Add files using upload-large-folder tool

data/sampled_jsons/'Section_5.1'_'fine-tuning_on_high-quality_demonstrations'_'close_to_the_ceiling'_password-locked_mo_year_2024.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Smart Home Automationva - The Ultimate Smart Home Guide", "date": "", "ddg_snippet": "They then adjust the temperature to the ... Read the instruction manual carefully to understand the signs and symbols that will appear on the screen.", "subpage_snippet": "", "source": "smarthomeautomationva.com", "link": "https://smarthomeautomationva.com/", "content": "They then adjust the temperature to the ... Read the instruction manual carefully to understand the signs and symbols that will appear on the screen."}
+{"idx": 1, "title": "When does capability elicitation bound risk? — AI Alignment", "date": "", "ddg_snippet": "... model evaluations?” cites “gradient hacking” (strategically interfering with the learning process) as the main reason supervised fine - tuning ...", "subpage_snippet": "", "source": "www.alignmentforum.org", "link": "https://www.alignmentforum.org/posts/u3taQsgxqCzrgErMM/when-does-capability-elicitation-bound-risk", "content": "... model evaluations?” cites “gradient hacking” (strategically interfering with the learning process) as the main reason supervised fine - tuning ..."}
+{"idx": 2, "title": "When does capability elicitation bound risk? — LessWrong", "date": "", "ddg_snippet": "... model evaluations?” cites “gradient hacking” (strategically interfering with the learning process) as the main reason supervised fine - tuning ...", "subpage_snippet": "", "source": "www.lesswrong.com", "link": "https://www.lesswrong.com/posts/u3taQsgxqCzrgErMM/when-does-capability-elicitation-bound-risk", "content": "... model evaluations?” cites “gradient hacking” (strategically interfering with the learning process) as the main reason supervised fine - tuning ..."}
+{"idx": 3, "title": "When does capability elicitation bound risk? - LessWrong 2.0", "date": "", "ddg_snippet": "... model evaluations?” cites “gradient hacking” (strategically interfering with the learning process) as the main reason supervised fine - tuning ...", "subpage_snippet": "", "source": "www.greaterwrong.com", "link": "https://www.greaterwrong.com/posts/u3taQsgxqCzrgErMM/when-does-capability-elicitation-bound-risk", "content": "... model evaluations?” cites “gradient hacking” (strategically interfering with the learning process) as the main reason supervised fine - tuning ..."}
+{"idx": 4, "title": "Formulate linear programming model Jobs, Employment | Freelancer", "date": "", "ddg_snippet": "... High -resolution PDF proof • Mock-up image showing front and back views Once approved, I ’ ll hand the files directly to our lanyard ...", "subpage_snippet": "", "source": "www.freelancer.ie", "link": "https://www.freelancer.ie/job-search/formulate-linear-programming-model/5/", "content": "... High -resolution PDF proof • Mock-up image showing front and back views Once approved, I ’ ll hand the files directly to our lanyard ..."}
+{"idx": 5, "title": "Histopathology Products Manufacturer,Supplier,Exporter, Ambala", "date": "", "ddg_snippet": "Covid-19 Products ... ConXport Oxygen Cylinder Aluminium 1 Ltr. ... ConXport Fine Adjustment Valve Rota Meter and Humidifier Bottle", "subpage_snippet": "", "source": "www.hospitalsequipments.com", "link": "https://www.hospitalsequipments.com/histopathology-products.html", "content": "Covid-19 Products ... ConXport Oxygen Cylinder Aluminium 1 Ltr. ... ConXport Fine Adjustment Valve Rota Meter and Humidifier Bottle"}
+{"idx": 6, "title": "Rotary Microtomespencer Manufacturer,Supplier,Exporter", "date": "", "ddg_snippet": "Covid-19 Products ... ConXport Oxygen Cylinder Aluminium 1 Ltr. ... ConXport Fine Adjustment Valve Rota Meter and Humidifier Bottle", "subpage_snippet": "", "source": "www.hospitalsequipments.com", "link": "https://www.hospitalsequipments.com/rotary-microtomespencer-6965461.html", "content": "Covid-19 Products ... ConXport Oxygen Cylinder Aluminium 1 Ltr. ... ConXport Fine Adjustment Valve Rota Meter and Humidifier Bottle"}
+{"idx": 7, "title": "Private Cheats | Semi-Rage, Legacy, ESP – Health &", "date": "", "ddg_snippet": "Independent Learners in Year 5 :: Thursday, October 16, Year 5 students were independent learners this week as they demonstrated their inquiry skills ...", "subpage_snippet": "", "source": "fitstopxp.com", "link": "http://fitstopxp.com/2023/02/25/private-cheats-semi-rage-legacy-esp/", "content": "Independent Learners in Year 5 :: Thursday, October 16, Year 5 students were independent learners this week as they demonstrated their inquiry skills ..."}
+{"idx": 8, "title": "An Approach to Technical AGI Safety and Security", "date": "", "ddg_snippet": "It is especially important to have broader consensus on appropriate standards and best practices, to prevent a potential race to the bottom on safety ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.01849v1", "content": "It is especially important to have broader consensus on appropriate standards and best practices, to prevent a potential race to the bottom on safety ..."}
+{"idx": 9, "title": "Mountain Biking - a how-to community for mountain bikers of all", "date": "", "ddg_snippet": "Once you test out a bike that closely fits you, you can fine tune the bike to fit your body exactly. Once you get on your bike, you need to get ...", "subpage_snippet": "", "source": "mountain-bike.wonderhowto.com", "link": "https://mountain-bike.wonderhowto.com/", "content": "Once you test out a bike that closely fits you, you can fine tune the bike to fit your body exactly. Once you get on your bike, you need to get ..."}

data/sampled_jsons/0A4Y9qRnu9_Leveraging_Per-Instance_Privacy_for_Machine_Unlearning_SGLD_noise_tensor_shape.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Grand Canyon Education, Inc . ( LOPE) Stock Price, News, Quote &...", "date": "", "ddg_snippet": "Find the latest Grand Canyon Education, Inc . ( LOPE) stock quote, history, news and other vital information to help you with your stock trading and investing.", "subpage_snippet": "", "source": "finance.yahoo.com", "link": "https://finance.yahoo.com/quote/LOPE/?fr=sycsrp_catchall", "content": "Find the latest Grand Canyon Education, Inc . ( LOPE) stock quote, history, news and other vital information to help you with your stock trading and investing."}
+{"idx": 1, "title": "LOPE $209.17 ( 0.17%) Grand Canyon Education Inc | Google Finance", "date": "", "ddg_snippet": "Get the latest Grand Canyon Education Inc ( LOPE ) real-time quote, historical performance, charts, and other financial information to help you make more informed trading and investment decisions.", "subpage_snippet": "", "source": "www.google.com", "link": "https://www.google.com/finance/quote/LOPE:NASDAQ", "content": "Get the latest Grand Canyon Education Inc ( LOPE ) real-time quote, historical performance, charts, and other financial information to help you make more informed trading and investment decisions."}
+{"idx": 2, "title": "LOPE Stock Price | Grand Canyon Education Inc . Stock Quote (U.S...", "date": "", "ddg_snippet": "6 days ago · LOPE | Complete Grand Canyon Education Inc . stock news by MarketWatch . View real-time stock prices and stock quotes for a full financial overview.", "subpage_snippet": "", "source": "www.marketwatch.com", "link": "https://www.marketwatch.com/investing/stock/LOPE", "content": "6 days ago · LOPE | Complete Grand Canyon Education Inc . stock news by MarketWatch . View real-time stock prices and stock quotes for a full financial overview."}
+{"idx": 3, "title": "Grand Canyon Education - LOPE - Stock Price Today - Zacks", "date": "", "ddg_snippet": "6 days ago · View Grand Canyon Education, Inc LOPE investment & stock information. Get the latest Grand Canyon Education, Inc LOPE detailed stock quotes, stock data, Real-Time ECN, charts, stats and more.", "subpage_snippet": "", "source": "www.zacks.com", "link": "https://www.zacks.com/stock/quote/LOPE", "content": "6 days ago · View Grand Canyon Education, Inc LOPE investment & stock information. Get the latest Grand Canyon Education, Inc LOPE detailed stock quotes, stock data, Real-Time ECN, charts, stats and more."}
+{"idx": 4, "title": "LOPE | Grand Canyon Education Inc . Stock Overview (U.S.: Nasdaq...", "date": "", "ddg_snippet": "Sep 17, 2025 · Complete Grand Canyon Education Inc . stock information by Barron's. View real-time LOPE stock price and news, along with industry-best analysis.", "subpage_snippet": "", "source": "www.barrons.com", "link": "https://www.barrons.com/market-data/stocks/lope", "content": "Sep 17, 2025 · Complete Grand Canyon Education Inc . stock information by Barron's. View real-time LOPE stock price and news, along with industry-best analysis."}
+{"idx": 5, "title": "LOPE : Grand Canyon Education Inc - Stock Price, Quote and News - ...", "date": "", "ddg_snippet": "Get Grand Canyon Education Inc ( LOPE :NASDAQ) real-time stock quotes, news, price and financial information from CNBC .", "subpage_snippet": "", "source": "www.cnbc.com", "link": "https://www.cnbc.com/quotes/LOPE", "content": "Get Grand Canyon Education Inc ( LOPE :NASDAQ) real-time stock quotes, news, price and financial information from CNBC ."}
