynchronous_Mobile_Edge_Learning", "content": "Adaptive task allocation for asynchronous federated and parallelized mobile edge learning ."}
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data/sampled_jsons/Adcock_Collier_2001_paper_title_year_2001.jsonl
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{"idx": 0, "title": "Adcock y Collier (2001) - Measurement Validity. A Shared ... - Scribd", "date": "", "ddg_snippet": "Adcock y Collier ( 2001 ). Measurement Validity. a Shared Standart for Qualitative and Quantitative Research. - Free download as PDF File (.pdf), Text File (.txt) or read online for free.", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/520421528/Adcock-y-Collier-2001-Measurement-Validity-a-Shared-Standart-for-Qualitative-and-Quantitative-Research", "content": "Adcock y Collier ( 2001 ). Measurement Validity. a Shared Standart for Qualitative and Quantitative Research. - Free download as PDF File (.pdf), Text File (.txt) or read online for free."}
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| 2 |
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{"idx": 1, "title": "Adcock Collier 2001 Measurement Validity | PDF - Scribd", "date": "", "ddg_snippet": "Adcock Collier 2001 Measurement Validity - Free download as PDF File (.pdf), Text File (.txt) or read online for free.", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/797627345/Adcock-Collier-2001-Measurement-Validity", "content": "Adcock Collier 2001 Measurement Validity - Free download as PDF File (.pdf), Text File (.txt) or read online for free."}
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| 3 |
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{"idx": 2, "title": "Adcock & Collier (2001) Measurement Validity - A Shared Standard for ...", "date": "", "ddg_snippet": "The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.", "subpage_snippet": "", "source": "www.theisrm.org", "link": "https://www.theisrm.org/library/adcock-collier-2001-measurement-validity-a-shared-standard-for-qualitative-and-quantitative-research-pdf/", "content": "The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you."}
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| 4 |
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{"idx": 3, "title": "Measurement Validity: A Shared Standard for Qualitative and ...", "date": "", "ddg_snippet": "Robert Adcock (adcockr@uclink4.berkeley.edu) is a Ph.D candi- This literature provides an opportunity to identify date, Department of Political Science, and David Collier parallel concerns about validity as well as differences in (dcollier@socrates.berkeley.edu) is Professor of Political Science, specific practices.", "subpage_snippet": "", "source": "www.jstor.org", "link": "https://www.jstor.org/stable/3118231", "content": "Robert Adcock (adcockr@uclink4.berkeley.edu) is a Ph.D candi- This literature provides an opportunity to identify date, Department of Political Science, and David Collier parallel concerns about validity as well as differences in (dcollier@socrates.berkeley.edu) is Professor of Political Science, specific practices."}
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| 5 |
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{"idx": 4, "title": "(PDF) Measurement Validity: A Shared Standard For Qualitative and ...", "date": "", "ddg_snippet": "The literature has pointed to three different strategies for measurement validity ( Adcock and Collier 2001 ): content validity (the measurement captures the full content of the definition ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/228277142_Measurement_Validity_A_Shared_Standard_For_Qualitative_and_Quantitative_Research", "content": "The literature has pointed to three different strategies for measurement validity ( Adcock and Collier 2001 ): content validity (the measurement captures the full content of the definition ..."}
|
| 6 |
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{"idx": 5, "title": "Measurement validity: A shared standard for - ProQuest", "date": "", "ddg_snippet": "Measurement validity: A shared standard for qualitative and quantitative research Adcock , Robert; Collier , David. The American Political Science Review; Washington Vol. 95, Iss. 3, (Sep 2001 ): 529-546.", "subpage_snippet": "", "source": "www.proquest.com", "link": "https://www.proquest.com/docview/214424808", "content": "Measurement validity: A shared standard for qualitative and quantitative research Adcock , Robert; Collier , David. The American Political Science Review; Washington Vol. 95, Iss. 3, (Sep 2001 ): 529-546."}
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{"idx": 6, "title": "Measurement Validity: A Shared Standard for Qualitative and ...", "date": "", "ddg_snippet": "Measurement Validity: A Shared Standard for Qualitative and Quantitative Research Robert Adcock , David Collier +1 more - 31 Aug 2001 - American Political Science Review - Vol. 95, Iss: 3, pp 529-546", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/measurement-validity-a-shared-standard-for-qualitative-and-2r00s4iydu", "content": "Measurement Validity: A Shared Standard for Qualitative and Quantitative Research Robert Adcock , David Collier +1 more - 31 Aug 2001 - American Political Science Review - Vol. 95, Iss: 3, pp 529-546"}
|
| 8 |
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{"idx": 7, "title": "Measurement Validity: A Shared Standard for Qualitative and ...", "date": "", "ddg_snippet": "Google Scholar Collier , David, and Adcock , Robert. 1999. \"Democracy and Dichotomies: A Pragmatic Approach to Choices about Concepts.\" Annual Review of Political Science 2: 537 - 65. CrossRef Google Scholar Collier , David, and Levitsky, Steven. 1997. \" Democracy with Adjectives: Conceptual Innovation in Comparative Research.", "subpage_snippet": "", "source": "www.cambridge.org", "link": "https://www.cambridge.org/core/journals/american-political-science-review/article/abs/measurement-validity-a-shared-standard-for-qualitative-and-quantitative-research/91C7A9800DB26A76EBBABC5889A50C8B", "content": "Google Scholar Collier , David, and Adcock , Robert. 1999. \"Democracy and Dichotomies: A Pragmatic Approach to Choices about Concepts.\" Annual Review of Political Science 2: 537 - 65. CrossRef Google Scholar Collier , David, and Levitsky, Steven. 1997. \" Democracy with Adjectives: Conceptual Innovation in Comparative Research."}
|
| 9 |
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{"idx": 8, "title": "PDF Measurement Validity: A Shared Standard for Qualitative and ...", "date": "", "ddg_snippet": "ROBERT ADCOCK and DAVID COLLIER University of California, Berkeley Scholars routinely make claims that presuppose the validity of the observations and measurements that operationalize their concepts. Yet, despite recent advances in political science methods, surprisingly little attention has been devoted to measurement validity. We address this gap by exploring four themes. First, we seek to ...", "subpage_snippet": "", "source": "www.theisrm.org", "link": "https://www.theisrm.org/documents/Adcock+&+Collier+(2001)+Measurement+Validity+-+A+Shared+Standard+for+Qualitative+and+Quantitative+Research.pdf", "content": "ROBERT ADCOCK and DAVID COLLIER University of California, Berkeley Scholars routinely make claims that presuppose the validity of the observations and measurements that operationalize their concepts. Yet, despite recent advances in political science methods, surprisingly little attention has been devoted to measurement validity. We address this gap by exploring four themes. First, we seek to ..."}
|
| 10 |
+
{"idx": 9, "title": "Measurement Validity: A Shared Standard for Qualitative and ...", "date": "", "ddg_snippet": "Measurement Validity: A Shared Standard for Qualitative and Quantitative Research Robert Adcock and David Collier American Political Science Review, 2001 , vol. 95, issue 3, 529-546 Abstract: Scholars routinely make claims that presuppose the validity of the observations and measurements that operationalize their concepts.", "subpage_snippet": "", "source": "econpapers.repec.org", "link": "https://econpapers.repec.org/RePEc:cup:apsrev:v:95:y:2001:i:03:p:529-546_00", "content": "Measurement Validity: A Shared Standard for Qualitative and Quantitative Research Robert Adcock and David Collier American Political Science Review, 2001 , vol. 95, issue 3, 529-546 Abstract: Scholars routinely make claims that presuppose the validity of the observations and measurements that operationalize their concepts."}
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data/sampled_jsons/Advancing_mathematics_by_guiding_human_intuition_with_AI_knot_theory_representation_theory.jsonl
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{"idx": 0, "title": "Artificial Intelligence in Knot Theory – AMR", "date": "", "ddg_snippet": "... Advancing Mathematics by Guiding Human Intuition with AI , the authors describe an application of neural networks to finding correlations between ...", "subpage_snippet": "", "source": "amathr.org", "link": "https://amathr.org/artificial-intelligence-in-knot-theory/", "content": "... Advancing Mathematics by Guiding Human Intuition with AI , the authors describe an application of neural networks to finding correlations between ..."}
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+
{"idx": 1, "title": "Advancing mathematics by guiding human intuition with AI |", "date": "", "ddg_snippet": "... framework, illustrated in Fig. 1 , describes a general method by which mathematicians can use tools from machine learning to guide their intuitions ...", "subpage_snippet": "", "source": "ddcolrs.wordpress.com", "link": "https://ddcolrs.wordpress.com/2021/12/04/advancing-mathematics-by-guiding-human-intuition-with-ai/", "content": "... framework, illustrated in Fig. 1 , describes a general method by which mathematicians can use tools from machine learning to guide their intuitions ..."}
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+
{"idx": 2, "title": "DeepMind’s AI can untangle knots. But does it guide human", "date": "", "ddg_snippet": "... coming from the Alphabet-owned artificial intelligence lab, the paper, which is titled “ Advancing mathematics by guiding human intuition with AI ...", "subpage_snippet": "", "source": "bdtechtalks.com", "link": "https://bdtechtalks.com/2021/12/13/deepminds-machine-learning-mathematics/", "content": "... coming from the Alphabet-owned artificial intelligence lab, the paper, which is titled “ Advancing mathematics by guiding human intuition with AI ..."}
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| 4 |
+
{"idx": 3, "title": "Sure, DeepMind’s AI is impressive, but can it guide human", "date": "", "ddg_snippet": "... coming from the Alphabet-owned artificial intelligence lab, the paper, which is titled “ Advancing mathematics by guiding human intuition with AI ...", "subpage_snippet": "", "source": "thenextweb.com", "link": "https://thenextweb.com/news/deepminds-ai-impressive-can-it-guide-human-intuition-syndication", "content": "... coming from the Alphabet-owned artificial intelligence lab, the paper, which is titled “ Advancing mathematics by guiding human intuition with AI ..."}
|
| 5 |
+
{"idx": 4, "title": "Mathematical discoveries take intuition and creativity, and now", "date": "", "ddg_snippet": "... with experts at artificial ... More information: Alex Davies et al, Advancing mathematics by guiding human intuition with AI , Nature (2021).", "subpage_snippet": "", "source": "techxplore.com", "link": "https://techxplore.com/news/2021-12-mathematical-discoveries-intuition-creativity-ai.html", "content": "... with experts at artificial ... More information: Alex Davies et al, Advancing mathematics by guiding human intuition with AI , Nature (2021)."}
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+
{"idx": 5, "title": "Augmenting Human Intuition", "date": "", "ddg_snippet": "Learn from Petar Veličković, author of \" Advancing mathematics by guiding human intuition with AI \", how machines empower researchers conjecturing ...", "subpage_snippet": "", "source": "picampus.it", "link": "https://picampus.it/events/augmenting-human-intuition/", "content": "Learn from Petar Veličković, author of \" Advancing mathematics by guiding human intuition with AI \", how machines empower researchers conjecturing ..."}
|
| 7 |
+
{"idx": 6, "title": "Mathematics, word problems, common sense, and artificial", "date": "", "ddg_snippet": "... the capacities and limitations of current artificial intelligence ( AI ) technology to solve word problems that combine elementary mathematics with ...", "subpage_snippet": "", "source": "sugaku.net", "link": "https://sugaku.net/oa/W4391836239/", "content": "... the capacities and limitations of current artificial intelligence ( AI ) technology to solve word problems that combine elementary mathematics with ..."}
|
| 8 |
+
{"idx": 7, "title": "Mathematics and Machine Creativity: A Survey on Bridging", "date": "", "ddg_snippet": "Notably, this survey challenges this perspective by presenting a fresh narrative: AI can indeed make meaningful contributions to mathematic research ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2412.16543v1?", "content": "Notably, this survey challenges this perspective by presenting a fresh narrative: AI can indeed make meaningful contributions to mathematic research ..."}
|
| 9 |
+
{"idx": 8, "title": "DeepMind AI Used To Develop New Math Techniques | Technology", "date": "", "ddg_snippet": "... guided by mathematical intuition , machine learning provides a powerful framework that ... Advancing mathematics by guiding human intuition with AI .", "subpage_snippet": "", "source": "www.technologynetworks.com", "link": "https://www.technologynetworks.com/neuroscience/news/deepmind-ai-used-to-develop-new-math-techniques-356418", "content": "... guided by mathematical intuition , machine learning provides a powerful framework that ... Advancing mathematics by guiding human intuition with AI ."}
|
| 10 |
+
{"idx": 9, "title": "AI-assisted mathematical discovery | London Institute for", "date": "", "ddg_snippet": "... mathematical constructs in number theory and ... His work concerns advancing mathematics by guiding human intuition with AI and geometric topology.", "subpage_snippet": "", "source": "lims.ac.uk", "link": "https://lims.ac.uk/event/ai-assisted-maths-discovery/", "content": "... mathematical constructs in number theory and ... His work concerns advancing mathematics by guiding human intuition with AI and geometric topology."}
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data/sampled_jsons/Algorithm_1_Data-Efficient_Visual_Concept_Bottleneck_Models_filter_concept_proposals_by_area.jsonl
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{"idx": 0, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "by K Prasse — This paper proposed a data - efficient Concept Bottleneck Model (DCBM) that enables concept generation while maintaining interpretability with ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=BdO4R6XxUH", "content": "by K Prasse — This paper proposed a data - efficient Concept Bottleneck Model (DCBM) that enables concept generation while maintaining interpretability with ..."}
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| 2 |
+
{"idx": 1, "title": "VLG-CBM: Training Concept Bottleneck Models with Vision ...", "date": "", "ddg_snippet": "Concept Bottleneck Models (CBMs) provide interpretable prediction by introducing an intermediate Concept Bottleneck Layer (CBL), which encodes human- ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2408.01432v2", "content": "Concept Bottleneck Models (CBMs) provide interpretable prediction by introducing an intermediate Concept Bottleneck Layer (CBL), which encodes human- ..."}
|
| 3 |
+
{"idx": 2, "title": "VLG-CBM: Training Concept Bottleneck Models with Vision ...", "date": "", "ddg_snippet": "by D Srivastava · 2024 · Cited by 22 — To address Challenge # 1 , we propose to use the open-domain grounded object detection model to generate localized, visually recognizable concept annotations in ... 38 pages", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper_files/paper/2024/file/90043ebd68500f9efe84fedf860a64f3-Paper-Conference.pdf", "content": "by D Srivastava · 2024 · Cited by 22 — To address Challenge # 1 , we propose to use the open-domain grounded object detection model to generate localized, visually recognizable concept annotations in ... 38 pages"}
|
| 4 |
+
{"idx": 3, "title": "Interpretable prognostics with concept bottleneck models", "date": "", "ddg_snippet": "by F Forest · 2025 · Cited by 3 — We propose concept bottleneck models for more interpretable prognostics, where degradation modes of an asset are used as intermediate concepts .", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S1566253525005007", "content": "by F Forest · 2025 · Cited by 3 — We propose concept bottleneck models for more interpretable prognostics, where degradation modes of an asset are used as intermediate concepts ."}
|
| 5 |
+
{"idx": 4, "title": "VLG-CBM: Training Concept Bottleneck Models with Vision ...", "date": "", "ddg_snippet": "We propose a novel framework called Vision -Language-Guided Concept Bottleneck Model (VLG-CBM) to enable faithful interpretability with the benefits of boosted ...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/poster/95698", "content": "We propose a novel framework called Vision -Language-Guided Concept Bottleneck Model (VLG-CBM) to enable faithful interpretability with the benefits of boosted ..."}
|
| 6 |
+
{"idx": 5, "title": "Editable Concept Bottleneck Models", "date": "", "ddg_snippet": "24 May 2024 — We propose Editable Concept Bottleneck Models (ECBMs). Specifically, ECBMs support three different levels of data removal: concept -label-level, concept -level, ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2405.15476v1", "content": "24 May 2024 — We propose Editable Concept Bottleneck Models (ECBMs). Specifically, ECBMs support three different levels of data removal: concept -label-level, concept -level, ..."}
|
| 7 |
+
{"idx": 6, "title": "CVPR Poster Incremental Residual Concept Bottleneck Models", "date": "", "ddg_snippet": "Concept Bottleneck Models (CBMs) map the black-box visual representations extracted by deep neural networks onto a set of interpretable concepts and use the ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2024/poster/29363", "content": "Concept Bottleneck Models (CBMs) map the black-box visual representations extracted by deep neural networks onto a set of interpretable concepts and use the ..."}
|
| 8 |
+
{"idx": 7, "title": "Navigating the landscape of concept-supported XAI", "date": "", "ddg_snippet": "by Z Shams Khoozani · 2024 · Cited by 9 — The Concept Bottleneck Model (CBM) proposed in [87] is based on the Bottleneck (BN) design and accepts input features such as pixels, denoted as ...", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s11042-023-17666-y", "content": "by Z Shams Khoozani · 2024 · Cited by 9 — The Concept Bottleneck Model (CBM) proposed in [87] is based on the Bottleneck (BN) design and accepts input features such as pixels, denoted as ..."}
|
| 9 |
+
{"idx": 8, "title": "Probabilistic Concept Bottleneck Models", "date": "", "ddg_snippet": "The concept predic- tion in CBM is trained as deterministic binary classification by using a dataset that includes concept labels indicating the existence ( 1 ) ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v202/kim23g/kim23g.pdf", "content": "The concept predic- tion in CBM is trained as deterministic binary classification by using a dataset that includes concept labels indicating the existence ( 1 ) ..."}
|
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{"idx": 9, "title": "Enhancing Interpretable Image Classification Through LLM ...", "date": "", "ddg_snippet": "by Y Jiang · 2025 — To address this issue, we introduce Condi- tional Concept Bottleneck Models (CoCoBMs) that incorporates category-specific scoring and weight-.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.acl-long.600.pdf", "content": "by Y Jiang · 2025 — To address this issue, we introduce Condi- tional Concept Bottleneck Models (CoCoBMs) that incorporates category-specific scoring and weight-."}
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data/sampled_jsons/Algorithm_1_delta_tilde_Statistical_Collusion_Collectives_Learning_Platforms_Appendix_B_year_2024.jsonl
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{"idx": 0, "title": "Statistical Collusion by Collectives on Learning Platforms", "date": "", "ddg_snippet": "As platforms increasingly rely on learning algorithms , collectives may form and seek ways to influence these platforms to align with their own interests. This can be achieved by coordinated submission of altered data. Appendix B Algorithms .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.04879v3", "content": "As platforms increasingly rely on learning algorithms , collectives may form and seek ways to influence these platforms to align with their own interests. This can be achieved by coordinated submission of altered data. Appendix B Algorithms ."}
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{"idx": 1, "title": "GitHub - GauthierE/statistical-collusion", "date": "", "ddg_snippet": "statistical-collusion This repository contains the code for reproducing the experiments and figures presented in the paper Statistical Collusion by Collectives on Learning Platforms .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/GauthierE/statistical-collusion", "content": "statistical-collusion This repository contains the code for reproducing the experiments and figures presented in the paper Statistical Collusion by Collectives on Learning Platforms ."}
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{"idx": 2, "title": "Statistical Collusion by Collectives on Learning Platforms | Read Paper ...", "date": "", "ddg_snippet": "This paper talks about how groups of people can work together to change the way online platforms use data and learning algorithms to benefit their interests. The authors created a method that help...", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/icml/46504/paper", "content": "This paper talks about how groups of people can work together to change the way online platforms use data and learning algorithms to benefit their interests. The authors created a method that help..."}
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{"idx": 3, "title": "Algorithmic Collective Action in Machine Learning - PMLR", "date": "", "ddg_snippet": "We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms . We propose a simple theoretical model of a collective interacting with a firm's learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v202/hardt23a.html", "content": "We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms . We propose a simple theoretical model of a collective interacting with a firm's learning algorithm . The collective pools the data of participating individuals and executes an algorithmic strategy by instructing participants how to modify their own data to achieve a ..."}
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{"idx": 4, "title": "Statistical Collusion by Collectives on Learning Platforms", "date": "", "ddg_snippet": "A framework is developed that provides a theoretical and algorithmic treatment of the issues of a priori assessments of the effect of the collective before taking action and presents experimental results in a product evaluation domain. As platforms increasingly rely on learning algorithms , collectives may form and seek ways to influence these platforms to align with their own interests. This ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Statistical-Collusion-by-Collectives-on-Learning-Gauthier-Bach/1c45ef9ad56839c3309f0a0bdcff50fbb3ad73f5", "content": "A framework is developed that provides a theoretical and algorithmic treatment of the issues of a priori assessments of the effect of the collective before taking action and presents experimental results in a product evaluation domain. As platforms increasingly rely on learning algorithms , collectives may form and seek ways to influence these platforms to align with their own interests. This ..."}
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{"idx": 5, "title": "PDF Statistical Collusion by Collectives on Learning Platforms", "date": "", "ddg_snippet": "Statistical Collusion by Collectives on Learning Platforms Etienne Gauthier, Francis Bach, Michael I. Jordan (INRIA, Ecole Normale Supérieure) Numerous examples of collectives emerging to strategically influence platforms Uber drivers deactivate the app to create a supply shortage and drive up prices", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/media/icml-2025/Slides/47263.pdf", "content": "Statistical Collusion by Collectives on Learning Platforms Etienne Gauthier, Francis Bach, Michael I. Jordan (INRIA, Ecole Normale Supérieure) Numerous examples of collectives emerging to strategically influence platforms Uber drivers deactivate the app to create a supply shortage and drive up prices"}
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{"idx": 6, "title": "Statistical Collusion by Collectives on Learning Platforms", "date": "", "ddg_snippet": "Technical Explanation The study develops mathematical frameworks for detecting coordinated manipulation of learning systems. It examines how collective behaviors create statistical signatures that differ from organic user patterns. The researchers analyzed multiple types of learning platforms , including:", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/statistical-collusion-by-collectives-learning-platforms", "content": "Technical Explanation The study develops mathematical frameworks for detecting coordinated manipulation of learning systems. It examines how collective behaviors create statistical signatures that differ from organic user patterns. The researchers analyzed multiple types of learning platforms , including:"}
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{"idx": 7, "title": "Statistical Collusion by Collectives on Learning Platforms", "date": "", "ddg_snippet": "Oral Statistical Collusion by Collectives on Learning Platforms Etienne Gauthier · Francis Bach · Michael Jordan West Ballroom D [ Abstract ] [ Visit Oral 6E Social and Economic Perspectives ] Thu 17 Jul 4 p.m. — 4:15 p.m. PDT Poster presentation: Statistical Collusion by Collectives on Learning Platforms Thu 17 Jul 4:30 p.m. PDT — 7 p.m. PDT", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/oral/47263", "content": "Oral Statistical Collusion by Collectives on Learning Platforms Etienne Gauthier · Francis Bach · Michael Jordan West Ballroom D [ Abstract ] [ Visit Oral 6E Social and Economic Perspectives ] Thu 17 Jul 4 p.m. — 4:15 p.m. PDT Poster presentation: Statistical Collusion by Collectives on Learning Platforms Thu 17 Jul 4:30 p.m. PDT — 7 p.m. PDT"}
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{"idx": 8, "title": "ICML Poster Statistical Collusion by Collectives on Learning ...", "date": "", "ddg_snippet": "As platforms increasingly rely on learning algorithms , collectives may form and seek ways to influence these platforms to align with their own interests. This can be achieved by coordinated submission of altered data.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46504", "content": "As platforms increasingly rely on learning algorithms , collectives may form and seek ways to influence these platforms to align with their own interests. This can be achieved by coordinated submission of altered data."}
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| 10 |
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{"idx": 9, "title": "Statistical Collusion by Collectives on Learning Platforms", "date": "", "ddg_snippet": "As platforms increasingly rely on learning algorithms , collectives may form and seek ways to influence these platforms to align with their own interests. This can be achieved by coordinated submission of altered data.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/Statistical-Collusion-by-Collectives-on-Learning-Platforms-deaeb81c-5365-4cec-9af2-e4d286dfd04a", "content": "As platforms increasingly rely on learning algorithms , collectives may form and seek ways to influence these platforms to align with their own interests. This can be achieved by coordinated submission of altered data."}
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data/sampled_jsons/AltUp_Baykal_2023_transformer_dimension_approximation_computational_cost.jsonl
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{"idx": 0, "title": "[2301.13310] Alternating Updates for Efficient Transformers Alternating Updates for Efficient Transformers - NIPS Alternating updates for efficient transformers - Google Research NeurIPS 2023 Presentation Alternating updates for efficient transformers - ichibanai.com Alternating Updates for Efficient Transformers - OpenReview [2301.13310] Alternating Updates for Efficient Transformers [2301.13310] Alternating Updates for Efficient Transformers [2301.13310] Alternating Updates for Efficient Transformers Alternating updates for efficient transformers – Google ...", "date": "", "ddg_snippet": "Jan 30, 2023 · It has been well established that increasing scale in deep transformer networks leads to improved quality and performance. However, this increase in scale often comes with prohibitive increases in compute cost and inference latency. We introduce Alternating Updates ( AltUp ), a simple-to-implement method to increase a model's capacity without the computational burden. AltUp enables the widening ... Authors Cenk Baykal , Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang Abstract It has been well established that increasing scale in deep transformer networks leads to improved quality and performance. However, this increase in scale often comes with prohibitive increases in compute cost and inference latency. We introduce Alternating Updates ( AltUp ), a simple-to ... Nov 7, 2023 · A natural question is whether we can reap the benefits of larger models without incurring the computational burden. In “ Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method to take advantage of increased token representation without increasing the computation cost . Can we get the benefits of increased representation dimension without the full computational cost ? Performance for a word2vec model with varying representation dimension (figure from Yang et al., 2022). In “ Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method to take advantage of increased token representation without increasing the computation cost . AltUp is easy to implement, widely applicable to any transformer architecture, and requires minimal hyperparameter tuning. Sep 21, 2023 · The paper proposes a novel technique named “ AltUp ” to expand Transformer ’s feature dimension while preserving the computation cost . The key idea of AltUp is to divide wide hidden features into multiple blocks, where only one block is processed by Transformer sub-layers, while the other blocks are computed through a linear combination of ... What is alternating updates (altup)? We introduce Alternating Updates (AltUp), a simple-to-implement method to increase a model's capacity without the computational burden . AltUp enables the widening of the learned representation, i.e., the token embedding, while only incurring a negligible increase in latency. How does scale affect the performance of a deep transformer network? It has been well established that increasing scale in deep transformer networks leads to improved quality and performance . However, this increase in scale often comes with prohibitive increases in compute cost and inference latency. How does altup work? AltUp enables the widening of the learned representation, i.e., the token embedding, while only incurring a negligible increase in latency. AltUp achieves this by working on a subblock of the widened representation at each layer and using a predict-and-correct mechanism to update the inactivated blocks. Nov 7, 2023 · In our research paper, “Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method that allows us to take advantage of increased token representation without increasing computation cost .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2301.13310", "content": "Jan 30, 2023 · It has been well established that increasing scale in deep transformer networks leads to improved quality and performance. However, this increase in scale often comes with prohibitive increases in compute cost and inference latency. We introduce Alternating Updates ( AltUp ), a simple-to-implement method to increase a model's capacity without the computational burden. AltUp enables the widening ... Authors Cenk Baykal , Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang Abstract It has been well established that increasing scale in deep transformer networks leads to improved quality and performance. However, this increase in scale often comes with prohibitive increases in compute cost and inference latency. We introduce Alternating Updates ( AltUp ), a simple-to ... Nov 7, 2023 · A natural question is whether we can reap the benefits of larger models without incurring the computational burden. In “ Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method to take advantage of increased token representation without increasing the computation cost . Can we get the benefits of increased representation dimension without the full computational cost ? Performance for a word2vec model with varying representation dimension (figure from Yang et al., 2022). In “ Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method to take advantage of increased token representation without increasing the computation cost . AltUp is easy to implement, widely applicable to any transformer architecture, and requires minimal hyperparameter tuning. Sep 21, 2023 · The paper proposes a novel technique named “ AltUp ” to expand Transformer ’s feature dimension while preserving the computation cost . The key idea of AltUp is to divide wide hidden features into multiple blocks, where only one block is processed by Transformer sub-layers, while the other blocks are computed through a linear combination of ... What is alternating updates (altup)? We introduce Alternating Updates (AltUp), a simple-to-implement method to increase a model's capacity without the computational burden . AltUp enables the widening of the learned representation, i.e., the token embedding, while only incurring a negligible increase in latency. How does scale affect the performance of a deep transformer network? It has been well established that increasing scale in deep transformer networks leads to improved quality and performance . However, this increase in scale often comes with prohibitive increases in compute cost and inference latency. How does altup work? AltUp enables the widening of the learned representation, i.e., the token embedding, while only incurring a negligible increase in latency. AltUp achieves this by working on a subblock of the widened representation at each layer and using a predict-and-correct mechanism to update the inactivated blocks. Nov 7, 2023 · In our research paper, “Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method that allows us to take advantage of increased token representation without increasing computation cost ."}
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{"idx": 1, "title": "Alternating Updates for Efficient Transformers - NIPS", "date": "", "ddg_snippet": "Authors Cenk Baykal , Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang Abstract It has been well established that increasing scale in deep transformer networks leads to improved quality and performance. However, this increase in scale often comes with prohibitive increases in compute cost and inference latency. We introduce Alternating Updates ( AltUp ), a simple-to ...", "subpage_snippet": "", "source": "papers.nips.cc", "link": "https://papers.nips.cc/paper_files/paper/2023/hash/f2059277ac6ce66e7e5543001afa8bb5-Abstract-Conference.html", "content": "Authors Cenk Baykal , Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang Abstract It has been well established that increasing scale in deep transformer networks leads to improved quality and performance. However, this increase in scale often comes with prohibitive increases in compute cost and inference latency. We introduce Alternating Updates ( AltUp ), a simple-to ..."}