+{"idx": 6, "title": "Grand Canyon Education ( LOPE) Stock Price & Overview", "date": "", "ddg_snippet": "6 days ago · A detailed overview of Grand Canyon Education, Inc. (LOPE) stock , including real-time price, chart, key statistics, news, and more.", "subpage_snippet": "", "source": "stockanalysis.com", "link": "https://stockanalysis.com/stocks/lope/", "content": "6 days ago · A detailed overview of Grand Canyon Education, Inc. (LOPE) stock , including real-time price, chart, key statistics, news, and more."}
+{"idx": 7, "title": "Grand Canyon Education ( LOPE) Stock Price, News & Analysis", "date": "", "ddg_snippet": "6 days ago · Should You Buy or Sell Grand Canyon Education Stock ? Get The Latest LOPE Stock Analysis, Price Target, Earnings Estimates, Headlines, and Short Interest at MarketBeat.", "subpage_snippet": "", "source": "www.marketbeat.com", "link": "https://www.marketbeat.com/stocks/NASDAQ/LOPE/", "content": "6 days ago · Should You Buy or Sell Grand Canyon Education Stock ? Get The Latest LOPE Stock Analysis, Price Target, Earnings Estimates, Headlines, and Short Interest at MarketBeat."}
+{"idx": 8, "title": "LOPE Stock Price Quote | Morningstar", "date": "", "ddg_snippet": "6 days ago · See the latest Grand Canyon Education Inc stock price ( LOPE :XNAS), related news, valuation, dividends and more to help you make your investing decisions.", "subpage_snippet": "", "source": "www.morningstar.com", "link": "https://www.morningstar.com/stocks/XNAS/LOPE/quote", "content": "6 days ago · See the latest Grand Canyon Education Inc stock price ( LOPE :XNAS), related news, valuation, dividends and more to help you make your investing decisions."}
+{"idx": 9, "title": "Grand Canyon Education Stock Price | LOPE Stock Quote, News, and...", "date": "", "ddg_snippet": "Aug 29, 2025 · The latest Grand Canyon Education stock prices, stock quotes, news, and LOPE history to help you invest and trade smarter.", "subpage_snippet": "", "source": "markets.businessinsider.com", "link": "https://markets.businessinsider.com/stocks/lope-stock", "content": "Aug 29, 2025 · The latest Grand Canyon Education stock prices, stock quotes, news, and LOPE history to help you invest and trade smarter."}

data/sampled_jsons/0hrkN07DuO_Linear_convergence_Sinkhorn_generalized_Schrödinger_bridge_tameness_condition.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Schrödinger equation - Wikipedia", "date": "", "ddg_snippet": "Conceptually, the Schrödinger equation is the quantum counterpart of Newton's second law in classical mechanics. Given a set of known initial conditions , Newton's second law makes a mathematical prediction as to what path a given physical system will take over time.", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Schrödinger_equation", "content": "Conceptually, the Schrödinger equation is the quantum counterpart of Newton's second law in classical mechanics. Given a set of known initial conditions , Newton's second law makes a mathematical prediction as to what path a given physical system will take over time."}
+{"idx": 1, "title": "ICML Poster Linear convergence of Sinkhorn 's algorithm for...", "date": "", "ddg_snippet": "We establish Kantorovich duality and linear convergence of Sinkhorn 's algorithm for the generalized SSB problem under mild conditions .", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46671", "content": "We establish Kantorovich duality and linear convergence of Sinkhorn 's algorithm for the generalized SSB problem under mild conditions ."}
+{"idx": 2, "title": "(PDF) An Optimal Transport Approach for the Schrödinger Bridge ...", "date": "", "ddg_snippet": "Bridge problem, including convergence of Sinkhorn algorithm in the multi-marginal case.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/345547115_An_Optimal_Transport_Approach_for_the_Schrodinger_Bridge_Problem_and_Convergence_of_Sinkhorn_Algorithm", "content": "Bridge problem, including convergence of Sinkhorn algorithm in the multi-marginal case."}
+{"idx": 3, "title": "Large random matrices with given margins, Schrödinger bridge , and...", "date": "", "ddg_snippet": "⇐ For Schrödinger bridge (µ = Poisson(1)), use exact form of Sinkhorn updates For general µ, no exact form of Sinkhorn updates (implicit). Hanbaek Lyu. Large random matrices with given margins.", "subpage_snippet": "", "source": "hanbaeklyu.com", "link": "https://hanbaeklyu.com/wp-content/uploads/2024/10/ct_limit_kaist_col.pdf", "content": "⇐ For Schrödinger bridge (µ = Poisson(1)), use exact form of Sinkhorn updates For general µ, no exact form of Sinkhorn updates (implicit). Hanbaek Lyu. Large random matrices with given margins."}
+{"idx": 4, "title": "A Differential Approach to the Multi-Marginal Schrödinger System", "date": "", "ddg_snippet": "Stability of Schrödinger potentials and convergence of Sinkhorn ’s algorithm.The aim of this note is to give an elementary proof of linear convergence of the Sinkhorn algorithm for the entropic regularization of multimarginal optimal transport in the setting of general probability spaces.", "subpage_snippet": "", "source": "epubs.siam.org", "link": "https://epubs.siam.org/doi/abs/10.1137/19M1253800", "content": "Stability of Schrödinger potentials and convergence of Sinkhorn ’s algorithm.The aim of this note is to give an elementary proof of linear convergence of the Sinkhorn algorithm for the entropic regularization of multimarginal optimal transport in the setting of general probability spaces."}
+{"idx": 5, "title": "The Sinkhorn Knopp Algorithm — Without Proof | by Frank... | Medium", "date": "", "ddg_snippet": "I've recently come across various mentions of the Sinkhorn Knopp algorithm. It deals with scaling the rows and columns of a non-negative matrix A such that its rows and columns all sum to 1 (i.e. it is doubly-stochastic).", "subpage_snippet": "", "source": "fulkast.medium.com", "link": "https://fulkast.medium.com/the-sinkhorn-knopp-algorithm-without-proof-697c9af7df7", "content": "I've recently come across various mentions of the Sinkhorn Knopp algorithm. It deals with scaling the rows and columns of a non-negative matrix A such that its rows and columns all sum to 1 (i.e. it is doubly-stochastic)."}
+{"idx": 6, "title": "Network Learning with Directional", "date": "", "ddg_snippet": "Sinkhorn with Directional Sign Templates. General Higher-order Networks.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2403.14915.pdf", "content": "Sinkhorn with Directional Sign Templates. General Higher-order Networks."}
+{"idx": 7, "title": "Charlie Yan MS Thesis", "date": "", "ddg_snippet": "Neural Schrödinger Bridge with Sinkhorn Losses. Charlie Yan.", "subpage_snippet": "", "source": "abhishekhalder.org", "link": "https://abhishekhalder.org/Charlie_Yan_UCSC_MS_Thesis_Slides_05182023.pdf", "content": "Neural Schrödinger Bridge with Sinkhorn Losses. Charlie Yan."}
+{"idx": 8, "title": "(PDF) Partial minimization of strict convex functions and tensor scaling", "date": "", "ddg_snippet": "We provide global convergence analysis for a general scheme admitting inexactness in solving the auxiliary subproblem. In the case of using for this purpose high-order tensor methods, we demonstrate an acceleration effect for both convex and uniformly convex composite objective functions.", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/128044855/Partial_minimization_of_strict_convex_functions_and_tensor_scaling", "content": "We provide global convergence analysis for a general scheme admitting inexactness in solving the auxiliary subproblem. In the case of using for this purpose high-order tensor methods, we demonstrate an acceleration effect for both convex and uniformly convex composite objective functions."}
+{"idx": 9, "title": "Unbalanced Optimal Transport: Models, Numerical Methods, Applications", "date": "", "ddg_snippet": "parameter θopt computed from the linear convergence rate of Sinkhorn ’s iterations. Stopping criterion is u(ℓ) − uopt ∞ < 2 × 10−6 (except for the last line where the tolerance is 10−8).", "subpage_snippet": "", "source": "theses.hal.science", "link": "https://theses.hal.science/tel-01881166/document", "content": "parameter θopt computed from the linear convergence rate of Sinkhorn ’s iterations. Stopping criterion is u(ℓ) − uopt ∞ < 2 × 10−6 (except for the last line where the tolerance is 10−8)."}

data/sampled_jsons/0yzOEMbShU_Section_4.5_LRU_cache_Equation_15_visit_frequency_approximation.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "146. LRU Cache - In-Depth Explanation - AlgoMonster", "date": "", "ddg_snippet": "In-depth solution and explanation for LeetCode 146. LRU Cache in Python, Java, C++ and more. Intuitions, example walk through, and complexity analysis. Better than official and forum solutions.", "subpage_snippet": "", "source": "algo.monster", "link": "https://algo.monster/liteproblems/146", "content": "In-depth solution and explanation for LeetCode 146. LRU Cache in Python, Java, C++ and more. Intuitions, example walk through, and complexity analysis. Better than official and forum solutions."}