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{"idx": 2, "title": "Alternating updates for efficient transformers - Google Research", "date": "", "ddg_snippet": "Nov 7, 2023 · A natural question is whether we can reap the benefits of larger models without incurring the computational burden. In “ Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method to take advantage of increased token representation without increasing the computation cost .", "subpage_snippet": "", "source": "research.google", "link": "https://research.google/blog/alternating-updates-for-efficient-transformers/", "content": "Nov 7, 2023 · A natural question is whether we can reap the benefits of larger models without incurring the computational burden. In “ Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method to take advantage of increased token representation without increasing the computation cost ."}
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{"idx": 3, "title": "NeurIPS 2023 Presentation", "date": "", "ddg_snippet": "Can we get the benefits of increased representation dimension without the full computational cost ? Performance for a word2vec model with varying representation dimension (figure from Yang et al., 2022).", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/media/neurips-2023/Slides/72994.pdf", "content": "Can we get the benefits of increased representation dimension without the full computational cost ? Performance for a word2vec model with varying representation dimension (figure from Yang et al., 2022)."}
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{"idx": 4, "title": "Alternating updates for efficient transformers - ichibanai.com", "date": "", "ddg_snippet": "In “ Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method to take advantage of increased token representation without increasing the computation cost . AltUp is easy to implement, widely applicable to any transformer architecture, and requires minimal hyperparameter tuning.", "subpage_snippet": "", "source": "ichibanai.com", "link": "https://ichibanai.com/alternating-updates-for-efficient-transformers/", "content": "In “ Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method to take advantage of increased token representation without increasing the computation cost . AltUp is easy to implement, widely applicable to any transformer architecture, and requires minimal hyperparameter tuning."}
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{"idx": 5, "title": "Alternating Updates for Efficient Transformers - OpenReview", "date": "", "ddg_snippet": "Sep 21, 2023 · The paper proposes a novel technique named “ AltUp ” to expand Transformer ’s feature dimension while preserving the computation cost . The key idea of AltUp is to divide wide hidden features into multiple blocks, where only one block is processed by Transformer sub-layers, while the other blocks are computed through a linear combination of ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=1p6teT6F73", "content": "Sep 21, 2023 · The paper proposes a novel technique named “ AltUp ” to expand Transformer ’s feature dimension while preserving the computation cost . The key idea of AltUp is to divide wide hidden features into multiple blocks, where only one block is processed by Transformer sub-layers, while the other blocks are computed through a linear combination of ..."}
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| 7 |
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{"idx": 6, "title": "Alternating updates for efficient transformers – Google ...", "date": "", "ddg_snippet": "Nov 7, 2023 · In our research paper, “Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method that allows us to take advantage of increased token representation without increasing computation cost .", "subpage_snippet": "", "source": "news.pourover.ai", "link": "https://news.pourover.ai/alternating-updates-for-efficient-transformers-google-research-blog/", "content": "Nov 7, 2023 · In our research paper, “Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp , a method that allows us to take advantage of increased token representation without increasing computation cost ."}
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{"idx": 7, "title": "Alternating updates for efficient transformers - googblogs.com", "date": "", "ddg_snippet": "A natural question is whether we can reap the benefits of larger models without incurring the computational burden. In “Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp ...", "subpage_snippet": "", "source": "www.googblogs.com", "link": "https://www.googblogs.com/alternating-updates-for-efficient-transformers/", "content": "A natural question is whether we can reap the benefits of larger models without incurring the computational burden. In “Alternating Updates for Efficient Transformers ”, accepted as a Spotlight at NeurIPS 2023 , we introduce AltUp ..."}
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{"idx": 8, "title": "Google AI Introduces AltUp (Alternating Updates): An... - MarkTechPost", "date": "", "ddg_snippet": "By maintaining the model dimension and sidestepping the quadratic increase in computation associated with straightforward expansion, AltUp emerges as a promising solution to the computational challenges posed by larger Transformer networks.", "subpage_snippet": "", "source": "www.marktechpost.com", "link": "https://www.marktechpost.com/2023/11/12/google-ai-introduces-altup-alternating-updates-an-artificial-intelligence-method-that-takes-advantage-of-increasing-scale-in-transformer-networks-without-increasing-the-computation-cost/", "content": "By maintaining the model dimension and sidestepping the quadratic increase in computation associated with straightforward expansion, AltUp emerges as a promising solution to the computational challenges posed by larger Transformer networks."}
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{"idx": 9, "title": "Google AI's AltUp : Advancing Transformer Networks without...", "date": "", "ddg_snippet": "AltUp leverages alternating updates to enhance the performance of Transformer Networks without incurring additional computational expenses. This breakthrough paves the way for more efficient and cost -effective AI systems.", "subpage_snippet": "", "source": "fataldeaths.com", "link": "https://fataldeaths.com/NewsSite/2023/11/13/AI/articles/google-ais-altup-advancing-transformer-networks-without-increased-costs.html", "content": "AltUp leverages alternating updates to enhance the performance of Transformer Networks without incurring additional computational expenses. This breakthrough paves the way for more efficient and cost -effective AI systems."}
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data/sampled_jsons/Alternating_updates_for_efficient_transformers_Baykal_et_al.,_2023.jsonl
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{"idx": 0, "title": "Alternating updates for efficient transformers", "date": "", "ddg_snippet": "November 7, 2023 .In contrast, Alternating Updates keeps the layer width constant and efficiently computes the output by operating on a sub-block of the representation at each layer.", "subpage_snippet": "", "source": "research.google", "link": "https://research.google/blog/alternating-updates-for-efficient-transformers/", "content": "November 7, 2023 .In contrast, Alternating Updates keeps the layer width constant and efficiently computes the output by operating on a sub-block of the representation at each layer."}
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{"idx": 1, "title": "Alternating Updates for Efficient Transformers | DeepAI", "date": "", "ddg_snippet": "research. ∙ 05/03/ 2023 . Towards Being Parameter- Efficient : A Stratified Sparsely Activated Transformer with Dynamic Capacity. Mixture-of-experts (MoE) models that employ sparse activation have demon... 0 Haoran Xu, et al . ∙.", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/publication/alternating-updates-for-efficient-transformers", "content": "research. ∙ 05/03/ 2023 . Towards Being Parameter- Efficient : A Stratified Sparsely Activated Transformer with Dynamic Capacity. Mixture-of-experts (MoE) models that employ sparse activation have demon... 0 Haoran Xu, et al . ∙."}
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{"idx": 2, "title": "[2301.13310] Alternating Updates for Efficient Transformers", "date": "", "ddg_snippet": "Abstract page for arXiv paper 2301.13310: Alternating Updates for Efficient Transformers .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2301.13310", "content": "Abstract page for arXiv paper 2301.13310: Alternating Updates for Efficient Transformers ."}
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{"idx": 3, "title": "Alternating Updates for Efficient Transformers", "date": "", "ddg_snippet": "Cenk Baykal , Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang.We introduce Alternating Updates (AltUp), a simple-to-implement method to increase a model's capacity without the computational burden.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/hash/f2059277ac6ce66e7e5543001afa8bb5-Abstract-Conference.html", "content": "Cenk Baykal , Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang.We introduce Alternating Updates (AltUp), a simple-to-implement method to increase a model's capacity without the computational burden."}
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{"idx": 4, "title": "Cenk Baykal - Google Scholar", "date": "", "ddg_snippet": "Alternating updates for efficient transformers . C Baykal , D Cutler, N Dikkala, N Ghosh, R Panigrahy, X Wang. Advances in Neural Information Processing Systems 36, 76718-76736, 2023 .", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=lRxoOlwAAAAJ&hl=en", "content": "Alternating updates for efficient transformers . C Baykal , D Cutler, N Dikkala, N Ghosh, R Panigrahy, X Wang. Advances in Neural Information Processing Systems 36, 76718-76736, 2023 ."}
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{"idx": 5, "title": "Alternating Updates for Efficient Transformers", "date": "", "ddg_snippet": "Our experiments on various transformer models and language tasks demonstrate the consistent effectiveness of alternating updates on a diverse set of benchmarks.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/Alternating-Updates-for-Efficient-Transformers-f814b5ae-ce27-453f-a1c3-41ee060de9f3", "content": "Our experiments on various transformer models and language tasks demonstrate the consistent effectiveness of alternating updates on a diverse set of benchmarks."}
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{"idx": 6, "title": "Cenk Baykal · CSAuthors", "date": "", "ddg_snippet": "Alternating Updates for Efficient Transformers . Cenk Baykal .", "subpage_snippet": "", "source": "www.csauthors.net", "link": "https://www.csauthors.net/cenk-baykal/", "content": "Alternating Updates for Efficient Transformers . Cenk Baykal ."}
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{"idx": 7, "title": "Alternating Updates for Efficient Transformers | alphaXiv", "date": "", "ddg_snippet": "Our experiments on benchmark transformer models and language tasks demonstrate the consistent effectiveness of AltUp on a diverse set of scenarios. Notably, on SuperGLUE and SQuAD benchmarks, AltUp enables up to $87\\%$ speedup relative to the dense baselines at the same accuracy.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/zh/overview/2301.13310v2", "content": "Our experiments on benchmark transformer models and language tasks demonstrate the consistent effectiveness of AltUp on a diverse set of scenarios. Notably, on SuperGLUE and SQuAD benchmarks, AltUp enables up to $87\\%$ speedup relative to the dense baselines at the same accuracy."}
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{"idx": 8, "title": "ml-papers/papers/ 2023 /230130 Alternating Updates for Efficient ...", "date": "", "ddg_snippet": "My collection of machine learning papers. Contribute to rosinality/ml-papers development by creating an account on GitHub.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/rosinality/ml-papers/blob/main/papers/2023/230130+Alternating+Updates+for+Efficient+Transformers.md", "content": "My collection of machine learning papers. Contribute to rosinality/ml-papers development by creating an account on GitHub."}
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{"idx": 9, "title": "Nishanth Dikkala - Google Akademik", "date": "", "ddg_snippet": "2024. Alternating updates for efficient transformers . C Baykal , D Cutler, N Dikkala, N Ghosh, R Panigrahy, X Wang.", "subpage_snippet": "", "source": "scholar.google.dk", "link": "https://scholar.google.dk/citations?user=ViBqWZYAAAAJ&hl=tr", "content": "2024. Alternating updates for efficient transformers . C Baykal , D Cutler, N Dikkala, N Ghosh, R Panigrahy, X Wang."}
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{"idx": 0, "title": "AN ANALYSIS FOR REASONING BIAS OF LANGUAGE MODELS WITH SMALL ...", "date": "", "ddg_snippet": "Feb 10, 2025 · In this work, we identify a reasoning bias during the training of neural networks that learn natural language when initialized with small parameter scales.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.04375v1", "content": "Feb 10, 2025 · In this work, we identify a reasoning bias during the training of neural networks that learn natural language when initialized with small parameter scales."}
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{"idx": 1, "title": "An Analysis for Reasoning Bias of Language Models with Small ...", "date": "", "ddg_snippet": "In this work, we identify a reasoning bias during the train-ing of neural networks that learn natural language when initialized with small parameter scales.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.04375", "content": "In this work, we identify a reasoning bias during the train-ing of neural networks that learn natural language when initialized with small parameter scales."}
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{"idx": 2, "title": "An analysis for reasoning bias of language models with small ...", "date": "", "ddg_snippet": "Transformer-based Large Language Models (LLMs) have revolutionized Natural Language Processing by demonstrating exceptional performance across diverse tasks. This study investigates the impact of the parameter initialization scale on the training behavior and task...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.04375v1", "content": "Transformer-based Large Language Models (LLMs) have revolutionized Natural Language Processing by demonstrating exceptional performance across diverse tasks. This study investigates the impact of the parameter initialization scale on the training behavior and task..."}
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{"idx": 3, "title": "(PDF) An Analysis for Reasoning Bias of Language Models with ...", "date": "", "ddg_snippet": "We validate this reasoning bias via real datasets and meticulously designed anchor functions.This work enhances our understanding of how initialization strategies influence LLM performance on reasoning tasks and offers valuable guidelines for training models .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/388848015_An_Analysis_for_Reasoning_Bias_of_Language_Models_with_Small_Initialization", "content": "We validate this reasoning bias via real datasets and meticulously designed anchor functions.This work enhances our understanding of how initialization strategies influence LLM performance on reasoning tasks and offers valuable guidelines for training models ."}
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{"idx": 4, "title": "an analysis for reasoning bias of language models", "date": "", "ddg_snippet": "by J Yao · 2025 · Cited by 2 — In this work, we identify a reasoning bias during the training of neural networks that learn natural language when initialized with small ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.04375?", "content": "by J Yao · 2025 · Cited by 2 — In this work, we identify a reasoning bias during the training of neural networks that learn natural language when initialized with small ..."}
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{"idx": 5, "title": "ToolRM: Outcome Reward Models for Tool-Calling Large ...", "date": "", "ddg_snippet": "5 days ago — We summarize the key insights below: • Small Language Models (SLMs) benefit the most: Best-of-n sampling with Qwen3-0.6B and. ToolRM-14B as the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2509.11963", "content": "5 days ago — We summarize the key insights below: • Small Language Models (SLMs) benefit the most: Best-of-n sampling with Qwen3-0.6B and. ToolRM-14B as the ..."}
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{"idx": 6, "title": "Can Language Models Perform Robust Reasoning in ...", "date": "", "ddg_snippet": "by Z Zhou · Cited by 20 — Abstract. This paper investigates an under-explored challenge in large language models . (LLMs): chain-of-thought prompting with noisy rationales, ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=FbuODM02ra", "content": "by Z Zhou · Cited by 20 — Abstract. This paper investigates an under-explored challenge in large language models . (LLMs): chain-of-thought prompting with noisy rationales, ..."}
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{"idx": 7, "title": "Towards Better Causal Reasoning in Language Models", "date": "", "ddg_snippet": "by L Yu · 2025 · Cited by 4 — Through systematic analysis of model outputs, we identify four common types of errors in causal reasoning . Logical errors occur when the model ...", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.naacl-long.622.pdf", "content": "by L Yu · 2025 · Cited by 4 — Through systematic analysis of model outputs, we identify four common types of errors in causal reasoning . Logical errors occur when the model ..."}
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{"idx": 8, "title": "A Large Language Model Fine-Tuning Framework for Causal ...", "date": "", "ddg_snippet": "Figure 2 BRQA Q&A Data. The step-by-step functions of BRQA for Q&A data are listed in Table 1. Table 1 Step by step function. Step by step function. Step01 ...", "subpage_snippet": "", "source": "papers.ssrn.com", "link": "https://papers.ssrn.com/sol3/Delivery.cfm/f3d4b069-6a1c-4ba6-b8c4-49cc2ceb19a5-MECA.pdf?abstractid=5394371&mirid=1", "content": "Figure 2 BRQA Q&A Data. The step-by-step functions of BRQA for Q&A data are listed in Table 1. Table 1 Step by step function. Step by step function. Step01 ..."}