+{"idx": 1, "title": "LRU Cache - Complete Tutorial - GeeksforGeeks", "date": "", "ddg_snippet": "Jul 23, 2025 · Please refer LRU cache implementation using Doubly Linked List and Hashing for details Complexity Analysis of the Efficient Solution Time Complexity: put () operation: O (1) i.e. time required to insert or update new key-value pair is constant get () operation: O (1) i.e. time required to get the value of a key is constant Auxiliary Space: O (c) where c is the capacity of the Cache . Advantages ...", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/system-design/lru-cache-implementation/", "content": "Jul 23, 2025 · Please refer LRU cache implementation using Doubly Linked List and Hashing for details Complexity Analysis of the Efficient Solution Time Complexity: put () operation: O (1) i.e. time required to insert or update new key-value pair is constant get () operation: O (1) i.e. time required to get the value of a key is constant Auxiliary Space: O (c) where c is the capacity of the Cache . Advantages ..."}
+{"idx": 2, "title": "LRU Cache - LeetCode", "date": "", "ddg_snippet": "Implement the LRUCache class: * LRUCache (int capacity) Initialize the LRU cache with positive size capacity. * int get (int key) Return the value of the key if the key exists, otherwise return -1. * void put (int key, int value) Update the value of the key if the key exists. Otherwise, add the key-value pair to the cache .", "subpage_snippet": "", "source": "leetcode.com", "link": "https://leetcode.com/problems/lru-cache/", "content": "Implement the LRUCache class: * LRUCache (int capacity) Initialize the LRU cache with positive size capacity. * int get (int key) Return the value of the key if the key exists, otherwise return -1. * void put (int key, int value) Update the value of the key if the key exists. Otherwise, add the key-value pair to the cache ."}
+{"idx": 3, "title": "Introduction to LRU and LFU Caching Concepts ... - Alex K", "date": "", "ddg_snippet": "Understanding LRU and LFU Caching: Exploring Concepts, Implementations, and Real-World Applications Caching is a fundamental technique used to improve the performance and efficiency of computer systems by storing frequently accessed data in a readily accessible location.", "subpage_snippet": "", "source": "alxkm.github.io", "link": "https://alxkm.github.io/posts/introduction_to_lru_and_lfu_caching_concepts_implementations_and_practical_use_cases/", "content": "Understanding LRU and LFU Caching: Exploring Concepts, Implementations, and Real-World Applications Caching is a fundamental technique used to improve the performance and efficiency of computer systems by storing frequently accessed data in a readily accessible location."}
+{"idx": 4, "title": "Least Recently Used (LRU) Revealed: Cracking the Cache Code ...", "date": "", "ddg_snippet": "Jul 30, 2023 · The LRU algorithm is a clever technique used in cache management systems to maintain a balance between memory usage and performance. Its central principle is simple but incredibly effective ...", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@mohith.j/least-recently-used-lru-revealed-cracking-the-cache-code-for-optimal-performance-c007d74110aa", "content": "Jul 30, 2023 · The LRU algorithm is a clever technique used in cache management systems to maintain a balance between memory usage and performance. Its central principle is simple but incredibly effective ..."}
+{"idx": 5, "title": "Solving-the-LRU-Cache-Problem-in-C---LeetCode-146/f ... - GitHub", "date": "", "ddg_snippet": "A comprehensive solution for the LeetCode problem 146: LRU Cache , implemented in C. This repository includes a detailed explanation of the Least Recently Used ( LRU ) Cache concept and a step-by-step guide to implementing it efficiently.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/MustcodeQ/Solving-the-LRU-Cache-Problem-in-C---LeetCode-146/blob/master/f_LRU_Cache.c", "content": "A comprehensive solution for the LeetCode problem 146: LRU Cache , implemented in C. This repository includes a detailed explanation of the Least Recently Used ( LRU ) Cache concept and a step-by-step guide to implementing it efficiently."}
+{"idx": 6, "title": "LRU , метод вытеснения из кэша / Хабр", "date": "", "ddg_snippet": "Поэтому я решил написать небольшую статью, где расс��ажу как быстро реализовать метод LRU , и не вынуждать коллег вручную сбрасывать кэш там, где не требуется.", "subpage_snippet": "", "source": "habr.com", "link": "https://habr.com/ru/articles/136758/", "content": "Поэтому я решил написать небольшую статью, где расскажу как быстро реализовать метод LRU , и не вынуждать коллег вручную сбрасывать кэш там, где не требуется."}
+{"idx": 7, "title": "lru - cache - npm", "date": "", "ddg_snippet": "Start using lru - cache in your project by running `npm i lru - cache `.However, note that using some of the features will necessarily impact performance, by causing the cache to have to do more work. See the \"Performance\" section below. Installation. npm install lru - cache --save. Usage.", "subpage_snippet": "", "source": "www.npmjs.com", "link": "https://www.npmjs.com/package/lru-cache", "content": "Start using lru - cache in your project by running `npm i lru - cache `.However, note that using some of the features will necessarily impact performance, by causing the cache to have to do more work. See the \"Performance\" section below. Installation. npm install lru - cache --save. Usage."}
+{"idx": 8, "title": "Как предотвратить повторное вычисление функции с lru _ cache", "date": "", "ddg_snippet": "Используйте lru _ cache (functools) в качестве кэша в коде на Python для того, чтобы сохранить промежуточные результаты функции.Как работает Least Recently Used ( LRU ) алгоритм. Параметры функции lru _ cache .", "subpage_snippet": "", "source": "python-school.ru", "link": "https://python-school.ru/blog/python/lru_cache/", "content": "Используйте lru _ cache (functools) в качестве кэша в коде на Python для того, чтобы сохранить промежуточные результаты функции.Как работает Least Recently Used ( LRU ) алгоритм. Параметры функции lru _ cache ."}
+{"idx": 9, "title": "TOMPECS0304-20 - SJTU", "date": "", "ddg_snippet": "The modeling and analysis of an LRU cache is extremely challenging as exact results for the main performance metrics (e.g., hit rate) are either lacking or cannot be used because of their high computational complexity for large caches. As a result, various approximations have been proposed. The state-of-the-art method is the so-called TTL approximation , first proposed and shown to be ...", "subpage_snippet": "", "source": "jhc.sjtu.edu.cn", "link": "https://jhc.sjtu.edu.cn/~bjiang/papers/Jiang_ToMPECS2018_TTL.pdf", "content": "The modeling and analysis of an LRU cache is extremely challenging as exact results for the main performance metrics (e.g., hit rate) are either lacking or cannot be used because of their high computational complexity for large caches. As a result, various approximations have been proposed. The state-of-the-art method is the so-called TTL approximation , first proposed and shown to be ..."}

data/sampled_jsons/1IyPRv1A0r_A_Likelihood_Based_Approach_Distribution_Regression_MNIST_Wasserstein.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Likelihood Based Approach to Distribution Regression Using ...", "date": "", "ddg_snippet": "To the best of our knowledge, our study is the first at-tempt to explore the likelihood-based approach for distri-butional regression using a conditional deep generative model, considering full-dimensional noise and the poten-tial presence of singular underlying support.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=1IyPRv1A0r", "content": "To the best of our knowledge, our study is the first at-tempt to explore the likelihood-based approach for distri-butional regression using a conditional deep generative model, considering full-dimensional noise and the poten-tial presence of singular underlying support."}
+{"idx": 1, "title": "A Likelihood-Based Approach for Multivariate Categorical Response ...", "date": "", "ddg_snippet": "We propose a penalized likelihood method to fit the bivariate categorical response regression model. Our method allows practitioners to estimate which predictors are irrelevant, which predictors only affect the marginal distributions of the bivariate response, and which predictors affect both the marginal distributions and log odds ratios.", "subpage_snippet": "", "source": "www.tandfonline.com", "link": "https://www.tandfonline.com/doi/full/10.1080/01621459.2021.1999819", "content": "We propose a penalized likelihood method to fit the bivariate categorical response regression model. Our method allows practitioners to estimate which predictors are irrelevant, which predictors only affect the marginal distributions of the bivariate response, and which predictors affect both the marginal distributions and log odds ratios."}
+{"idx": 2, "title": "Chapter2: Likelihood-based approach | PDF | Web Development - SlideShare", "date": "", "ddg_snippet": "This document summarizes key concepts from Chapter 2 of a book on statistical methods for handling incomplete data. It introduces the likelihood-based approach and defines key terms like the likelihood function, maximum likelihood estimator, Fisher information, and missing at random. The chapter also provides examples of observed likelihood functions for censored regression and survival ...", "subpage_snippet": "", "source": "www.slideshare.net", "link": "https://www.slideshare.net/slideshow/chapter2-likelihoodbased-approach/86416477", "content": "This document summarizes key concepts from Chapter 2 of a book on statistical methods for handling incomplete data. It introduces the likelihood-based approach and defines key terms like the likelihood function, maximum likelihood estimator, Fisher information, and missing at random. The chapter also provides examples of observed likelihood functions for censored regression and survival ..."}
+{"idx": 3, "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 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": "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 ..."}
+{"idx": 4, "title": "PDF Wasserstein Clustering", "date": "", "ddg_snippet": "First, the goal of the likelihood-based approach is to minimize the Kullback-Leibler divergence between the original data distribution and the parametrized model data distribution (which is equivalent to maximizing the likelihood Duda et al. [2012]).", "subpage_snippet": "", "source": "harchaoui.org", "link": "https://harchaoui.org/warith/phd/wasserstein-clustering-phd-warith-harchaoui.pdf", "content": "First, the goal of the likelihood-based approach is to minimize the Kullback-Leibler divergence between the original data distribution and the parametrized model data distribution (which is equivalent to maximizing the likelihood Duda et al. [2012])."}
+{"idx": 5, "title": "A generalized likelihood-based Bayesian approach for scalable joint ...", "date": "", "ddg_snippet": "Using a bi-convex regression based generalized likelihood and spike-and-slab priors, we develop an algorithm called Joint Regression Network Selector (JRNS) for joint regression and covariance selection which (a) can accommodate general sparsity patterns, (b) provides posterior samples for uncertainty quantification, and (c) is scalable and ...", "subpage_snippet": "", "source": "pubmed.ncbi.nlm.nih.gov", "link": "https://pubmed.ncbi.nlm.nih.gov/36713060/", "content": "Using a bi-convex regression based generalized likelihood and spike-and-slab priors, we develop an algorithm called Joint Regression Network Selector (JRNS) for joint regression and covariance selection which (a) can accommodate general sparsity patterns, (b) provides posterior samples for uncertainty quantification, and (c) is scalable and ..."}
+{"idx": 6, "title": "A Likelihood Based Approach to Distribution Regression Using...", "date": "", "ddg_snippet": "More specifically, we study the large-sample properties of a likelihood-based approach for estimating these models. Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart) of the response given predictors in the Hellinger ( Wasserstein ) metric.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=1IyPRv1A0r", "content": "More specifically, we study the large-sample properties of a likelihood-based approach for estimating these models. Our results lead to the convergence rate of a sieve maximum likelihood estimator (MLE) for estimating the conditional distribution (and its devolved counterpart) of the response given predictors in the Hellinger ( Wasserstein ) metric."}
+{"idx": 7, "title": "Distribution Regression with Sliced Wasserstein Kernels", "date": "", "ddg_snippet": "In this work, we propose an OT- based estimator for distribution regression . We build on the Sliced Wasserstein distance to obtain an OT- based representation. We study the theoretical properties of a kernel ridge regression estimator based on such representation, for which we prove universal consistency and excess risk bounds.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2202.03926", "content": "In this work, we propose an OT- based estimator for distribution regression . We build on the Sliced Wasserstein distance to obtain an OT- based representation. We study the theoretical properties of a kernel ridge regression estimator based on such representation, for which we prove universal consistency and excess risk bounds."}
+{"idx": 8, "title": "PDF A Likelihood Approach to Nonparametric Estimation of a Singular ...", "date": "", "ddg_snippet": "We investigate statistical properties of a likelihood approach to nonparametric estimation of a singular distribution using deep generative models. More speci cally, a deep generative model is used to model high-dimensional data that are assumed to concentrate around some low-dimensional structure.", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume24/21-1099/21-1099.pdf", "content": "We investigate statistical properties of a likelihood approach to nonparametric estimation of a singular distribution using deep generative models. More speci cally, a deep generative model is used to model high-dimensional data that are assumed to concentrate around some low-dimensional structure."}
+{"idx": 9, "title": "arXiv:2410.02025v1 [math.ST] 2 Oct 2024", "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 response variable lies in a high-dimensional am-bient 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/pdf/2410.02025", "content": "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 am-bient 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 ..."}

data/sampled_jsons/2403.09040_RAGGED_retriever_paradigms.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Greenhouse gases emissions and global climate change: Examining...", "date": "", "ddg_snippet": "Jul 20, 2024 · The increase in GHG concentrations as a result of human activity enhances the greenhouse effect, leading to global warming . This process influences the climate, causing changes in weather patterns, sea levels, and other aspects of the environment.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S004896972403506X", "content": "Jul 20, 2024 · The increase in GHG concentrations as a result of human activity enhances the greenhouse effect, leading to global warming . This process influences the climate, causing changes in weather patterns, sea levels, and other aspects of the environment."}
+{"idx": 1, "title": "Climate change: atmospheric carbon dioxide - NOAA Climate.gov", "date": "", "ddg_snippet": "May 21, 2025 · Without any carbon dioxide, Earth’s natural greenhouse effect would be too weak to keep the average global surface temperature above freezing. By adding more carbon dioxide to the atmosphere, people are amplifying the natural greenhouse effect, causing global temperature to rise .", "subpage_snippet": "", "source": "www.climate.gov", "link": "https://www.climate.gov/news-features/understanding-climate/climate-change-atmospheric-carbon-dioxide", "content": "May 21, 2025 · Without any carbon dioxide, Earth’s natural greenhouse effect would be too weak to keep the average global surface temperature above freezing. By adding more carbon dioxide to the atmosphere, people are amplifying the natural greenhouse effect, causing global temperature to rise ."}
+{"idx": 2, "title": "Greenhouse gases surged to new highs in 2023, warns UN ... - UN...", "date": "", "ddg_snippet": "Oct 28, 2024 · Key greenhouse gas -producing events include forest fires and the El Niño weather phenomenon which fuelled drier conditions and a “ surge ” in gas concentrations in the latter part of 2023,...", "subpage_snippet": "", "source": "news.un.org", "link": "https://news.un.org/en/story/2024/10/1156186", "content": "Oct 28, 2024 · Key greenhouse gas -producing events include forest fires and the El Niño weather phenomenon which fuelled drier conditions and a “ surge ” in gas concentrations in the latter part of 2023,..."}
+{"idx": 3, "title": "The world at 60 gigatonnes of greenhouse gas emissions", "date": "", "ddg_snippet": "4 days ago · Global greenhouse gas emissions remain at record highs of around 60 gigatonnes, but updated World Emissions Clock data shows signs of progress.", "subpage_snippet": "", "source": "www.brookings.edu", "link": "https://www.brookings.edu/articles/the-world-at-60-gigatonnes-of-greenhouse-gas-emissions/", "content": "4 days ago · Global greenhouse gas emissions remain at record highs of around 60 gigatonnes, but updated World Emissions Clock data shows signs of progress."}
+{"idx": 4, "title": "Emissions Gap Report 2023 - UNEP - UN Environment Programme", "date": "", "ddg_snippet": "Nov 19, 2023 · The report is the 14th edition in a series that brings together many of the world’s top climate scientists to look at future trends in greenhouse gas emissions and provide potential solutions to the challenge of global warming .", "subpage_snippet": "", "source": "www.unep.org", "link": "https://www.unep.org/resources/emissions-gap-report-2023", "content": "Nov 19, 2023 · The report is the 14th edition in a series that brings together many of the world’s top climate scientists to look at future trends in greenhouse gas emissions and provide potential solutions to the challenge of global warming ."}
+{"idx": 5, "title": "Greenhouse gas concentrations surge again to new record in 2023", "date": "", "ddg_snippet": "1 day ago · Greenhouse gas levels surged to a new record in 2023, committing the planet to rising temperatures for many years to come, according to a report from the World Meteorological Organization (WMO).", "subpage_snippet": "", "source": "wmo.int", "link": "https://wmo.int/news/media-centre/greenhouse-gas-concentrations-surge-again-new-record-2023", "content": "1 day ago · Greenhouse gas levels surged to a new record in 2023, committing the planet to rising temperatures for many years to come, according to a report from the World Meteorological Organization (WMO)."}