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{"idx": 9, "title": "A Practical Guidance for Building and Evaluating Chinese ...", "date": "", "ddg_snippet": "by X Wen · 2025 — We propose CheemsBench, the first large- scale and comprehensive benchmark designed specifically for Chinese reward models . • We construct ...", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.acl-long.737.pdf", "content": "by X Wen · 2025 — We propose CheemsBench, the first large- scale and comprehensive benchmark designed specifically for Chinese reward models . • We construct ..."}
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data/sampled_jsons/Anvith_Thudi_2024_per-instance_privacy.jsonl
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{"idx": 0, "title": "Leveraging Per - Instance Privacy for Machine Unlearning | OpenReview", "date": "", "ddg_snippet": "We present a principled, per - instance approach to quantifying the difficulty of unlearning via fine-tuning. We begin by sharpening an analysis of noisy gradient descent for unlearning (Chien et al., 2024 ), obtaining a better utility–unlearning trade-off by replacing...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=0A4Y9qRnu9&referrer=[the+profile+of+Nazanin+Mohammadi+Sepahvand](/profile?id=~Nazanin_Mohammadi_Sepahvand1)", "content": "We present a principled, per - instance approach to quantifying the difficulty of unlearning via fine-tuning. We begin by sharpening an analysis of noisy gradient descent for unlearning (Chien et al., 2024 ), obtaining a better utility–unlearning trade-off by replacing..."}
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{"idx": 1, "title": "Leveraging Per - Instance Privacy for Machine Unlearning", "date": "", "ddg_snippet": "( 2024 ) and a per - instance Re´nyi-differential privacy analysis by Thudi et al. An - vith Thudi is also supported by a Vanier Fellowship from NSERC. Daniel M. Roy is supported by the funding through.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.18786", "content": "( 2024 ) and a per - instance Re´nyi-differential privacy analysis by Thudi et al. An - vith Thudi is also supported by a Vanier Fellowship from NSERC. Daniel M. Roy is supported by the funding through."}
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{"idx": 2, "title": "CleverHans Lab - Anvith", "date": "", "ddg_snippet": "@article{ anvith 2024 fromjournal, author = { Thudi , Anvith and Shumailov, Ilia and Boenisch, Franziska and Papernot, Nicolas}, title = {From Differential Privacy to Bounds on Membership Inference: Less can be More}, year = { 2024 } }.", "subpage_snippet": "", "source": "cleverhans.io", "link": "https://cleverhans.io/members/anvith.html", "content": "@article{ anvith 2024 fromjournal, author = { Thudi , Anvith and Shumailov, Ilia and Boenisch, Franziska and Papernot, Nicolas}, title = {From Differential Privacy to Bounds on Membership Inference: Less can be More}, year = { 2024 } }."}
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{"idx": 3, "title": "Anvith Thudi", "date": "", "ddg_snippet": "anvith .com anvith . thudi @mail.utoronto.ca.“Training Private Models That Know What They Don’t Know”: Stephan Rabanser, Anvith Thudi , Abhradeep Thakurta, Krishnamurthy Dvijotham, Nicolas Papernot. Proceedings of the 37th Conference on Neural Information Processing Systems.", "subpage_snippet": "", "source": "www.anvith.com", "link": "https://www.anvith.com/Anvith_Thudi_CV_May_22_2025.pdf", "content": "anvith .com anvith . thudi @mail.utoronto.ca.“Training Private Models That Know What They Don’t Know”: Stephan Rabanser, Anvith Thudi , Abhradeep Thakurta, Krishnamurthy Dvijotham, Nicolas Papernot. Proceedings of the 37th Conference on Neural Information Processing Systems."}
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{"idx": 4, "title": "Nicolas PAPERNOT | Professor (Assistant) | Doctor of Philosophy", "date": "", "ddg_snippet": "Anvith Thudi Anvith Thudi .We present a principled, per - instance approach to quantifying the difficulty of unlearning via fine-tuning.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/profile/Nicolas-Papernot", "content": "Anvith Thudi Anvith Thudi .We present a principled, per - instance approach to quantifying the difficulty of unlearning via fine-tuning."}
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{"idx": 5, "title": "Leveraging Per -Example Privacy for Machine Unlearning", "date": "", "ddg_snippet": "Anvith Thudi . Berivan Isik.Our results show that per - instance privacy levels computed from training dynamics reliably predict unlearning difficulty, offering a principled and practical way to assess unlearning performance.", "subpage_snippet": "", "source": "research.google", "link": "https://research.google/pubs/leveraging-per-example-privacy-for-machine-unlearning/", "content": "Anvith Thudi . Berivan Isik.Our results show that per - instance privacy levels computed from training dynamics reliably predict unlearning difficulty, offering a principled and practical way to assess unlearning performance."}
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| 7 |
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{"idx": 6, "title": "Anvith Thudi - Google Scholar", "date": "", "ddg_snippet": "Anvith Thudi . CS PhD, UofT.Leveraging Per - Instance Privacy for Machine Unlearning.", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=bTEybH0AAAAJ&hl=en", "content": "Anvith Thudi . CS PhD, UofT.Leveraging Per - Instance Privacy for Machine Unlearning."}
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| 8 |
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{"idx": 7, "title": "Nicolas Papernot", "date": "", "ddg_snippet": "[C7] Leveraging Per - Instance Privacy for Machine Unlearning. Nazanin Mohammadi Sepahvand, Anvith Thudi , Berivan Isik, Ashmita Bhattacharyya, Nicolas Papernot, Eleni Triantafillou, Daniel M. Roy, Gintare Karolina Dziugaite.", "subpage_snippet": "", "source": "www.papernot.fr", "link": "https://www.papernot.fr/papernot_cv.pdf", "content": "[C7] Leveraging Per - Instance Privacy for Machine Unlearning. Nazanin Mohammadi Sepahvand, Anvith Thudi , Berivan Isik, Ashmita Bhattacharyya, Nicolas Papernot, Eleni Triantafillou, Daniel M. Roy, Gintare Karolina Dziugaite."}
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{"idx": 8, "title": "GitHub - Anvith - Thudi /MixMax: The repository for https...", "date": "", "ddg_snippet": "Codespaces. Instant dev environments. Issues. Anvith - Thudi / MixMax Public. Notifications You must be signed in to change notification settings.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Anvith-Thudi/MixMax", "content": "Codespaces. Instant dev environments. Issues. Anvith - Thudi / MixMax Public. Notifications You must be signed in to change notification settings."}
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{"idx": 9, "title": "https://infosecurity.us - USENIX Security '22 - Anvith Thudi , Hengrui...", "date": "", "ddg_snippet": "April 07, 2023 by Marc Handelman in USENIX, USENIX Security, Security Conferences, Regulatory Education, Cybersecurity Education, Security Education, Infosec Education, Education, Privacy , Hardware Security, USENIX NSDI '24.", "subpage_snippet": "", "source": "www.infosecurity.us", "link": "https://www.infosecurity.us/blog/2023/4/7/usenix-security-22-anvith-thudi-hengrui-jia-ilia-shumailov-nicolas-papernot-on-the-necessity-of-auditable-algorithmic-definitions-for-machine-unlearning", "content": "April 07, 2023 by Marc Handelman in USENIX, USENIX Security, Security Conferences, Regulatory Education, Cybersecurity Education, Security Education, Infosec Education, Education, Privacy , Hardware Security, USENIX NSDI '24."}
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data/sampled_jsons/Archetypal_SAE_RA-SAE_TopK_SAE_stability_score_DINOv2_table_1.jsonl
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{"idx": 0, "title": "Archetypal SAEs: Adaptive and Stable Dictionary Learning for ...", "date": "", "ddg_snippet": "Mar 20, 2025 · Figure 1 . A) Compared to a Regular- SAE , Archetypal -SAEs constrain dictionary atoms (decoder directions) to the data’s convex hull, improving stability . A relaxed variant ( RA-SAE ) allows mild relaxation, matching standard SAEs in reconstruction while maintaining stability . Both integrate with any SAE variant (e.g., TopK , JumpReLU).", "subpage_snippet": "", "source": "kempnerinstitute.harvard.edu", "link": "https://kempnerinstitute.harvard.edu/research/deeper-learning/archetypal-saes-adaptive-and-stable-dictionary-learning-for-concept-extraction-in-large-vision-models/", "content": "Mar 20, 2025 · Figure 1 . A) Compared to a Regular- SAE , Archetypal -SAEs constrain dictionary atoms (decoder directions) to the data’s convex hull, improving stability . A relaxed variant ( RA-SAE ) allows mild relaxation, matching standard SAEs in reconstruction while maintaining stability . Both integrate with any SAE variant (e.g., TopK , JumpReLU)."}
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{"idx": 1, "title": "Archetypal SAE: Adaptive and Stable Dictionary Learning for ...", "date": "", "ddg_snippet": "Figure 1 : A) Archetypal - SAE . Archetypal -SAEs constrain dictionary atoms (decoder directions) to the data’s convex hull, improving stability . A relaxed variant ( RA-SAE ) allows mild relaxation, matching standard SAEs in reconstruction while maintaining stability . Both integrate with any SAE variant (e.g., TopK , JumpReLU). B) Instability Problem. Standard SAEs produce inconsistent dictionaries ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.12892v2", "content": "Figure 1 : A) Archetypal - SAE . Archetypal -SAEs constrain dictionary atoms (decoder directions) to the data’s convex hull, improving stability . A relaxed variant ( RA-SAE ) allows mild relaxation, matching standard SAEs in reconstruction while maintaining stability . Both integrate with any SAE variant (e.g., TopK , JumpReLU). B) Instability Problem. Standard SAEs produce inconsistent dictionaries ..."}
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{"idx": 2, "title": "Archetypal - Overcomplete", "date": "", "ddg_snippet": "RelaxedArchetypalDictionary Dictionary used for Relaxed Archetypal SAE ( RA-SAE ). __init__(self, in_dimensions, nb_concepts, points, delta= 1 .0, use_multiplier=True, device='cpu') Parameters in_dimensions : int Dimensionality of the input data (e.g number of channels). nb_concepts : int Number of components/concepts in the dictionary. The dictionary is overcomplete if the number of concepts > in ...", "subpage_snippet": "", "source": "kempnerinstitute.github.io", "link": "https://kempnerinstitute.github.io/overcomplete/saes/archetypal/", "content": "RelaxedArchetypalDictionary Dictionary used for Relaxed Archetypal SAE ( RA-SAE ). __init__(self, in_dimensions, nb_concepts, points, delta= 1 .0, use_multiplier=True, device='cpu') Parameters in_dimensions : int Dimensionality of the input data (e.g number of channels). nb_concepts : int Number of components/concepts in the dictionary. The dictionary is overcomplete if the number of concepts > in ..."}
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{"idx": 3, "title": "Archetypal SAE: Variable and stable methods to learn the ...", "date": "", "ddg_snippet": "Mar 17, 2025 · RA-SAE Expands the frame and includes a minimum rest time, allowing a slight deviation from the convex hull to improve model fluctuations while storing firmness. The investigators examine their method using five detecters: Dinov2 , SIGLIP, VIT, Conving, and Revnet50, all received from Timm brillion.", "subpage_snippet": "", "source": "dataforcee.us", "link": "https://dataforcee.us/2025/03/17/archetypal-sae-variable-and-stable-methods-to-learn-the-temple-dictionary-in-the-largest-visual-models/", "content": "Mar 17, 2025 · RA-SAE Expands the frame and includes a minimum rest time, allowing a slight deviation from the convex hull to improve model fluctuations while storing firmness. The investigators examine their method using five detecters: Dinov2 , SIGLIP, VIT, Conving, and Revnet50, all received from Timm brillion."}
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{"idx": 4, "title": "Archetypal SAEs: Adaptive and Stable Dictionary ... - Medium", "date": "", "ddg_snippet": "A) Compared to a Regular- SAE , Archetypal -SAEs constrain dictionary atoms (decoder directions) to the data’s convex hull, improving stability . A relaxed variant ( RA-SAE ) allows mild relaxation ...", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@kempnerinstitute/archetypal-saes-adaptive-and-stable-dictionary-learning-for-concept-extraction-in-large-vision-acf95010c691", "content": "A) Compared to a Regular- SAE , Archetypal -SAEs constrain dictionary atoms (decoder directions) to the data’s convex hull, improving stability . A relaxed variant ( RA-SAE ) allows mild relaxation ..."}
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+
{"idx": 5, "title": "GitHub - gorobarak/sae: Experiments with different SAE ...", "date": "", "ddg_snippet": "Experiments with different SAE architectures. Contribute to gorobarak/ sae development by creating an account on GitHub.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/gorobarak/sae", "content": "Experiments with different SAE architectures. Contribute to gorobarak/ sae development by creating an account on GitHub."}
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{"idx": 6, "title": "[2502.12892] Archetypal SAE: Adaptive and Stable Dictionary ...", "date": "", "ddg_snippet": "Feb 18, 2025 · This geometric anchoring significantly enhances the stability of inferred dictionaries, and their mildly relaxed variants RA -SAEs further match state-of-the-art reconstruction abilities.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.12892", "content": "Feb 18, 2025 · This geometric anchoring significantly enhances the stability of inferred dictionaries, and their mildly relaxed variants RA -SAEs further match state-of-the-art reconstruction abilities."}
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{"idx": 7, "title": "(PDF) Archetypal SAE : Adaptive and Stable Dictionary Learning for...", "date": "", "ddg_snippet": "SAE TopK SAE Jump SAE SNMF CNMF RA - SAE . Table 1 . Quantitative comparison of the dictionary learning methods on DINOv 2 , using a 90% sparse, overcomplete dictionary.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/389129606_Archetypal_SAE_Adaptive_and_Stable_Dictionary_Learning_for_Concept_Extraction_in_Large_Vision_Models", "content": "SAE TopK SAE Jump SAE SNMF CNMF RA - SAE . Table 1 . Quantitative comparison of the dictionary learning methods on DINOv 2 , using a 90% sparse, overcomplete dictionary."}
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{"idx": 8, "title": "matybohacek/ RA - SAE - DINOv 2 -32k · Hugging Face", "date": "", "ddg_snippet": "RA - SAE - DINOv 2 -32k is an archetypal SAE , which decomposes DINOv 2 featues into interpretable concept activations, allowing you to extract human-understandable visual concepts from any image as sparse feature vectors. With 32,000 concepts, it is the largest such model to date.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/matybohacek/RA-SAE-DINOv2-32k", "content": "RA - SAE - DINOv 2 -32k is an archetypal SAE , which decomposes DINOv 2 featues into interpretable concept activations, allowing you to extract human-understandable visual concepts from any image as sparse feature vectors. With 32,000 concepts, it is the largest such model to date."}
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{"idx": 9, "title": "Archetypal SAE : Adaptive and Secure Dictionary... - I Tech Epic", "date": "", "ddg_snippet": "Furthermore, RA - SAE builds upon a TopK SAE structure to keep up constant sparsity ranges throughout experiments.", "subpage_snippet": "", "source": "itechepic.com", "link": "https://itechepic.com/archetypal-sae-adaptive-and-secure-dictionary-studying-for-idea-extraction-in-massive-imaginative-and-prescient-fashions/", "content": "Furthermore, RA - SAE builds upon a TopK SAE structure to keep up constant sparsity ranges throughout experiments."}
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data/sampled_jsons/Archetypal_analysis_Cutler_Breiman_1994_journal.jsonl
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{"idx": 0, "title": "Archetypal Analysis on JSTOR", "date": "", "ddg_snippet": "journal article. Archetypal Analysis . Adele Cutler and Leo Breiman . Archetypal analysis represents each individual in a data set as a mixture of individuals of pure type or archetypes . The archetypes themselves are restricted to being mixtures of the individuals in the data set.", "subpage_snippet": "", "source": "www.jstor.org", "link": "https://www.jstor.org/stable/1269949", "content": "journal article. Archetypal Analysis . Adele Cutler and Leo Breiman . Archetypal analysis represents each individual in a data set as a mixture of individuals of pure type or archetypes . The archetypes themselves are restricted to being mixtures of the individuals in the data set."}
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{"idx": 1, "title": "Archetypal Analysis : Technometrics: Vol 36, No 4", "date": "", "ddg_snippet": "Archetypal Analysis . Adele Cutler Department of Mathematics and Statistics, Utah State University, Logan, UT, 84322-3900. & Leo Breiman Department of Statistics, University of California, Berkeley, CA, 94720.", "subpage_snippet": "", "source": "www.tandfonline.com", "link": "https://www.tandfonline.com/doi/abs/10.1080/00401706.1994.10485840", "content": "Archetypal Analysis . Adele Cutler Department of Mathematics and Statistics, Utah State University, Logan, UT, 84322-3900. & Leo Breiman Department of Statistics, University of California, Berkeley, CA, 94720."}
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{"idx": 2, "title": "Archetypal analysis for machine learning and data mining", "date": "", "ddg_snippet": "Archetypal analysis (aa) proposed by Cutler and Breiman ( 1994 ) [7] estimates the principal convex hull (pch) of a data set.", "subpage_snippet": "", "source": "orbit.dtu.dk", "link": "https://orbit.dtu.dk/en/publications/archetypal-analysis-for-machine-learning-and-data-mining", "content": "Archetypal analysis (aa) proposed by Cutler and Breiman ( 1994 ) [7] estimates the principal convex hull (pch) of a data set."}
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{"idx": 3, "title": "Archetypal Analysis ++: Rethinking the Initialization Strategy", "date": "", "ddg_snippet": "Archetypal analysis (AA) ( Cutler & Breiman , 1994 ) is a matrix factorization method with convexity constraints.Furthermore, Cutler & Breiman ( 1994 ) state that a careful initialization improves the convergence speed and that archetypes should not be initialized too close to each other.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2301.13748v4", "content": "Archetypal analysis (AA) ( Cutler & Breiman , 1994 ) is a matrix factorization method with convexity constraints.Furthermore, Cutler & Breiman ( 1994 ) state that a careful initialization improves the convergence speed and that archetypes should not be initialized too close to each other."}
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{"idx": 4, "title": "From Spider-Man to Hero – Archetypal Analysis in R", "date": "", "ddg_snippet": "In statistics archetypal analysis was rst introduced by Cutler and Breiman ( 1994 ). In their paper they laid out the theoretical foundations, dened the concrete problem as a nonlinear least squares problem and presented an alternating minimizing algorithm to solve it.", "subpage_snippet": "", "source": "cran.r-project.org", "link": "https://cran.r-project.org/web/packages/archetypes/vignettes/archetypes.pdf", "content": "In statistics archetypal analysis was rst introduced by Cutler and Breiman ( 1994 ). In their paper they laid out the theoretical foundations, dened the concrete problem as a nonlinear least squares problem and presented an alternating minimizing algorithm to solve it."}
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{"idx": 5, "title": "Non-negative Matrix Factorization via Archetypal Analysis | DeepAI", "date": "", "ddg_snippet": "The archetypal analysis method of ( Cutler , Breiman , 1994 ) is recovered as the limiting case in which the last term is given infinite weight. We introduce a `uniqueness condition' on the data which is necessary for exactly recovering the archetypes from noiseless data.", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/publication/non-negative-matrix-factorization-via-archetypal-analysis", "content": "The archetypal analysis method of ( Cutler , Breiman , 1994 ) is recovered as the limiting case in which the last term is given infinite weight. We introduce a `uniqueness condition' on the data which is necessary for exactly recovering the archetypes from noiseless data."}
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| 7 |
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{"idx": 6, "title": "(PDF) Archetypal Analysis ++: Rethinking the Initialization Strategy", "date": "", "ddg_snippet": "Archetypal analysis (AA) ( Cutler and Breiman , 1994 ) is a matrix factorization method with convexity. constraints. The idea is to represent every data point as a convex combination of points, called.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/367652277_Archetypal_Analysis_Rethinking_the_Initialization_Strategy", "content": "Archetypal analysis (AA) ( Cutler and Breiman , 1994 ) is a matrix factorization method with convexity. constraints. The idea is to represent every data point as a convex combination of points, called."}
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{"idx": 7, "title": "ICML Poster Archetypal SAE: Adaptive and Stable Dictionary Learning...", "date": "", "ddg_snippet": "Create Profile. Journal To Conference Track.To address this issue, we draw inspiration from the Archetypal Analysis framework introduced by Cutler & Breiman ( 1994 ) and present Archetypal SAEs (A-SAE), wherein dictionary atoms are constrained to the data’s convex hull.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46195", "content": "Create Profile. Journal To Conference Track.To address this issue, we draw inspiration from the Archetypal Analysis framework introduced by Cutler & Breiman ( 1994 ) and present Archetypal SAEs (A-SAE), wherein dictionary atoms are constrained to the data’s convex hull."}
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{"idx": 8, "title": "Probabilistic archetypal analysis", "date": "", "ddg_snippet": "1 Introduction. Archetypal analysis (AA) represents observations as composition of pure patterns, i.e., archetypes , or equivalently convex combinations of extreme values ( Cutler and Breiman 1994 ).", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/s10994-015-5498-8.pdf", "content": "1 Introduction. Archetypal analysis (AA) represents observations as composition of pure patterns, i.e., archetypes , or equivalently convex combinations of extreme values ( Cutler and Breiman 1994 )."}
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{"idx": 9, "title": "Frame-based Data Factorizations", "date": "", "ddg_snippet": "The goal of Archetypal Analysis (AA) ( Cutler & Breiman , 1994 ) is to nd a factorization of the data. Journal of Mathematical Modelling and Algorithms, 4(2):219–234, 2005. Mørup, Morten and Hansen, Lars Kai. Archetypal analysis for machine learning.", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v70/mair17a/mair17a.pdf", "content": "The goal of Archetypal Analysis (AA) ( Cutler & Breiman , 1994 ) is to nd a factorization of the data. Journal of Mathematical Modelling and Algorithms, 4(2):219–234, 2005. Mørup, Morten and Hansen, Lars Kai. Archetypal analysis for machine learning."}
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{"idx": 0, "title": "ATP: Adaptive Tensor Parallelism for Foundation Models Adaptive Tensor Parallelism for Foundation Models - GitHub ATP: Adaptive Tensor Parallelism for Foundation Models Publications | Ziming Liu | MLSYS Researcher - GitHub Pages ATP: Adaptive Tensor Parallelism for Foundation Models Distributed Machine Learning | Proceedings of the 25th ... ATP : Adaptive Tensor Parallelism for Foundation Models ATP : Adaptive Tensor Parallelism for Foundation Models ATP : Adaptive Tensor Parallelism for Foundation Models ATP : Adaptive Tensor Parallelism for Foundation Models Shenggan Cheng - dblp", "date": "", "ddg_snippet": "Jan 20, 2023 · However, current tensor parallelism in machine learning frameworks misses optimization opportunities in fitting various interconnection topologies. In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. Adaptive Tensor Parallelism for Large Model Traning and Inference ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics. 1.Two-Level Search Space for Tensor Parallelism . 2. Adaptive Tensor Parallelism with Hierarchical Communication Matrix. 3.Chunk-based Communication-Computation Overlapping. 4.An estimator that helps study the performance of ATP on networks with different topologies. See full list on github.com To install ATP , you will need: •Python 3.8 or 3.9. •PyTorch 1.13 •SPMD from pytorch/tau See full list on github.com In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You ( 2023 ). ATP : Adaptive Tensor Parallelism for Foundation Models . Arxiv Preprint. ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections, is presented and the communication overhead of ATP decreases with scaling, indicating a qualitative leap forward. Jan 22, 2024 · Shenggan Cheng , Ziming Liu, Jiangsu Du, and Yang You. 2023 . ATP : Adaptive Tensor Parallelism for Foundation Models . arXiv preprint arXiv:2301.08658 ( 2023 ). Is ATP an adaptive tensor parallelism framework for foundation models? In this work, we present ATP, an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Can tensor parallelism be used in machine learning? However, current tensor parallelism in machine learning frameworks misses optimization opportunities in fitting various interconnection topologies. In this work, we present ATP, an adaptive tensor parallelism framework for foundation models, which can automatically select the optimal parallel strategy on different interconnections. How can ATP identify optimal tensor parallelism based on 2D device meshes? We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Combined with the hierarchical communication matrix , ATP can identify the optimal strategy in the search space. We also propose chunk-based overlapping to reduce communication overhead. Why is tensor parallelism important in Foundation model training? The increasing size of the models introduces great challenges for the training. Tensor parallelism is a critical technique that is currently used in almost all foundation model training and has a significant impact on overall training performance . [i5] Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You: ATP : Adaptive Tensor Parallelism for Foundation Models . CoRR abs/2301.08658 ( 2023 )", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2301.08658", "content": "Jan 20, 2023 · However, current tensor parallelism in machine learning frameworks misses optimization opportunities in fitting various interconnection topologies. In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. Adaptive Tensor Parallelism for Large Model Traning and Inference ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics. 1.Two-Level Search Space for Tensor Parallelism . 2. Adaptive Tensor Parallelism with Hierarchical Communication Matrix. 3.Chunk-based Communication-Computation Overlapping. 4.An estimator that helps study the performance of ATP on networks with different topologies. See full list on github.com To install ATP , you will need: •Python 3.8 or 3.9. •PyTorch 1.13 •SPMD from pytorch/tau See full list on github.com In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You ( 2023 ). ATP : Adaptive Tensor Parallelism for Foundation Models . Arxiv Preprint. ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections, is presented and the communication overhead of ATP decreases with scaling, indicating a qualitative leap forward. Jan 22, 2024 · Shenggan Cheng , Ziming Liu, Jiangsu Du, and Yang You. 2023 . ATP : Adaptive Tensor Parallelism for Foundation Models . arXiv preprint arXiv:2301.08658 ( 2023 ). Is ATP an adaptive tensor parallelism framework for foundation models? In this work, we present ATP, an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Can tensor parallelism be used in machine learning? However, current tensor parallelism in machine learning frameworks misses optimization opportunities in fitting various interconnection topologies. In this work, we present ATP, an adaptive tensor parallelism framework for foundation models, which can automatically select the optimal parallel strategy on different interconnections. How can ATP identify optimal tensor parallelism based on 2D device meshes? We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Combined with the hierarchical communication matrix , ATP can identify the optimal strategy in the search space. We also propose chunk-based overlapping to reduce communication overhead. Why is tensor parallelism important in Foundation model training? The increasing size of the models introduces great challenges for the training. Tensor parallelism is a critical technique that is currently used in almost all foundation model training and has a significant impact on overall training performance . [i5] Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You: ATP : Adaptive Tensor Parallelism for Foundation Models . CoRR abs/2301.08658 ( 2023 )"}
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{"idx": 1, "title": "Adaptive Tensor Parallelism for Foundation Models - GitHub ATP: Adaptive Tensor Parallelism for Foundation Models Publications | Ziming Liu | MLSYS Researcher - GitHub Pages ATP: Adaptive Tensor Parallelism for Foundation Models Distributed Machine Learning | Proceedings of the 25th ... ATP : Adaptive Tensor Parallelism for Foundation Models ATP : Adaptive Tensor Parallelism for Foundation Models ATP : Adaptive Tensor Parallelism for Foundation Models ATP : Adaptive Tensor Parallelism for Foundation Models Shenggan Cheng - dblp", "date": "", "ddg_snippet": "Adaptive Tensor Parallelism for Large Model Traning and Inference ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics. 1.Two-Level Search Space for Tensor Parallelism . 2. Adaptive Tensor Parallelism with Hierarchical Communication Matrix. 3.Chunk-based Communication-Computation Overlapping. 4.An estimator that helps study the performance of ATP on networks with different topologies. See full list on github.com To install ATP , you will need: •Python 3.8 or 3.9. •PyTorch 1.13 •SPMD from pytorch/tau See full list on github.com In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You ( 2023 ). ATP : Adaptive Tensor Parallelism for Foundation Models . Arxiv Preprint. ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections, is presented and the communication overhead of ATP decreases with scaling, indicating a qualitative leap forward. Jan 22, 2024 · Shenggan Cheng , Ziming Liu, Jiangsu Du, and Yang You. 2023 . ATP : Adaptive Tensor Parallelism for Foundation Models . arXiv preprint arXiv:2301.08658 ( 2023 ). Is ATP an adaptive tensor parallelism framework for foundation models? In this work, we present ATP, an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Can tensor parallelism be used in machine learning? However, current tensor parallelism in machine learning frameworks misses optimization opportunities in fitting various interconnection topologies. In this work, we present ATP, an adaptive tensor parallelism framework for foundation models, which can automatically select the optimal parallel strategy on different interconnections. How can ATP identify optimal tensor parallelism based on 2D device meshes? We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Combined with the hierarchical communication matrix , ATP can identify the optimal strategy in the search space. We also propose chunk-based overlapping to reduce communication overhead. Why is tensor parallelism important in Foundation model training? The increasing size of the models introduces great challenges for the training. Tensor parallelism is a critical technique that is currently used in almost all foundation model training and has a significant impact on overall training performance . [i5] Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You: ATP : Adaptive Tensor Parallelism for Foundation Models . CoRR abs/2301.08658 ( 2023 )", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Shenggan/atp", "content": "Adaptive Tensor Parallelism for Large Model Traning and Inference ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics. 1.Two-Level Search Space for Tensor Parallelism . 2. Adaptive Tensor Parallelism with Hierarchical Communication Matrix. 3.Chunk-based Communication-Computation Overlapping. 4.An estimator that helps study the performance of ATP on networks with different topologies. See full list on github.com To install ATP , you will need: •Python 3.8 or 3.9. •PyTorch 1.13 •SPMD from pytorch/tau See full list on github.com In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You ( 2023 ). ATP : Adaptive Tensor Parallelism for Foundation Models . Arxiv Preprint. ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections, is presented and the communication overhead of ATP decreases with scaling, indicating a qualitative leap forward. Jan 22, 2024 · Shenggan Cheng , Ziming Liu, Jiangsu Du, and Yang You. 2023 . ATP : Adaptive Tensor Parallelism for Foundation Models . arXiv preprint arXiv:2301.08658 ( 2023 ). Is ATP an adaptive tensor parallelism framework for foundation models? In this work, we present ATP, an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Can tensor parallelism be used in machine learning? However, current tensor parallelism in machine learning frameworks misses optimization opportunities in fitting various interconnection topologies. In this work, we present ATP, an adaptive tensor parallelism framework for foundation models, which can automatically select the optimal parallel strategy on different interconnections. How can ATP identify optimal tensor parallelism based on 2D device meshes? We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space. Combined with the hierarchical communication matrix , ATP can identify the optimal strategy in the search space. We also propose chunk-based overlapping to reduce communication overhead. Why is tensor parallelism important in Foundation model training? The increasing size of the models introduces great challenges for the training. Tensor parallelism is a critical technique that is currently used in almost all foundation model training and has a significant impact on overall training performance . [i5] Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You: ATP : Adaptive Tensor Parallelism for Foundation Models . CoRR abs/2301.08658 ( 2023 )"}
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{"idx": 2, "title": "ATP: Adaptive Tensor Parallelism for Foundation Models", "date": "", "ddg_snippet": "In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space.", "subpage_snippet": "", "source": "ui.adsabs.harvard.edu", "link": "https://ui.adsabs.harvard.edu/abs/2023arXiv230108658C/abstract", "content": "In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based on 2D device meshes and construct a search space."}
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{"idx": 3, "title": "ATP: Adaptive Tensor Parallelism for Foundation Models", "date": "", "ddg_snippet": "ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections, is presented and the communication overhead of ATP decreases with scaling, indicating a qualitative leap forward.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/ATP:-Adaptive-Tensor-Parallelism-for-Foundation-Cheng-Liu/c389de868d0647257ca2577e814630e8e3f4a484/figure/6", "content": "ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections, is presented and the communication overhead of ATP decreases with scaling, indicating a qualitative leap forward."}
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{"idx": 4, "title": "Shenggan Cheng - dblp", "date": "", "ddg_snippet": "[i5] Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You: ATP : Adaptive Tensor Parallelism for Foundation Models . CoRR abs/2301.08658 ( 2023 )", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/pid/258/2485", "content": "[i5] Shenggan Cheng , Ziming Liu, Jiangsu Du, Yang You: ATP : Adaptive Tensor Parallelism for Foundation Models . CoRR abs/2301.08658 ( 2023 )"}