+{"idx": 6, "title": "CO2 Emissions – Global Energy Review 2025 – Analysis - IEA", "date": "", "ddg_snippet": "2 days ago · Overall, higher temperatures contributed to increase emissions by 230 Mt CO 2 in 2024 compared with 2023, accounting for around 80% of the total increase in energy-related emissions .", "subpage_snippet": "", "source": "www.iea.org", "link": "https://www.iea.org/reports/global-energy-review-2025/co2-emissions", "content": "2 days ago · Overall, higher temperatures contributed to increase emissions by 230 Mt CO 2 in 2024 compared with 2023, accounting for around 80% of the total increase in energy-related emissions ."}
+{"idx": 7, "title": "CO₂ and Greenhouse Gas Emissions - Our World in Data", "date": "", "ddg_snippet": "Human emissions of carbon dioxide and other greenhouse gases are the primary drivers of the global rise in temperatures .1 This link between global temperatures and greenhouse gas concentrations – especially CO2 – has been true throughout Earth’s history.2", "subpage_snippet": "", "source": "ourworldindata.org", "link": "https://ourworldindata.org/co2-and-greenhouse-gas-emissions", "content": "Human emissions of carbon dioxide and other greenhouse gases are the primary drivers of the global rise in temperatures .1 This link between global temperatures and greenhouse gas concentrations – especially CO2 – has been true throughout Earth’s history.2"}
+{"idx": 8, "title": "Why Are Greenhouse Gas Emissions Increasing?", "date": "", "ddg_snippet": "Aug 14, 2025 · The increasing global impact of greenhouse gas emissions is due to human activities such as burning fossil fuels, cutting down forests, and farming livestock. These activities contribute to the increase in greenhouse gases , which trap heat and make the planet warmer.", "subpage_snippet": "", "source": "climatecontroljournal.com", "link": "https://climatecontroljournal.com/why-are-greenhouse-gas-emissions-increasing.html", "content": "Aug 14, 2025 · The increasing global impact of greenhouse gas emissions is due to human activities such as burning fossil fuels, cutting down forests, and farming livestock. These activities contribute to the increase in greenhouse gases , which trap heat and make the planet warmer."}
+{"idx": 9, "title": "Chapter 2: Emissions trends and drivers - IPCC", "date": "", "ddg_snippet": "Oct 4, 2024 · Globally , GHG emissions continued to rise across all sectors and subsectors; most rapidly in transport and industry (high confidence).", "subpage_snippet": "", "source": "www.ipcc.ch", "link": "https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-2/", "content": "Oct 4, 2024 · Globally , GHG emissions continued to rise across all sectors and subsectors; most rapidly in transport and industry (high confidence)."}

data/sampled_jsons/26JsumCG0z_The_Value_of_Prediction_Identifying_Worst-Off_Equation_2.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "The Value of Prediction in Identifying the Worst - Off", "date": "", "ddg_snippet": "Given a predictor f , a screening budget of α, and a target parameter β, the value of a prediction system is equal to the fraction of the at-risk population that it identifies", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=26JsumCG0z", "content": "Given a predictor f , a screening budget of α, and a target parameter β, the value of a prediction system is equal to the fraction of the at-risk population that it identifies"}
+{"idx": 1, "title": "[Paper Note] The Value of Prediction in Identifying the Worst - Off ...", "date": "", "ddg_snippet": "Through mathematical models and a real-world case study on long-term unemployment amongst German residents, we develop a comprehensive understanding of the relative effectiveness of prediction in surfacing the worst - off .", "subpage_snippet": "", "source": "githubissues.com", "link": "https://githubissues.com/AkihikoWatanabe/paper_notes/2220", "content": "Through mathematical models and a real-world case study on long-term unemployment amongst German residents, we develop a comprehensive understanding of the relative effectiveness of prediction in surfacing the worst - off ."}
+{"idx": 2, "title": "[ICML 2025] The Value of Prediction in Identifying the Worst - Off", "date": "", "ddg_snippet": "Improving Predictions : Enhancing a model's predictive power (measured by R ² ). Expanding Access: Increasing the screening capacity (α), or the proportion of the population that can be evaluated and supported.", "subpage_snippet": "", "source": "arxiviq.substack.com", "link": "https://arxiviq.substack.com/p/icml-2025-the-value-of-prediction", "content": "Improving Predictions : Enhancing a model's predictive power (measured by R ² ). Expanding Access: Increasing the screening capacity (α), or the proportion of the population that can be evaluated and supported."}
+{"idx": 3, "title": "The Value of Prediction in Identifying the Worst - Off Authors: Unai...", "date": "", "ddg_snippet": "Краеугольным камнем методологии статьи является коэффициент «предсказание-доступ» ( Prediction -Access Ratio, PAR) — метрика, предназначенная для количественной оценки компромисса между двумя ключевыми инструментами политики: 1. Улучшение...", "subpage_snippet": "", "source": "vk.com", "link": "https://vk.com/wall49591166_67792", "content": "Краеугольным камнем методологии статьи является коэффициент «предсказание-доступ» ( Prediction -Access Ratio, PAR) — метрика, предназначенная для количественной оценки компромисса между двумя ключевыми инструментами политики: 1. Улучшение..."}
+{"idx": 4, "title": "The number of non-trivial solutions of the system x=y+z=0, x+ 2 y-z=0, 2", "date": "", "ddg_snippet": "The number of real values of a for which the system of equations x+ay−z=0, 2 x−y+az=0,ax+y+ 2 z=0 has a non trivial solution is.", "subpage_snippet": "", "source": "www.doubtnut.com", "link": "https://www.doubtnut.com/qna/95420694", "content": "The number of real values of a for which the system of equations x+ay−z=0, 2 x−y+az=0,ax+y+ 2 z=0 has a non trivial solution is."}
+{"idx": 5, "title": "FC 26 Team of The Week 2 Predictions ! | FUTBIN", "date": "", "ddg_snippet": "FC 26 Predictions . With the power curve supposedly slowing, IFs will likely become a lot more relevant within the game this year. There are plenty to get excited about from TOTW 2 , with the likes of Son, Messi, Coman, Gravenberch, and Militao offering quality all over the pitch!", "subpage_snippet": "", "source": "www.futbin.com", "link": "https://www.futbin.com/news/articles/1610/fc-26-team-of-the-week-2-predictions", "content": "FC 26 Predictions . With the power curve supposedly slowing, IFs will likely become a lot more relevant within the game this year. There are plenty to get excited about from TOTW 2 , with the likes of Son, Messi, Coman, Gravenberch, and Militao offering quality all over the pitch!"}
+{"idx": 6, "title": "The value of k for which the planes `kx+4y+z=0, 4x+ky+ 2 z=0 nd...", "date": "", "ddg_snippet": "asked Feb 26, 2020 in Mathematics by MukundJain (94.7k points). equation -of-plane.", "subpage_snippet": "", "source": "www.sarthaks.com", "link": "https://www.sarthaks.com/1689744/the-value-of-for-which-the-planes-kx-4y-4x-ky-2z-nd-2x-2y-intersect-in-straighat-line-is-1-b-2-c-3-d", "content": "asked Feb 26, 2020 in Mathematics by MukundJain (94.7k points). equation -of-plane."}
+{"idx": 7, "title": "BIG vs. ESC at Exort The Proving Grounds Season 4 | HLTV.org", "date": "", "ddg_snippet": "0.26. BIG.play to gain point to get up in the ranking, 1st monday of every month valve releases new invite lists which TOs use to invite teams, from around ~26th global place you can get into tier 1 events.", "subpage_snippet": "", "source": "www.hltv.org", "link": "https://www.hltv.org/matches/2385825/big-vs-esc-exort-the-proving-grounds-season-4", "content": "0.26. BIG.play to gain point to get up in the ranking, 1st monday of every month valve releases new invite lists which TOs use to invite teams, from around ~26th global place you can get into tier 1 events."}
+{"idx": 8, "title": "Telegram: View @gonzo_ML_podcasts", "date": "", "ddg_snippet": "Авторы разрабатывают коэффициент «предсказание-доступ» ( Prediction -Access Ratio, PAR) — новую метрику, которая количественно определяет относительную пользу для общественного благосостояния от инвестиций в более точные прогнозы по сравнению с...", "subpage_snippet": "", "source": "t.me", "link": "https://t.me/gonzo_ML_podcasts/551", "content": "Авторы разрабатывают коэффициент «предсказание-доступ» ( Prediction -Access Ratio, PAR) — новую метрику, которая количественно определяет относительную пользу для общественного благосостояния от инвестиций в более точные прогнозы по сравнению с..."}
+{"idx": 9, "title": "Fastest way to earn 6,000 season points in FC 26 Ultimate Team...", "date": "", "ddg_snippet": "TOTW Predictions – Team of the Week Predictions .This is the fastest way to unlock packs, rewards, and progress through the new Season Pass on day one. For official details on FC 26 Ultimate Team and the Season Pass, check EA’s official FC 26 page.", "subpage_snippet": "", "source": "futfc.gg", "link": "https://futfc.gg/fastest-way-to-earn-6000-season-points-in-fc-26-ultimate-team/", "content": "TOTW Predictions – Team of the Week Predictions .This is the fastest way to unlock packs, rewards, and progress through the new Season Pass on day one. For official details on FC 26 Ultimate Team and the Season Pass, check EA’s official FC 26 page."}