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{"idx": 5, "title": "ATP : Adaptive Tensor Parallelism for Foundation Models ( 2023 )", "date": "", "ddg_snippet": "In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections.", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/atp-adaptive-tensor-parallelism-for-foundation-models-30sqdiqh", "content": "In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections."}
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{"idx": 6, "title": "Shenggan Cheng - Google Akademik", "date": "", "ddg_snippet": "2023 . ATP : Adaptive Tensor Parallelism for Foundation Models .", "subpage_snippet": "", "source": "scholar.google.com.tr", "link": "https://scholar.google.com.tr/citations?user=kDdwP6UAAAAJ&hl=tr", "content": "2023 . ATP : Adaptive Tensor Parallelism for Foundation Models ."}
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{"idx": 7, "title": "Adaptive Tensor Parallelism for Foundation Models", "date": "", "ddg_snippet": "Adaptive Tensor Parallelism for Large Model Traning and Inference. ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics.", "subpage_snippet": "", "source": "awesome.ecosyste.ms", "link": "https://awesome.ecosyste.ms/projects/github.com/shenggan/atp", "content": "Adaptive Tensor Parallelism for Large Model Traning and Inference. ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics."}
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{"idx": 8, "title": "Cheng , Shenggan | BibSonomy", "date": "", "ddg_snippet": "ACM, (2024 ) ATP : Adaptive Tensor Parallelism for Foundation Models .S. Cheng , Z. Liu, J. Du, and Y. You. CoRR, ( 2023 )tcFFT: A Fast Half-Precision FFT Library for NVIDIA Tensor Cores.B. Li, S. Cheng , and J. Lin.", "subpage_snippet": "", "source": "www.bibsonomy.org", "link": "https://www.bibsonomy.org/person/15184484c13c23846983c9b9376f4b47a/author/0", "content": "ACM, (2024 ) ATP : Adaptive Tensor Parallelism for Foundation Models .S. Cheng , Z. Liu, J. Du, and Y. You. CoRR, ( 2023 )tcFFT: A Fast Half-Precision FFT Library for NVIDIA Tensor Cores.B. Li, S. Cheng , and J. Lin."}
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{"idx": 9, "title": "Tensor Parallelism", "date": "", "ddg_snippet": "Tensor parallelism is a technique used to fit a large model in multiple GPUs. Tensor Parallelism only works for models officially supported, it will not work when falling back to transformers.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/docs/text-generation-inference/conceptual/tensor_parallelism", "content": "Tensor parallelism is a technique used to fit a large model in multiple GPUs. Tensor Parallelism only works for models officially supported, it will not work when falling back to transformers."}
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data/sampled_jsons/Atp_Adaptive_tensor_parallelism_for_foundation_models_Cheng_et_al._abstract_year_2023.jsonl
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{"idx": 0, "title": "ATP : Adaptive Tensor Parallelism for Foundation Models | DeepAI", "date": "", "ddg_snippet": "by Shenggan Cheng , et al .In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based...", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/publication/atp-adaptive-tensor-parallelism-for-foundation-models", "content": "by Shenggan Cheng , et al .In this work, we present ATP , an adaptive tensor parallelism framework for foundation models , which can automatically select the optimal parallel strategy on different interconnections. We propose column- and row-first tensor parallelism based..."}
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{"idx": 1, "title": "ATP : Adaptive Tensor Parallelism for Foundation Models", "date": "", "ddg_snippet": "View a PDF of the paper titled ATP : Adaptive Tensor Parallelism for Foundation Models , by Shenggan Cheng and 3 other authors.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2301.08658", "content": "View a PDF of the paper titled ATP : Adaptive Tensor Parallelism for Foundation Models , by Shenggan Cheng and 3 other authors."}
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{"idx": 2, "title": "Shenggan/ atp : Adaptive Tensor Parallelism for Foundation Models", "date": "", "ddg_snippet": "Adaptive Tensor Parallelism for Large Model Traning and Inference. ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics. Two-Level Search Space for Tensor Parallelism .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Shenggan/atp", "content": "Adaptive Tensor Parallelism for Large Model Traning and Inference. ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics. Two-Level Search Space for Tensor Parallelism ."}
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{"idx": 3, "title": "Shenggan Cheng - Google Akademik", "date": "", "ddg_snippet": "Takip et . Shenggan Cheng .2023. ATP : Adaptive Tensor Parallelism for Foundation Models .", "subpage_snippet": "", "source": "scholar.google.com.tr", "link": "https://scholar.google.com.tr/citations?user=kDdwP6UAAAAJ&hl=tr", "content": "Takip et . Shenggan Cheng .2023. ATP : Adaptive Tensor Parallelism for Foundation Models ."}
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{"idx": 4, "title": "Adaptive Tensor Parallelism for Foundation Models", "date": "", "ddg_snippet": "Adaptive Tensor Parallelism for Large Model Traning and Inference. ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics.", "subpage_snippet": "", "source": "awesome.ecosyste.ms", "link": "https://awesome.ecosyste.ms/projects/github.com/shenggan/atp", "content": "Adaptive Tensor Parallelism for Large Model Traning and Inference. ATP provides a high-performance implementation of Topology-aware Tensor Parallelism with the following characteristics."}
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| 6 |
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{"idx": 5, "title": "Tensor Parallelism", "date": "", "ddg_snippet": "Tensor parallelism is a technique used to fit a large model in multiple GPUs. Tensor Parallelism only works for models officially supported, it will not work when falling back to transformers.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/docs/text-generation-inference/conceptual/tensor_parallelism", "content": "Tensor parallelism is a technique used to fit a large model in multiple GPUs. Tensor Parallelism only works for models officially supported, it will not work when falling back to transformers."}
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{"idx": 6, "title": "AI Computing Systems for Large Language Models Training", "date": "", "ddg_snippet": "Ratner N, Levine Y, Belinkov Y et al . Parallel context windows for large language models . In Proc. the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Jul.", "subpage_snippet": "", "source": "www.sciopen.com", "link": "https://www.sciopen.com/article/10.1007/s11390-024-4178-1", "content": "Ratner N, Levine Y, Belinkov Y et al . Parallel context windows for large language models . In Proc. the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Jul."}
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{"idx": 7, "title": "Distributed Training of Large Language Models Across Multiple GPUs...", "date": "", "ddg_snippet": "Tensor parallelism represents the most sophisticated form of model parallelism , where individual tensor operations are distributed across multiple devices.", "subpage_snippet": "", "source": "www.rohan-paul.com", "link": "https://www.rohan-paul.com/p/distributed-training-of-large-language", "content": "Tensor parallelism represents the most sophisticated form of model parallelism , where individual tensor operations are distributed across multiple devices."}
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{"idx": 8, "title": "Cheng , Shenggan | BibSonomy", "date": "", "ddg_snippet": "ACM, (2024 ) ATP : Adaptive Tensor Parallelism for Foundation Models .S. Cheng , Z. Liu, J. Du, and Y. You. CoRR, (2023 )tcFFT: A Fast Half-Precision FFT Library for NVIDIA Tensor Cores.B. Li, S. Cheng , and J. Lin.", "subpage_snippet": "", "source": "www.bibsonomy.org", "link": "https://www.bibsonomy.org/person/15184484c13c23846983c9b9376f4b47a/author/0", "content": "ACM, (2024 ) ATP : Adaptive Tensor Parallelism for Foundation Models .S. Cheng , Z. Liu, J. Du, and Y. You. CoRR, (2023 )tcFFT: A Fast Half-Precision FFT Library for NVIDIA Tensor Cores.B. Li, S. Cheng , and J. Lin."}
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{"idx": 9, "title": "How Tensor Parallelism Works - Amazon SageMaker AI", "date": "", "ddg_snippet": "How the library adapts tensor parallelism to PyTorch nn.Linear module. Tensor parallelism takes place at the level of nn.Modules; it partitions specific modules in the model across tensor parallel ranks.", "subpage_snippet": "", "source": "docs.aws.amazon.com", "link": "https://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel-extended-features-pytorch-tensor-parallelism-how-it-works.html", "content": "How the library adapts tensor parallelism to PyTorch nn.Linear module. Tensor parallelism takes place at the level of nn.Modules; it partitions specific modules in the model across tensor parallel ranks."}
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data/sampled_jsons/BA-Cycle_method_∆∆G_calculation_Section_3.2_Boltzmann-Aligned_Inverse_Folding.jsonl
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{"idx": 0, "title": "boltzmann-aligned inverse folding model as", "date": "", "ddg_snippet": "This method is named BA-Cycle and uses the inverse folding model to evaluate ∆∆G by predicting the likelihoods of protein sequences, as shown on the left side ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/69e9689e53a10509760846b53b77823430a0c523.pdf", "content": "This method is named BA-Cycle and uses the inverse folding model to evaluate ∆∆G by predicting the likelihoods of protein sequences, as shown on the left side ..."}
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{"idx": 1, "title": "Calculation of the relative metastabilities of proteins in ...", "date": "", "ddg_snippet": "by JM Dick · 2008 · Cited by 9 — The purpose of this study is to quantify using a metastable equilibrium reference state the responses of popu- lations of model proteins for different ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/0812.0191", "content": "by JM Dick · 2008 · Cited by 9 — The purpose of this study is to quantify using a metastable equilibrium reference state the responses of popu- lations of model proteins for different ..."}
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{"idx": 2, "title": "Limitations and challenges in protein stability prediction ...", "date": "", "ddg_snippet": "by T Sanavia · 2020 · Cited by 155 — Δ G AB = - R T l o g A B. This relation is anti-symmetric in A and B, since the inverse transformation (from B to A) is described by: Δ G BA ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7397395/", "content": "by T Sanavia · 2020 · Cited by 155 — Δ G AB = - R T l o g A B. This relation is anti-symmetric in A and B, since the inverse transformation (from B to A) is described by: Δ G BA ..."}
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{"idx": 3, "title": "Computationally reconstructing cotranscriptional RNA ...", "date": "", "ddg_snippet": "by MY Angela · 2021 · Cited by 80 — We developed a method , named reconstructing RNA dynamics from data (R2D2), that combines nucleotide-resolution experimental RNA structure ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S1097276520309369", "content": "by MY Angela · 2021 · Cited by 80 — We developed a method , named reconstructing RNA dynamics from data (R2D2), that combines nucleotide-resolution experimental RNA structure ..."}
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| 5 |
+
{"idx": 4, "title": "Advancing Single-Molecule Nanopore Sensing", "date": "", "ddg_snippet": "calculation of the Gibbs free energy change, ∆G . At equilibrium, ∆G is related to the dissociation constant by the equation: Page 32. 16. ∆G = RT lnKD.", "subpage_snippet": "", "source": "scholar.smu.edu", "link": "https://scholar.smu.edu/cgi/viewcontent.cgi?article=1005&context=engineering_multidisciplinary_etds", "content": "calculation of the Gibbs free energy change, ∆G . At equilibrium, ∆G is related to the dissociation constant by the equation: Page 32. 16. ∆G = RT lnKD."}
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+
{"idx": 5, "title": "An Ensemble-Based Protocol for the Computational Prediction ...", "date": "", "ddg_snippet": "by NA Altwaijry · 2017 · Cited by 31 — An Ensemble-Based Protocol for the Computational Prediction of Helix–Helix Interactions in G Protein-Coupled Receptors using Coarse-Grained Molecular Dynamics.", "subpage_snippet": "", "source": "pubs.acs.org", "link": "https://pubs.acs.org/doi/10.1021/acs.jctc.6b01246", "content": "by NA Altwaijry · 2017 · Cited by 31 — An Ensemble-Based Protocol for the Computational Prediction of Helix–Helix Interactions in G Protein-Coupled Receptors using Coarse-Grained Molecular Dynamics."}
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| 7 |
+
{"idx": 6, "title": "Analysis of protein missense alterations by combining ...", "date": "", "ddg_snippet": "by A Gyulkhandanyan · 2020 · Cited by 49 — It is a structure‐based approach that provides predicted free energy change (ΔΔG) values as well as corresponding confidence estimation values for the ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7196459/", "content": "by A Gyulkhandanyan · 2020 · Cited by 49 — It is a structure‐based approach that provides predicted free energy change (ΔΔG) values as well as corresponding confidence estimation values for the ..."}
|
| 8 |
+
{"idx": 7, "title": "RNA Structural Dynamics As Captured by Molecular Simulations", "date": "", "ddg_snippet": "by J Šponer · 2018 · Cited by 567 — We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules.", "subpage_snippet": "", "source": "pubs.acs.org", "link": "https://pubs.acs.org/doi/10.1021/acs.chemrev.7b00427", "content": "by J Šponer · 2018 · Cited by 567 — We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules."}
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| 9 |
+
{"idx": 8, "title": "A general temperature-guided language model to design ...", "date": "", "ddg_snippet": "27 Nov 2024 — Designing protein mutants with both high stability and activity is a critical yet challenging task in protein engineering.", "subpage_snippet": "", "source": "www.science.org", "link": "https://www.science.org/doi/10.1126/sciadv.adr2641", "content": "27 Nov 2024 — Designing protein mutants with both high stability and activity is a critical yet challenging task in protein engineering."}
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| 10 |
+
{"idx": 9, "title": "Control of RNA function by conformational design", "date": "", "ddg_snippet": "I present four projects, two of them in form of a peer-reviewed publication, the other two are unpublished work with preliminary results.", "subpage_snippet": "", "source": "www.dna.caltech.edu", "link": "https://www.dna.caltech.edu/~badelt/files/badelt_thesis.pdf", "content": "I present four projects, two of them in form of a peer-reviewed publication, the other two are unpublished work with preliminary results."}
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data/sampled_jsons/BA-DDG_github_GPU_hardware.jsonl
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{"idx": 0, "title": "Configuration Options | aim-uofa/BA-DDG | DeepWiki", "date": "", "ddg_snippet": "This document provides a comprehensive guide to configuring the BA-DDG system for both training and inference operations. The BA-DDG system uses JSON configuration files to define all aspects of model behavior, from architecture parameters to training hyperparameters. For specific details about training configuration, see Training Configuration, and for inference-specific options, see ...", "subpage_snippet": "", "source": "deepwiki.com", "link": "https://deepwiki.com/aim-uofa/BA-DDG/5-configuration-options", "content": "This document provides a comprehensive guide to configuring the BA-DDG system for both training and inference operations. The BA-DDG system uses JSON configuration files to define all aspects of model behavior, from architecture parameters to training hyperparameters. For specific details about training configuration, see Training Configuration, and for inference-specific options, see ..."}
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| 2 |
+
{"idx": 1, "title": "BA_Cycle & BA_DDG with the same res #2 - GitHub", "date": "", "ddg_snippet": "Hi, I have tried to run your examples on the skempi dataset, but I got the same results for both the BA Cycle and BA DDG . Does anyone know what the problem may be?", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/aim-uofa/BA-DDG/issues/2", "content": "Hi, I have tried to run your examples on the skempi dataset, but I got the same results for both the BA Cycle and BA DDG . Does anyone know what the problem may be?"}
|
| 3 |
+
{"idx": 2, "title": "Optimization | aim-uofa/BA-DDG | DeepWiki", "date": "", "ddg_snippet": "The BA-DDG system uses a structured optimization process with batch-based training across multiple cross-validation folds. The training pipeline is managed through the train_skempi.py script which orchestrates the entire training process.", "subpage_snippet": "", "source": "deepwiki.com", "link": "https://deepwiki.com/aim-uofa/BA-DDG/3.2-optimization", "content": "The BA-DDG system uses a structured optimization process with batch-based training across multiple cross-validation folds. The training pipeline is managed through the train_skempi.py script which orchestrates the entire training process."}
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| 4 |
+
{"idx": 3, "title": "Issues · aim-uofa/BA-DDG - GitHub", "date": "", "ddg_snippet": "[ICLR 2025 Spotlight] Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions - aim-uofa/ BA - DDG", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/aim-uofa/BA-DDG/issues", "content": "[ICLR 2025 Spotlight] Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions - aim-uofa/ BA - DDG"}
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+