data/sampled_jsons/27tMzmzDjO_A_Geometric_Approach_to_Personalized_Recommendation_Table_1_dataset_statistics_train_Du_u.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Geometric Approach to Personalized Recommendation with...", "date": "", "ddg_snippet": "Personalized item recommendation typically suffers from data sparsity, which is most often addressed by learning vector representations of users and items via low-rank matrix factorization.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=27tMzmzDjO&referrer=[the+profile+of+Andrew+McCallum](/profile?id=~Andrew_McCallum1)", "content": "Personalized item recommendation typically suffers from data sparsity, which is most often addressed by learning vector representations of users and items via low-rank matrix factorization."}
+{"idx": 1, "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?fileType=csv", "content": "Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More."}
+{"idx": 2, "title": "Sequential Data Augmentation for Generative Recommendation", "date": "", "ddg_snippet": "Generative recommendation plays a crucial role in personalized systems, predicting users ’ future interactions from their historical behavior sequences. Table 4: The statistics of the datasets . Dataset . Beauty Toys Sports ML 1 M ML20M Internal.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2509.13648", "content": "Generative recommendation plays a crucial role in personalized systems, predicting users ’ future interactions from their historical behavior sequences. Table 4: The statistics of the datasets . Dataset . Beauty Toys Sports ML 1 M ML20M Internal."}
+{"idx": 3, "title": "distributions - Graphical intuition of statistics on a manifold - Cross...", "date": "", "ddg_snippet": "What are the points on the manifold? This quote from this online find , seemingly indicates that it can either be the data points, or the distribution parameters: Statistics on manifolds and information geometry are two different ways in which differential geometry meets statistics .", "subpage_snippet": "", "source": "stats.stackexchange.com", "link": "https://stats.stackexchange.com/questions/239496/graphical-intuition-of-statistics-on-a-manifold", "content": "What are the points on the manifold? This quote from this online find , seemingly indicates that it can either be the data points, or the distribution parameters: Statistics on manifolds and information geometry are two different ways in which differential geometry meets statistics ."}
+{"idx": 4, "title": "(PDF) Arabic Sentiment Analysis of Users ’ Opinions of Governmental...", "date": "", "ddg_snippet": "2 shows dataset statistics . Table 2: Dataset labelling. Total of records 7759. Negative records 2913.analysis dataset using distant supervision and self training ,” in Proc. of the 4th Workshop on Open-Source.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/360084773_Arabic_Sentiment_Analysis_of_Users'_Opinions_of_Governmental_Mobile_Applications", "content": "2 shows dataset statistics . Table 2: Dataset labelling. Total of records 7759. Negative records 2913.analysis dataset using distant supervision and self training ,” in Proc. of the 4th Workshop on Open-Source."}
+{"idx": 5, "title": "Windows. Ключи KMS | Д. С. Кулябов", "date": "", "ddg_snippet": "Julia language features for processing statistical data . A Geometric Approach to the Lagrangian and Hamiltonian Formalism of Electrodynamics. Application of Functional Integrals to Stochastic Equations.", "subpage_snippet": "", "source": "yamadharma.github.io", "link": "https://yamadharma.github.io/ru/post/2023/06/08/windows-kms-keys/", "content": "Julia language features for processing statistical data . A Geometric Approach to the Lagrangian and Hamiltonian Formalism of Electrodynamics. Application of Functional Integrals to Stochastic Equations."}
+{"idx": 6, "title": "Utility | Service / Support - GIGABYTE Global", "date": "", "ddg_snippet": "AI TOP Utility 4. 1 .0: 1 . Dataset Creator: Automatically transforms unorganized datasets into structured Q&A lists, ready for fine-tuning with optimal efficiency.", "subpage_snippet": "", "source": "www.gigabyte.com", "link": "https://www.gigabyte.com/Support/Utility/Motherboard", "content": "AI TOP Utility 4. 1 .0: 1 . Dataset Creator: Automatically transforms unorganized datasets into structured Q&A lists, ready for fine-tuning with optimal efficiency."}
+{"idx": 7, "title": "Journal of Medical Internet Research - Evaluating the Utility of...", "date": "", "ddg_snippet": "Data were extracted using structured summary tables and synthesized qualitatively to identify methodological trends, strengths, and limitations. Statistical pooling or effect size integration was not performed due to the diversity of outcome measures across studies.", "subpage_snippet": "", "source": "www.jmir.org", "link": "https://www.jmir.org/2025/1/e69422/", "content": "Data were extracted using structured summary tables and synthesized qualitatively to identify methodological trends, strengths, and limitations. Statistical pooling or effect size integration was not performed due to the diversity of outcome measures across studies."}
+{"idx": 8, "title": "New AI System Predicts Risk of 1 ,000 Diseases Years in... - Decrypt", "date": "", "ddg_snippet": "Starting from age 60 data , it can simulate thousands of possible health futures, producing population-level disease burden estimates accurate to within statistical margins. One synthetic dataset trained a secondary Delphi model that achieved 74...", "subpage_snippet": "", "source": "decrypt.co", "link": "https://decrypt.co/340776/new-ai-system-predicts-risk-1000-diseases-years-advance", "content": "Starting from age 60 data , it can simulate thousands of possible health futures, producing population-level disease burden estimates accurate to within statistical margins. One synthetic dataset trained a secondary Delphi model that achieved 74..."}
+{"idx": 9, "title": "QCY ArcBuds Lite TWS Earbuds T27 -White | QCY Bangladesh", "date": "", "ddg_snippet": "Trust QCY Bangladesh to fulfill all your gadget requirements, including the cutting-edge QCY ArcBuds Lite TWS Earbuds T27 TWS.", "subpage_snippet": "", "source": "qcybd.com", "link": "https://qcybd.com/product/qcy-arcbuds-lite-tws-earbuds-t27-white/", "content": "Trust QCY Bangladesh to fulfill all your gadget requirements, including the cutting-edge QCY ArcBuds Lite TWS Earbuds T27 TWS."}

data/sampled_jsons/32867_Descriptor-In-Pixel_SCAMP-7_maximum_FPS_year_2023.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CVPR Poster Descriptor - In - Pixel : Point-Feature Tracking For Pixel...", "date": "", "ddg_snippet": "This \"response map\" is utilized for both detection and tracking of point-features across the pixel -processor array. This approach is very fast, our implementation upon the SCAMP - 7 PPA prototype runs at over 3000 FPS ( Frames Per Second ), tracking...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/32867", "content": "This \"response map\" is utilized for both detection and tracking of point-features across the pixel -processor array. This approach is very fast, our implementation upon the SCAMP - 7 PPA prototype runs at over 3000 FPS ( Frames Per Second ), tracking..."}
+{"idx": 1, "title": "SCAMP Vision Sensor", "date": "", "ddg_snippet": "The SCAMP -5 vision chip contains a 256x256 processor array, operating in a SIMD mode, with one processing element per image pixel . The processors are simple albeit fully software-programmable entities, comprising local memory, ALU, control and I/O circuits.", "subpage_snippet": "", "source": "personalpages.manchester.ac.uk", "link": "https://personalpages.manchester.ac.uk/staff/p.dudek/scamp/", "content": "The SCAMP -5 vision chip contains a 256x256 processor array, operating in a SIMD mode, with one processing element per image pixel . The processors are simple albeit fully software-programmable entities, comprising local memory, ALU, control and I/O circuits."}
+{"idx": 2, "title": "Resize Image Pixel Online", "date": "", "ddg_snippet": "Then, you have one option resize the image pixel . An image is made up of thousands of pixels . Image size depends on the number of pixels and colors in that image. Reducing pixel size from file image size also decreases.", "subpage_snippet": "", "source": "image.pi7.org", "link": "https://image.pi7.org/resize-image-pixel", "content": "Then, you have one option resize the image pixel . An image is made up of thousands of pixels . Image size depends on the number of pixels and colors in that image. Reducing pixel size from file image size also decreases."}
+{"idx": 3, "title": "Как установить максимальную частоту кадров ( FPS ) в настройках...", "date": "", "ddg_snippet": "В статье предложен простой способ, как можно установить макс. ограничение для частоты кадров ( FPS ) в играх для видеокарт от NVIDIA и AMD.", "subpage_snippet": "", "source": "ocomp.info", "link": "https://ocomp.info/ustanovit-maksimalnyiy-fps.html", "content": "В статье предложен простой способ, как можно установить макс. ограничение для частоты кадров ( FPS ) в играх для видеокарт от NVIDIA и AMD."}
+{"idx": 4, "title": "Wplace Pixel Art - Convert Images to wplace Pixel", "date": "", "ddg_snippet": "Transform any image into Wplace pixel art with wplace pixel converter.Plan your Wplace build before you place a single pixel . Click to upload or drag and drop your image here. Supports JPEG, JPG, PNG - Max 5MB. Works with any image type for pixel art conversion.", "subpage_snippet": "", "source": "wplacepixel.com", "link": "https://wplacepixel.com/", "content": "Transform any image into Wplace pixel art with wplace pixel converter.Plan your Wplace build before you place a single pixel . Click to upload or drag and drop your image here. Supports JPEG, JPG, PNG - Max 5MB. Works with any image type for pixel art conversion."}
+{"idx": 5, "title": "How to Set a Maximum Frame Rate in NVIDIA's Drivers", "date": "", "ddg_snippet": "In the list of settings, click the box to the right of \" Max Frame Rate.\" By default, this option is disabled, and there is no maximum frame rate.", "subpage_snippet": "", "source": "www.howtogeek.com", "link": "https://www.howtogeek.com/509097/how-to-set-a-maximum-frame-rate-in-nvidias-drivers/", "content": "In the list of settings, click the box to the right of \" Max Frame Rate.\" By default, this option is disabled, and there is no maximum frame rate."}
+{"idx": 6, "title": "A4 size in pixels . Convenient calculator with different DPIs.", "date": "", "ddg_snippet": "In theory, an A4 size can be displayed or printed in any resolution. For a sharp image, however, a minimum number of pixels is required.You can also choose the number of Dots Per Inch (DPI) or Pixels Per Inch (PPI) for pixels . The result is shown in the last column under dimension.", "subpage_snippet": "", "source": "www.a4-size.com", "link": "https://www.a4-size.com/a4-size-in-pixels/", "content": "In theory, an A4 size can be displayed or printed in any resolution. For a sharp image, however, a minimum number of pixels is required.You can also choose the number of Dots Per Inch (DPI) or Pixels Per Inch (PPI) for pixels . The result is shown in the last column under dimension."}
+{"idx": 7, "title": "Как убрать ограничение ФПС в Роблоксе", "date": "", "ddg_snippet": "Убираем ограничение FPS в Roblox.Здесь можете управлять настройкой FPS через « Maximum Frame Rate». Установите подходящее для вас значение, после чего можете проверить, удалось ли тем самым убрать ограничения на FPS .", "subpage_snippet": "", "source": "Lumpics.ru", "link": "https://Lumpics.ru/how-to-remove-fps-limit-on-roblox/", "content": "Убираем ограничение FPS в Roblox.Здесь можете управлять настройкой FPS через « Maximum Frame Rate». Установите подходящее для вас значение, после чего можете проверить, удалось ли тем самым убрать ограничения на FPS ."}
+{"idx": 8, "title": "GitHub - shakilxt/ULTRA-EXTREME-UNLOCKER: This Magisk module...", "date": "", "ddg_snippet": "ULTRA-EXTREME-UNLOCKER. This Magisk module unlocks the maximum FPS setting in PUBG Mobile/BGMI and all other supported games on your Android device.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/shakilxt/ULTRA-EXTREME-UNLOCKER", "content": "ULTRA-EXTREME-UNLOCKER. This Magisk module unlocks the maximum FPS setting in PUBG Mobile/BGMI and all other supported games on your Android device."}
+{"idx": 9, "title": "Intel Iris Xe Graphics G 7 80EU: Detailed Specifications... - CpuTronic", "date": "", "ddg_snippet": "- Better in gaming (by 40-50%), but requires active cooling and increases the cost of devices. Conclusion: Iris Xe G 7 is an optimal choice for those who value silence and battery life over maximum FPS .", "subpage_snippet": "", "source": "cputronic.com", "link": "https://cputronic.com/gpu/intel-iris-xe-graphics-g7-80eu", "content": "- Better in gaming (by 40-50%), but requires active cooling and increases the cost of devices. Conclusion: Iris Xe G 7 is an optimal choice for those who value silence and battery life over maximum FPS ."}

data/sampled_jsons/33775_Instant_Gaussian_Stream_AGM-Net_training_dataset_test_sequences_Section_4.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Instant Gaussian Stream: Fast and Generalizable Streaming of ...", "date": "", "ddg_snippet": "Download our processed data from 4 sequences of N3DV, which can be directly used for training . It contains 1,200 optimized Gaussian points and requires 150GB of storage space.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/yjb6/IGS", "content": "Download our processed data from 4 sequences of N3DV, which can be directly used for training . It contains 1,200 optimized Gaussian points and requires 150GB of storage space."}
+{"idx": 1, "title": "Instant Gaussian Stream: Fast and Generalizable Streaming of ...", "date": "", "ddg_snippet": "Mar 21, 2025 · Second, AGM-Net has been trained on four sequences from the N3DV indoor dataset . The limited size of the training data constrains its generalization capability.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.16979v1", "content": "Mar 21, 2025 · Second, AGM-Net has been trained on four sequences from the N3DV indoor dataset . The limited size of the training data constrains its generalization capability."}
+{"idx": 2, "title": "(PDF) Instant Gaussian Stream: Fast and Generalizable ...", "date": "", "ddg_snippet": "Mar 21, 2025 · In this paper, we propose Instant Gaussian Stream (IGS), a fast and generalizable streaming framework, to address these issues.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/390114414_Instant_Gaussian_Stream_Fast_and_Generalizable_Streaming_of_Dynamic_Scene_Reconstruction_via_Gaussian_Splatting", "content": "Mar 21, 2025 · In this paper, we propose Instant Gaussian Stream (IGS), a fast and generalizable streaming framework, to address these issues."}
+{"idx": 3, "title": "demo_test_gaussian.ipynb - Colab - Google Colab", "date": "", "ddg_snippet": "This example shows you how to train a reconstruction network for an denoising problem on a fully self-supervised way, i.e., using corrupted measurement data only.", "subpage_snippet": "", "source": "colab.research.google.com", "link": "https://colab.research.google.com/github/bemc22/GeneralizedR2R/blob/main/demo_test_gaussian.ipynb", "content": "This example shows you how to train a reconstruction network for an denoising problem on a fully self-supervised way, i.e., using corrupted measurement data only."}
+{"idx": 4, "title": "Instant Gaussian Stream: Fast and Generalizable Streaming of ...", "date": "", "ddg_snippet": "In this pa-per, we propose Instant Gaussian Stream (IGS), a fast and tions, demonstrating that our approach can achieve stream-ing with a average per-frame reconstruction time of 2s+, alongside a enhancement in view synthesis quality.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Yan_Instant_Gaussian_Stream_Fast_and_Generalizable_Streaming_of_Dynamic_Scene_CVPR_2025_paper.pdf", "content": "In this pa-per, we propose Instant Gaussian Stream (IGS), a fast and tions, demonstrating that our approach can achieve stream-ing with a average per-frame reconstruction time of 2s+, alongside a enhancement in view synthesis quality."}
+{"idx": 5, "title": "AGM-Net Model & Training · Issue #4 · yjb6/IGS - GitHub", "date": "", "ddg_snippet": "Jul 8, 2025 · Which dataset did you train the AGM-Net on, while generating the quantitative results on the N3DV dataset ? We would like to add your paper to our benchmark for an upcoming submission.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/yjb6/IGS/issues/4", "content": "Jul 8, 2025 · Which dataset did you train the AGM-Net on, while generating the quantitative results on the N3DV dataset ? We would like to add your paper to our benchmark for an upcoming submission."}
+{"idx": 6, "title": "CVPR Poster Instant Gaussian Stream: Fast and ...", "date": "", "ddg_snippet": "In this Section , we first introduce the datasets we used, along with the partitioning and preprocessing of training data, in Sec . 4.1. Next, we provide a ...", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/33775", "content": "In this Section , we first introduce the datasets we used, along with the partitioning and preprocessing of training data, in Sec . 4.1. Next, we provide a ..."}
+{"idx": 7, "title": "每帧仅2秒的流式重建速度！IGS已开源：采用流式策略解决动态场景重建 ...", "date": "", "ddg_snippet": "为使流式框架更具实用性，本文介绍 即时高斯流（ Instant Gaussian Stream , IGS），这是一种单帧重建耗时仅2秒+、能抑制误差累积并提升视图合成质量的动态场景重建方法： 广义锚点驱动高斯运动网络（ AGM-Net ）：通过一组称为锚点的关键点携带运动特征来指导高斯 ...", "subpage_snippet": "", "source": "zhuanlan.zhihu.com", "link": "https://zhuanlan.zhihu.com/p/1915569198148593307", "content": "为使流式框架更具实用性，本文介绍 即时高斯��（ Instant Gaussian Stream , IGS），这是一种单帧重建耗时仅2秒+、能抑制误差累积并提升视图合成质量的动态场景重建方法： 广义锚点驱动高斯运动网络（ AGM-Net ）：通过一组称为锚点的关键点携带运动特征来指导高斯 ..."}
+{"idx": 8, "title": "typeid.txt", "date": "", "ddg_snippet": "... 4 Constellation 5 Solar System 6 Sun G5 (Yellow) 7 Sun K7 (Orange) 8 Sun K5 (Red Giant) 9 Sun B0 (Blue) 10 Sun F0 (White) 11 Planet (Temperate) 12 Planet ...", "subpage_snippet": "", "source": "eve-files.com", "link": "https://eve-files.com/chribba/typeid.txt", "content": "... 4 Constellation 5 Solar System 6 Sun G5 (Yellow) 7 Sun K7 (Orange) 8 Sun K5 (Red Giant) 9 Sun B0 (Blue) 10 Sun F0 (White) 11 Planet (Temperate) 12 Planet ..."}