{"idx": 4, "title": "In-Depth GPU Hardware Architecture and Operating Mechanisms", "date": "", "ddg_snippet": "Modern GPUs share similar structures and components, and their operating mechanisms also have many commonalities. Below is an overview of the operating mechanism of the Fermi architecture: Starting with the Fermi architecture, NVIDIA has adopted a similar principle in its designs. A Giga Thread Engine is used to manage all ongoing tasks. The GPU is divided into multiple GPCs (Graphics ...", "subpage_snippet": "", "source": "alalba221.github.io", "link": "https://alalba221.github.io/blog/vulkan/GPU_HardWare", "content": "Modern GPUs share similar structures and components, and their operating mechanisms also have many commonalities. Below is an overview of the operating mechanism of the Fermi architecture: Starting with the Fermi architecture, NVIDIA has adopted a similar principle in its designs. A Giga Thread Engine is used to manage all ongoing tasks. The GPU is divided into multiple GPCs (Graphics ..."}
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| 6 |
+
{"idx": 5, "title": "GitHub - NVIDIA/open-gpu-doc: Documentation of NVIDIA chip/hardware ...", "date": "", "ddg_snippet": "Documentation of NVIDIA chip/ hardware interfaces. Contribute to NVIDIA/open- gpu -doc development by creating an account on GitHub .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/NVIDIA/open-gpu-doc", "content": "Documentation of NVIDIA chip/ hardware interfaces. Contribute to NVIDIA/open- gpu -doc development by creating an account on GitHub ."}
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| 7 |
+
{"idx": 6, "title": "GitHub - aim-uofa/BA-DDG: [ICLR 2025 Spotlight] Boltzmann-Aligned ...", "date": "", "ddg_snippet": "The official implementation of our ICLR 2025 Spotlight paper \"Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions\", which establishes a bidirectional connection between log-likelihood in protein inverse folding models and Δ Δ G values.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/aim-uofa/BA-DDG", "content": "The official implementation of our ICLR 2025 Spotlight paper \"Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions\", which establishes a bidirectional connection between log-likelihood in protein inverse folding models and Δ Δ G values."}
|
| 8 |
+
{"idx": 7, "title": "BA-DDG/README.md at master · aim-uofa/BA-DDG · GitHub", "date": "", "ddg_snippet": "The official implementation of our ICLR 2025 Spotlight paper \"Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions\", which establishes a bidirectional connection between log-likelihood in protein inverse folding models and Δ Δ G values.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/aim-uofa/BA-DDG/blob/master/README.md", "content": "The official implementation of our ICLR 2025 Spotlight paper \"Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions\", which establishes a bidirectional connection between log-likelihood in protein inverse folding models and Δ Δ G values."}
|
| 9 |
+
{"idx": 8, "title": "B -a Inverse Folding Model As a Predictor of Mutational Effects on ...", "date": "", "ddg_snippet": "h Boltzmann Alignment. BA-DDG employs a forward process identical to that of BA -Cycle. During training, the parameters θ of the inverse folding model and kBT in Eq. 10 are treated as learnable parameters that undergo optimization. The objective of BA-DDG is to minimize the discrepancy between the ground truth ∆∆G and the predicted ∆∆G ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=lzdFImKK8w", "content": "h Boltzmann Alignment. BA-DDG employs a forward process identical to that of BA -Cycle. During training, the parameters θ of the inverse folding model and kBT in Eq. 10 are treated as learnable parameters that undergo optimization. The objective of BA-DDG is to minimize the discrepancy between the ground truth ∆∆G and the predicted ∆∆G ..."}
|
| 10 |
+
{"idx": 9, "title": "Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational ...", "date": "", "ddg_snippet": "Poster Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions Xiaoran Jiao · Weian Mao · Wengong Jin · Peiyuan Yang · Hao Chen · Chunhua Shen", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2025/poster/28490", "content": "Poster Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions Xiaoran Jiao · Weian Mao · Wengong Jin · Peiyuan Yang · Hao Chen · Chunhua Shen"}
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data/sampled_jsons/BIT-VO_Murai_in-pixel_feature_tracking.jsonl
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{"idx": 0, "title": "Transitioning to the Updated Postback/ Pixel Technology | ClickBank...", "date": "", "ddg_snippet": "Our existing integration features , both ISR tracking pixels and IPN/INS, will remain available for use even after the new Postback/ Pixels feature is released.Create the new integration in your primary (Master) user account, and set the status to inactive. Related: Postback/ Pixels Guide.", "subpage_snippet": "", "source": "support.clickbank.com", "link": "https://support.clickbank.com/en/articles/10535372-transitioning-to-the-updated-postback-pixel-technology", "content": "Our existing integration features , both ISR tracking pixels and IPN/INS, will remain available for use even after the new Postback/ Pixels feature is released.Create the new integration in your primary (Master) user account, and set the status to inactive. Related: Postback/ Pixels Guide."}
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| 2 |
+
{"idx": 1, "title": "Tracking pixel vs. cookie: What's the difference?", "date": "", "ddg_snippet": "Tracking pixels and cookies both track users while they browse the web.In January 2024, Google Chrome rolled out the testing phase of its Tracking Protection feature to 1% of Chrome users globally.", "subpage_snippet": "", "source": "www.techtarget.com", "link": "https://www.techtarget.com/whatis/feature/Tracking-pixel-vs-cookie-Whats-the-difference", "content": "Tracking pixels and cookies both track users while they browse the web.In January 2024, Google Chrome rolled out the testing phase of its Tracking Protection feature to 1% of Chrome users globally."}
|
| 3 |
+
{"idx": 2, "title": "Resize Image Pixel Online", "date": "", "ddg_snippet": "Pi7 Image Tool can resize the image pixel . Here, you can resize JPEG and PNG images. The tool also provides lossless compression to images.", "subpage_snippet": "", "source": "image.pi7.org", "link": "https://image.pi7.org/resize-image-pixel", "content": "Pi7 Image Tool can resize the image pixel . Here, you can resize JPEG and PNG images. The tool also provides lossless compression to images."}
|
| 4 |
+
{"idx": 3, "title": "How Tracking Pixels Monitor Your Email, and... - Make Tech Easier", "date": "", "ddg_snippet": "Tracking pixels in your email. Tracking pixels on the web. Tracking Pixel Feature . You know that little “Do you want to send a read receipt?” message you get every now and then when you open an email?", "subpage_snippet": "", "source": "www.maketecheasier.com", "link": "https://www.maketecheasier.com/how-tracking-pixels-monitor-email/", "content": "Tracking pixels in your email. Tracking pixels on the web. Tracking Pixel Feature . You know that little “Do you want to send a read receipt?” message you get every now and then when you open an email?"}
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| 5 |
+
{"idx": 4, "title": "How to enable Body Temperature on your Google Pixel using the...", "date": "", "ddg_snippet": "The Google Pixel devices come with a Thermometer app to measure temperature of any object, including bodies. Here is how to activate Body Temperature on your Google Pixel 8 Pro even outside the United States.", "subpage_snippet": "", "source": "www.androidsage.com", "link": "https://www.androidsage.com/2024/01/26/how-to-enable-body-temperature-on-your-google-pixel-outside-us/", "content": "The Google Pixel devices come with a Thermometer app to measure temperature of any object, including bodies. Here is how to activate Body Temperature on your Google Pixel 8 Pro even outside the United States."}
|
| 6 |
+
{"idx": 5, "title": "Wplace Pixel Art - Convert Images to wplace Pixel", "date": "", "ddg_snippet": "Our Wplace pixel converter supports multiple pixel art styles optimized for the Wplace platform. From retro 8- bit aesthetics to modern pixel designs, every conversion is crafted to stand out on the world's most viral collaborative art project.", "subpage_snippet": "", "source": "wplacepixel.com", "link": "https://wplacepixel.com/", "content": "Our Wplace pixel converter supports multiple pixel art styles optimized for the Wplace platform. From retro 8- bit aesthetics to modern pixel designs, every conversion is crafted to stand out on the world's most viral collaborative art project."}
|
| 7 |
+
{"idx": 6, "title": "4sysops.com/archives/iis-failed-request- tracing", "date": "", "ddg_snippet": "The failed request tracing is a feature that is available under web server role.", "subpage_snippet": "", "source": "4sysops.com", "link": "https://4sysops.com/archives/iis-failed-request-tracing/", "content": "The failed request tracing is a feature that is available under web server role."}
|
| 8 |
+
{"idx": 7, "title": "Video to GIF Converter - FreeConvert.com", "date": "", "ddg_snippet": "Our Video to GIF converter is free and works on any browser. We use 256- bit SSL encryption and remove your files after a few hours for privacy.", "subpage_snippet": "", "source": "www.freeconvert.com", "link": "https://www.freeconvert.com/convert/video-to-gif", "content": "Our Video to GIF converter is free and works on any browser. We use 256- bit SSL encryption and remove your files after a few hours for privacy."}
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| 9 |
+
{"idx": 8, "title": "Торговые центры в Нячанге, которые стоит посетить в 2025 г.", "date": "", "ddg_snippet": "Рынки и ТЦ - Нячанг - необходимая информация, погода, экскурсии, цены, отдых, шопинг и многое другое.", "subpage_snippet": "", "source": "dv-tours.com", "link": "https://dv-tours.com/torgovye-centry-v-nyachange/", "content": "Рынки и ТЦ - Нячанг - необходимая информация, погода, экскурсии, цены, отдых, шопинг и многое другое."}
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| 10 |
+
{"idx": 9, "title": "Горящие туры из Москвы 2025– Египет, Турция, ОАЭ до -70...", "date": "", "ddg_snippet": "Горящие туры из Москвы, цены до -70% на \"все включено\" от всех туроператоров в Египет, Турцию, Таиланд, Сочи, ОАЭ. Вылет в ближайшие дни, перелёт и трансфер включены в стоимость.", "subpage_snippet": "", "source": "travelata.ru", "link": "https://travelata.ru/tury", "content": "Горящие туры из Москвы, цены до -70% на \"все включено\" от всех туроператоров в Египет, Турцию, Таиланд, Сочи, ОАЭ. Вылет в ближайшие дни, перелёт и трансфер включены в стоимость."}
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data/sampled_jsons/Balke_Pearl_1994_probabilistic_evaluation_counterfactual_queries_abstract.jsonl
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{"idx": 0, "title": "PDF 1994-Probabilistic Evaluation of Counterfactual Queries", "date": "", "ddg_snippet": "Abstract In the real world, we seldom have adequate informa- Evaluation of counterfactual queries (e.g., \"If A were tion for verifying the truth of an indicative sentence, true, would C have been true?\") is important to fault much less the truth of a counterfactual sentence. Ex- cept for the small set of relationships ...", "subpage_snippet": "", "source": "cdn.aaai.org", "link": "https://cdn.aaai.org/AAAI/1994/AAAI94-035.pdf", "content": "Abstract In the real world, we seldom have adequate informa- Evaluation of counterfactual queries (e.g., \"If A were tion for verifying the truth of an indicative sentence, true, would C have been true?\") is important to fault much less the truth of a counterfactual sentence. Ex- cept for the small set of relationships ..."}
|
| 2 |
+
{"idx": 1, "title": "Probabilistic evaluation of counterfactual queries", "date": "", "ddg_snippet": "Article Probabilistic evaluation of counterfactual queries Authors: Alexander Balke , Judea Pearl Authors Info & Claims", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/199288.178004", "content": "Article Probabilistic evaluation of counterfactual queries Authors: Alexander Balke , Judea Pearl Authors Info & Claims"}
|
| 3 |
+
{"idx": 2, "title": "Counterfactual Probabilities: Computational Methods, Bounds and ...", "date": "", "ddg_snippet": "Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. In this paper we present methods for computing the probabilities of such queries using the formulation proposed in [ Balke and Pearl , 1994 ], where the antecedent of the query is interpreted as an external action that forces the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/1302.6784", "content": "Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. In this paper we present methods for computing the probabilities of such queries using the formulation proposed in [ Balke and Pearl , 1994 ], where the antecedent of the query is interpreted as an external action that forces the ..."}
|
| 4 |
+
{"idx": 3, "title": "PDF Probabilistic evaluation of counterfactual queries", "date": "", "ddg_snippet": "Abstract Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal net- works to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true. The antecedent of the query is inter ...", "subpage_snippet": "", "source": "gill.readingroo.ms", "link": "https://gill.readingroo.ms/ENTER/Philosophy-Psychology-Sociology+-+&+SEE+Self+Help/1+-+More+Books+on+Philosophy/Judea+Pearl+-+Probabilistic+Counterfactual+Queries.pdf", "content": "Abstract Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal net- works to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true. The antecedent of the query is inter ..."}
|
| 5 |
+
{"idx": 4, "title": "Counterfactual Probabilities: Computational Methods, Bounds and ...", "date": "", "ddg_snippet": "Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. In this paper we present methods for computing the probabilities of such queries using the formulation proposed in [ Balke and Pearl , 1994 ], where the antecedent of the query is interpreted as an external action that forces the ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/B9781558603325500110", "content": "Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. In this paper we present methods for computing the probabilities of such queries using the formulation proposed in [ Balke and Pearl , 1994 ], where the antecedent of the query is interpreted as an external action that forces the ..."}
|
| 6 |
+
{"idx": 5, "title": "dblp: Probabilistic Evaluation of Counterfactual Queries.", "date": "", "ddg_snippet": "Bibliographic details on Probabilistic Evaluation of Counterfactual Queries .", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/conf/aaai/BalkeP94", "content": "Bibliographic details on Probabilistic Evaluation of Counterfactual Queries ."}
|
| 7 |
+
{"idx": 6, "title": "PDF Probabilistic Evaluation of Counterfactual Queries", "date": "", "ddg_snippet": "Paper Contribution Provides the formal notation for a counterfactual query such as \"If A were true, then what is the probability that C would have been true, given that we know B.\" Provides an inference algorithm for the probabilistic evaluation of counterfactual queries", "subpage_snippet": "", "source": "ics.uci.edu", "link": "https://ics.uci.edu/~dechter/courses/ics-295cr/2021-22_Q2_Winter/slides/classP3-w22-KoheiTsujio-Probabilistic_Evaluation_of_Counterfactual_Queries.pdf", "content": "Paper Contribution Provides the formal notation for a counterfactual query such as \"If A were true, then what is the probability that C would have been true, given that we know B.\" Provides an inference algorithm for the probabilistic evaluation of counterfactual queries"}
|
| 8 |
+
{"idx": 7, "title": "Probabilistic evaluation of counterfactual queries - Technion", "date": "", "ddg_snippet": "Abstract Evaluation of counterfactual queries (e.g., 'If A were true, would C have been true?') is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal networks to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true. The antecedent of the query is interpreted ...", "subpage_snippet": "", "source": "cris.technion.ac.il", "link": "https://cris.technion.ac.il/en/publications/probabilistic-evaluation-of-counterfactual-queries", "content": "Abstract Evaluation of counterfactual queries (e.g., 'If A were true, would C have been true?') is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal networks to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true. The antecedent of the query is interpreted ..."}
|
| 9 |
+
{"idx": 8, "title": "Probabilistic Evaluation of Counterfactual Queries - AAAI", "date": "", "ddg_snippet": "Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal networks to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true.", "subpage_snippet": "", "source": "aaai.org", "link": "https://aaai.org/papers/00230-AAAI94-035-probabilistic-evaluation-of-counterfactual-queries/", "content": "Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal networks to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true."}
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| 10 |
+
{"idx": 9, "title": "Probabilistic Evaluation of Counterfactual Queries - ResearchGate", "date": "", "ddg_snippet": "In 1994 , in his Ph.D. dissertation, Alexander Balke gave a method for translating a certain type of causal theory, represented by a directed acyclic graph (DAG), and causal query into a ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/359040417_Probabilistic_Evaluation_of_Counterfactual_Queries", "content": "In 1994 , in his Ph.D. dissertation, Alexander Balke gave a method for translating a certain type of causal theory, represented by a directed acyclic graph (DAG), and causal query into a ..."}
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data/sampled_jsons/Balke_and_Pearl_1994_Probabilistic_evaluation_of_counterfactual_queries_abstract.jsonl
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{"idx": 0, "title": "PDF 1994-Probabilistic Evaluation of Counterfactual Queries", "date": "", "ddg_snippet": "Balke , A., and Pearl , J. 1994 . Bounds on probabilisti- tions. In Logic Programming: Proceedings of the 1991 tally evaluated counterfactual queries. Technical Re- International Symposium, 566-577. Cambridge, MA: port R-213-B, UCLA Cognitive Systems Lab. Boutilier, C. 1992. A logic for revision and subjunc- MIT Press.", "subpage_snippet": "", "source": "cdn.aaai.org", "link": "https://cdn.aaai.org/AAAI/1994/AAAI94-035.pdf", "content": "Balke , A., and Pearl , J. 1994 . Bounds on probabilisti- tions. In Logic Programming: Proceedings of the 1991 tally evaluated counterfactual queries. Technical Re- International Symposium, 566-577. Cambridge, MA: port R-213-B, UCLA Cognitive Systems Lab. Boutilier, C. 1992. A logic for revision and subjunc- MIT Press."}
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{"idx": 1, "title": "Probabilistic evaluation of counterfactual queries", "date": "", "ddg_snippet": "Article Probabilistic evaluation of counterfactual queries Authors: Alexander Balke , Judea Pearl Authors Info & Claims", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/199288.178004", "content": "Article Probabilistic evaluation of counterfactual queries Authors: Alexander Balke , Judea Pearl Authors Info & Claims"}
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{"idx": 2, "title": "Probabilistic evaluation of counterfactual queries - Technion", "date": "", "ddg_snippet": "Abstract Evaluation of counterfactual queries (e.g., 'If A were true, would C have been true?') is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal networks to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true. The antecedent of the query is interpreted ...", "subpage_snippet": "", "source": "cris.technion.ac.il", "link": "https://cris.technion.ac.il/en/publications/probabilistic-evaluation-of-counterfactual-queries", "content": "Abstract Evaluation of counterfactual queries (e.g., 'If A were true, would C have been true?') is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal networks to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true. The antecedent of the query is interpreted ..."}
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{"idx": 3, "title": "dblp: Probabilistic Evaluation of Counterfactual Queries.", "date": "", "ddg_snippet": "Bibliographic details on Probabilistic Evaluation of Counterfactual Queries .", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/conf/aaai/BalkeP94", "content": "Bibliographic details on Probabilistic Evaluation of Counterfactual Queries ."}
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{"idx": 4, "title": "PDF Probabilistic Evaluation of Counterfactual Queries", "date": "", "ddg_snippet": "Paper Contribution Provides the formal notation for a counterfactual query such as \"If A were true, then what is the probability that C would have been true, given that we know B.\" Provides an inference algorithm for the probabilistic evaluation of counterfactual queries", "subpage_snippet": "", "source": "ics.uci.edu", "link": "https://ics.uci.edu/~dechter/courses/ics-295cr/2021-22_Q2_Winter/slides/classP3-w22-KoheiTsujio-Probabilistic_Evaluation_of_Counterfactual_Queries.pdf", "content": "Paper Contribution Provides the formal notation for a counterfactual query such as \"If A were true, then what is the probability that C would have been true, given that we know B.\" Provides an inference algorithm for the probabilistic evaluation of counterfactual queries"}
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| 6 |
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{"idx": 5, "title": "PDF 1994-Probabilistic Evaluation of Counterfactual Queries", "date": "", "ddg_snippet": "Because of the tight connection between counterfac- of temporal persistence, and , as noted in ( Pearl 1993c), such a model is not part of static Bayesian networks. tuals and causal influences, any algorithm for comput- ing counterfactual queries must rely heavily on causal Functional specification, however, implicitly contains knowledge of the ...", "subpage_snippet": "", "source": "aaai-24.aaai.org", "link": "https://aaai-24.aaai.org/Papers/AAAI/1994/AAAI94-035.pdf", "content": "Because of the tight connection between counterfac- of temporal persistence, and , as noted in ( Pearl 1993c), such a model is not part of static Bayesian networks. tuals and causal influences, any algorithm for comput- ing counterfactual queries must rely heavily on causal Functional specification, however, implicitly contains knowledge of the ..."}
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| 7 |
+
{"idx": 6, "title": "Probabilistic Evaluation of Counterfactual Queries - CORE", "date": "", "ddg_snippet": "Abstract Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal networks to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true. The antecedent of the query ...", "subpage_snippet": "", "source": "core.ac.uk", "link": "https://core.ac.uk/display/24325313", "content": "Abstract Evaluation of counterfactual queries (e.g., \"If A were true, would C have been true?\") is important to fault diagnosis, planning, and determination of liability. We present a formalism that uses probabilistic causal networks to evaluate one's belief that the counterfactual consequent, C, would have been true if the antecedent, A, were true. The antecedent of the query ..."}
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| 8 |
+
{"idx": 7, "title": "Probabilistic Evaluation of Counterfactual Queries - ResearchGate", "date": "", "ddg_snippet": "In this paper, we focus on two fundamental issues in causal inference: probabilistic evaluation of counterfactual queries and the assumptions used to evaluate causal effects.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/359040417_Probabilistic_Evaluation_of_Counterfactual_Queries", "content": "In this paper, we focus on two fundamental issues in causal inference: probabilistic evaluation of counterfactual queries and the assumptions used to evaluate causal effects."}
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| 9 |
+
{"idx": 8, "title": "Probabilistic Evaluation of Counterfactual Queries", "date": "", "ddg_snippet": "Probabilistic evaluation of counterfactual queries . AAAI' 94 : Proceedings of the Twelfth AAAI National Conference on Artificial Intelligence.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3501714.3501733", "content": "Probabilistic evaluation of counterfactual queries . AAAI' 94 : Proceedings of the Twelfth AAAI National Conference on Artificial Intelligence."}
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{"idx": 9, "title": "Probabilistic evaluation of counterfactual queries", "date": "", "ddg_snippet": "by A Balke · 1994 · Cited by 239 — Balke , A., and Pearl , J. 1993. Nonparametric bounds on causal effects ... Probabilistic Evaluation of Counterfactual Queries . Probabilistic and Causal ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/2891730.2891765", "content": "by A Balke · 1994 · Cited by 239 — Balke , A., and Pearl , J. 1993. Nonparametric bounds on causal effects ... Probabilistic Evaluation of Counterfactual Queries . Probabilistic and Causal ..."}
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{"idx": 0, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models DCBM: Data-Efficient Visual Concept Bottleneck Models DCBM: Data-Efficient Visual Concept Bottleneck Models DCBM: Data-Efficient Visual Concept Bottleneck Models :: MPG.PuRe [2007.04612] Concept Bottleneck Models - arXiv.org ICML DCBM: Data-Efficient Visual Concept Bottleneck Models GitHub - deepopo/DCBM", "date": "", "ddg_snippet": "Dec 16, 2024 · Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts . However, current CBMs typically rely on concept sets extracted from large language models or extensive image corpora, limiting their effectiveness in data -sparse scenarios. We propose Data-efficient CBMs (DCBMs), which reduce the need for large sample sizes ... We propose Data -eficient CBMs (DCBMs), which reduce the need for large sample sizes during concept gener-ation while preserving interpretability. DCBMs define concepts as image regions detected by seg-mentation or detection foundation models , allow-ing each image to generate multiple concepts across different granularities. data /: Directories for classes, concepts , datasets, embeddings, and segments. experiments/: Code for experiments detailed in the main paper and supplementary material. Author: Prasse, Katharina et al.; Genre: Paper ; Published online: 2025; Open Access; Keywords: Computer Science, Computer Vision and Pattern Recognition, cs.CV; Title: DCBM : Data-Efficient Visual Concept Bottleneck Models Jul 9, 2020 · On x-ray grading and bird identification, concept bottleneck models achieve competitive accuracy with standard end-to-end models , while enabling interpretation in terms of high-level clinical concepts (\"bone spurs\") or bird attributes (\"wing color\"). Poster in Workshop: Actionable Interpretability DCBM : Data-Efficient Visual Concept Bottleneck Models Katharina Prasse · Patrick Knab · Sascha Marton · Christian Bartelt · Margret Keuper This is an implementation of the IEEE TPAMI paper The Decoupling Concept Bottleneck Model ( DCBM ). The vision-language- model (VLM) part is being refined and will be available soon. Figure 1: DCBM Pipeline. (A) DCBM for prediction and interpretation. (B) DCBM for human-machine interaction, including forward intervention and backward rectification.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2412.11576", "content": "Dec 16, 2024 · Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts . However, current CBMs typically rely on concept sets extracted from large language models or extensive image corpora, limiting their effectiveness in data -sparse scenarios. We propose Data-efficient CBMs (DCBMs), which reduce the need for large sample sizes ... We propose Data -eficient CBMs (DCBMs), which reduce the need for large sample sizes during concept gener-ation while preserving interpretability. DCBMs define concepts as image regions detected by seg-mentation or detection foundation models , allow-ing each image to generate multiple concepts across different granularities. data /: Directories for classes, concepts , datasets, embeddings, and segments. experiments/: Code for experiments detailed in the main paper and supplementary material. Author: Prasse, Katharina et al.; Genre: Paper ; Published online: 2025; Open Access; Keywords: Computer Science, Computer Vision and Pattern Recognition, cs.CV; Title: DCBM : Data-Efficient Visual Concept Bottleneck Models Jul 9, 2020 · On x-ray grading and bird identification, concept bottleneck models achieve competitive accuracy with standard end-to-end models , while enabling interpretation in terms of high-level clinical concepts (\"bone spurs\") or bird attributes (\"wing color\"). Poster in Workshop: Actionable Interpretability DCBM : Data-Efficient Visual Concept Bottleneck Models Katharina Prasse · Patrick Knab · Sascha Marton · Christian Bartelt · Margret Keuper This is an implementation of the IEEE TPAMI paper The Decoupling Concept Bottleneck Model ( DCBM ). The vision-language- model (VLM) part is being refined and will be available soon. Figure 1: DCBM Pipeline. (A) DCBM for prediction and interpretation. (B) DCBM for human-machine interaction, including forward intervention and backward rectification."}
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{"idx": 1, "title": "KathPra/ DCBM : Official repo for ICML25 paper : DCBM : Data - Efficient ...", "date": "", "ddg_snippet": "Aligning Visual and Semantic Interpretability through Visually Grounded Concept Bottleneck Models .We primarily report on CLIP models [RN-50, ViT-B16, ViT-L14] and save embeddings to reuse in DCBM training for efficiency .", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/KathPra/DCBM", "content": "Aligning Visual and Semantic Interpretability through Visually Grounded Concept Bottleneck Models .We primarily report on CLIP models [RN-50, ViT-B16, ViT-L14] and save embeddings to reuse in DCBM training for efficiency ."}
|
| 3 |
+
{"idx": 2, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "We propose Data -eficient CBMs (DCBMs), which reduce the need for large sample sizes during concept gener-ation while preserving interpretability. DCBMs define concepts as image regions detected by seg-mentation or detection foundation models , allow-ing each image to generate multiple concepts across different granularities.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/attachment?id=BdO4R6XxUH&name=pdf", "content": "We propose Data -eficient CBMs (DCBMs), which reduce the need for large sample sizes during concept gener-ation while preserving interpretability. DCBMs define concepts as image regions detected by seg-mentation or detection foundation models , allow-ing each image to generate multiple concepts across different granularities."}
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| 4 |
+
{"idx": 3, "title": "DCBM: Data-Efficient Visual Concept Bottleneck Models :: MPG.PuRe", "date": "", "ddg_snippet": "Author: Prasse, Katharina et al.; Genre: Paper ; Published online: 2025; Open Access; Keywords: Computer Science, Computer Vision and Pattern Recognition, cs.CV; Title: DCBM : Data-Efficient Visual Concept Bottleneck Models", "subpage_snippet": "", "source": "pure.mpg.de", "link": "https://pure.mpg.de/pubman/faces/ViewItemFullPage.jsp?itemId=item_3636912_1&view=ACTIONS", "content": "Author: Prasse, Katharina et al.; Genre: Paper ; Published online: 2025; Open Access; Keywords: Computer Science, Computer Vision and Pattern Recognition, cs.CV; Title: DCBM : Data-Efficient Visual Concept Bottleneck Models"}
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| 5 |
+
{"idx": 4, "title": "[2007.04612] Concept Bottleneck Models - arXiv.org ICML DCBM: Data-Efficient Visual Concept Bottleneck Models GitHub - deepopo/DCBM", "date": "", "ddg_snippet": "Jul 9, 2020 · On x-ray grading and bird identification, concept bottleneck models achieve competitive accuracy with standard end-to-end models , while enabling interpretation in terms of high-level clinical concepts (\"bone spurs\") or bird attributes (\"wing color\"). Poster in Workshop: Actionable Interpretability DCBM : Data-Efficient Visual Concept Bottleneck Models Katharina Prasse · Patrick Knab · Sascha Marton · Christian Bartelt · Margret Keuper This is an implementation of the IEEE TPAMI paper The Decoupling Concept Bottleneck Model ( DCBM ). The vision-language- model (VLM) part is being refined and will be available soon. Figure 1: DCBM Pipeline. (A) DCBM for prediction and interpretation. (B) DCBM for human-machine interaction, including forward intervention and backward rectification.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2007.04612", "content": "Jul 9, 2020 · On x-ray grading and bird identification, concept bottleneck models achieve competitive accuracy with standard end-to-end models , while enabling interpretation in terms of high-level clinical concepts (\"bone spurs\") or bird attributes (\"wing color\"). Poster in Workshop: Actionable Interpretability DCBM : Data-Efficient Visual Concept Bottleneck Models Katharina Prasse · Patrick Knab · Sascha Marton · Christian Bartelt · Margret Keuper This is an implementation of the IEEE TPAMI paper The Decoupling Concept Bottleneck Model ( DCBM ). The vision-language- model (VLM) part is being refined and will be available soon. Figure 1: DCBM Pipeline. (A) DCBM for prediction and interpretation. (B) DCBM for human-machine interaction, including forward intervention and backward rectification."}
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| 6 |
+
{"idx": 5, "title": "ICML DCBM: Data-Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "Poster in Workshop: Actionable Interpretability DCBM : Data-Efficient Visual Concept Bottleneck Models Katharina Prasse · Patrick Knab · Sascha Marton · Christian Bartelt · Margret Keuper", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/49558", "content": "Poster in Workshop: Actionable Interpretability DCBM : Data-Efficient Visual Concept Bottleneck Models Katharina Prasse · Patrick Knab · Sascha Marton · Christian Bartelt · Margret Keuper"}
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| 7 |
+
{"idx": 6, "title": "DCBM : Data - Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "DCBM is highly data - efficient in the concept generation phase and equally efficient as other models in the CBM training phase. In Table 5 we show the differences to another data-driven CBM, i.e., DN-CBM (Rao et al., 2024).", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2412.11576", "content": "DCBM is highly data - efficient in the concept generation phase and equally efficient as other models in the CBM training phase. In Table 5 we show the differences to another data-driven CBM, i.e., DN-CBM (Rao et al., 2024)."}
|
| 8 |
+
{"idx": 7, "title": "DCBM : Data - Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "We propose Data - efficient CBMs (DCBMs), which reduce the need for large sample sizes during concept generation while preserving interpretability.", "subpage_snippet": "", "source": "synthical.com", "link": "https://synthical.com/article/DCBM:-Data-Efficient-Visual-Concept-Bottleneck-Models-4be352f8-e37e-432a-9849-dc4f3c8c586f", "content": "We propose Data - efficient CBMs (DCBMs), which reduce the need for large sample sizes during concept generation while preserving interpretability."}
|
| 9 |
+
{"idx": 8, "title": "ICML Poster DCBM : Data - Efficient Visual Concept Bottleneck Models", "date": "", "ddg_snippet": "Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts .", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46104", "content": "Concept Bottleneck Models (CBMs) enhance the interpretability of neural networks by basing predictions on human-understandable concepts ."}
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| 10 |
+
{"idx": 9, "title": "DWS Area: Web Data Mining, Research | Universität Mannheim", "date": "", "ddg_snippet": "DCBM : Data - Efficient Visual Concept Bottleneck Models .", "subpage_snippet": "", "source": "www.uni-mannheim.de", "link": "https://www.uni-mannheim.de/dws/news-archiv/dws-area-web-data-mining-research/?tx_news_pi1[@widget_0][currentPage]=2&cHash=dbf1436b0d93f36eda0040b2d5b33144", "content": "DCBM : Data - Efficient Visual Concept Bottleneck Models ."}
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