+{"idx": 9, "title": "googlelist.counts", "date": "", "ddg_snippet": "... section 232270007 298 own 232024685 299 found 232011041 300 sports 231876585 ... training 176153292 437 too 176113530 438 credit 175927068 439 point ...", "subpage_snippet": "", "source": "mit.edu", "link": "http://mit.edu/~ecprice/Public/freq/googlelist.counts", "content": "... section 232270007 298 own 232024685 299 found 232011041 300 sports 231876585 ... training 176153292 437 too 176113530 438 credit 175927068 439 point ..."}

data/sampled_jsons/4Xnqm4f71y_DVI_Derivative-based_Vision_Network_arXiv.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "DVI: A Derivative-based Vision Network for INR - OpenReview", "date": "", "ddg_snippet": "DVI excels by leveraging the valuable features captured in the high order derivative map of the INR, then seamlessly fusing them into a pre-existing raster- based vision network , enhanc-ing its performance with additional, task-relevant structural information.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=4Xnqm4f71y", "content": "DVI excels by leveraging the valuable features captured in the high order derivative map of the INR, then seamlessly fusing them into a pre-existing raster- based vision network , enhanc-ing its performance with additional, task-relevant structural information."}
+{"idx": 1, "title": "[2309.13814v2] DVI-SLAM: A Dual Visual Inertial SLAM Network - arXiv.org", "date": "", "ddg_snippet": "Recent deep learning based visual simultaneous localization and mapping (SLAM) methods have made significant progress. However, how to make full use of visual information as well as better integrate with inertial measurement unit (IMU) in visual SLAM has potential research value. This paper proposes a novel deep SLAM network with dual visual factors. The basic idea is to integrate both ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2309.13814v2", "content": "Recent deep learning based visual simultaneous localization and mapping (SLAM) methods have made significant progress. However, how to make full use of visual information as well as better integrate with inertial measurement unit (IMU) in visual SLAM has potential research value. This paper proposes a novel deep SLAM network with dual visual factors. The basic idea is to integrate both ..."}
+{"idx": 2, "title": "ICML Poster DVI:A Derivative-based Vision Network for INR", "date": "", "ddg_snippet": "DVI:A Derivative-based Vision Network for INR RUNZHAO YANG · Xiaolong Wu · Zhihong Zhang · Fabian Zhang · Tingxiong Xiao · Zongren Li · Kunlun He · Jinli Suo", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46476", "content": "DVI:A Derivative-based Vision Network for INR RUNZHAO YANG · Xiaolong Wu · Zhihong Zhang · Fabian Zhang · Tingxiong Xiao · Zongren Li · Kunlun He · Jinli Suo"}
+{"idx": 3, "title": "DVI:A Derivative-based Vision Network for INR - AMiner", "date": "", "ddg_snippet": "Recent advancements in computer vision have seen Implicit Neural Representations (INR) becoming a dominant representation form for data due to their compactness and expre", "subpage_snippet": "", "source": "www.aminer.cn", "link": "https://www.aminer.cn/pub/6853e848163c01c8502f0416/dvi-a-derivative-based-vision-network-for-inr", "content": "Recent advancements in computer vision have seen Implicit Neural Representations (INR) becoming a dominant representation form for data due to their compactness and expre"}
+{"idx": 4, "title": "Implicit Neural Representation for Vision", "date": "", "ddg_snippet": "Downstream tasks based on INRs: Besides being an efficient and unified representation, INR presents exciting opportunities for various vision tasks. These include enhancing signals, recognizing patterns, and generating new data.", "subpage_snippet": "", "source": "inrv.github.io", "link": "https://inrv.github.io/", "content": "Downstream tasks based on INRs: Besides being an efficient and unified representation, INR presents exciting opportunities for various vision tasks. These include enhancing signals, recognizing patterns, and generating new data."}
+{"idx": 5, "title": "DVI:A Derivative-based Vision Network for INR", "date": "", "ddg_snippet": "DVI excels by extracting semantic information from the high order derivative map of the INR, then seamlessly fusing it into a pre-existing raster- based vision network , enhancing its performance with deeper, task-relevant semantic insights.", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/chatpaper/paper/167863", "content": "DVI excels by extracting semantic information from the high order derivative map of the INR, then seamlessly fusing it into a pre-existing raster- based vision network , enhancing its performance with deeper, task-relevant semantic insights."}
+{"idx": 6, "title": "DVI-SLAM: A Dual Visual Inertial SLAM Network - IEEE Xplore", "date": "", "ddg_snippet": "Recent deep learning based visual simultaneous localization and mapping (SLAM) methods have made significant progress. However, how to make full use of visual information as well as better integrate with inertial measurement unit (IMU) in visual SLAM has potential research value. This paper proposes a novel deep SLAM network with dual visual factors. The basic idea is to integrate both ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/abstract/document/10610042", "content": "Recent deep learning based visual simultaneous localization and mapping (SLAM) methods have made significant progress. However, how to make full use of visual information as well as better integrate with inertial measurement unit (IMU) in visual SLAM has potential research value. This paper proposes a novel deep SLAM network with dual visual factors. The basic idea is to integrate both ..."}
+{"idx": 7, "title": "DVI:A Derivative-based Vision Network for INR - OpenReview", "date": "", "ddg_snippet": "DVI excels by extracting semantic information from the high order derivative map of the INR, then seamlessly fusing it into a pre-existing raster- based vision network , enhancing its performance with deeper, task-relevant semantic insights.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=4Xnqm4f71y", "content": "DVI excels by extracting semantic information from the high order derivative map of the INR, then seamlessly fusing it into a pre-existing raster- based vision network , enhancing its performance with deeper, task-relevant semantic insights."}
+{"idx": 8, "title": "DVI-SLAM: A Dual Visual Inertial SLAM Network - arXiv.org", "date": "", "ddg_snippet": "In this paper, we propose a novel optimization- based deep SLAM method, which is named Dual Visual Inertial SLAM network ( DVI -SLAM). DVI -SLAM simultaneously infers camera pose and dense depth by dynamically fusing multiple factors with an end-to-end trainable differentiable structure.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2309.13814", "content": "In this paper, we propose a novel optimization- based deep SLAM method, which is named Dual Visual Inertial SLAM network ( DVI -SLAM). DVI -SLAM simultaneously infers camera pose and dense depth by dynamically fusing multiple factors with an end-to-end trainable differentiable structure."}
+{"idx": 9, "title": "DVI-SLAM: A Dual Visual Inertial SLAM Network - ResearchGate", "date": "", "ddg_snippet": "The vision -aided inertial navigation algorithm we propose has computational complexity only linear in the number of features, and is capable of high-precision pose estimation in large-scale real ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/382981789_DVI-SLAM_A_Dual_Visual_Inertial_SLAM_Network", "content": "The vision -aided inertial navigation algorithm we propose has computational complexity only linear in the number of features, and is capable of high-precision pose estimation in large-scale real ..."}

data/sampled_jsons/4uOEiitySn_A_Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_dataset_empirical_.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Checks - and - Balances Framework for Context - Aware Ethical AI ...", "date": "", "ddg_snippet": "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": "This work introduces a checks - and - balances framework for ethical AI behavior."}
+{"idx": 1, "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.", "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."}
+{"idx": 2, "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."}
+{"idx": 3, "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."}
+{"idx": 4, "title": "ICML Poster A Three-Branch Checks - and - Balances Framework for ...", "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. It implements three independent yet interacting components...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46461", "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. It implements three independent yet interacting components..."}
+{"idx": 5, "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."}
+{"idx": 6, "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."}
+{"idx": 7, "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."}
+{"idx": 8, "title": "A Human-centred Framework for Designing Complex AI ... | HackerNoon", "date": "", "ddg_snippet": "The practical framework helps designers, data scientists, and engineers find common ground, aligning the voice and needs of users with the design of AI systems.", "subpage_snippet": "", "source": "hackernoon.com", "link": "https://hackernoon.com/a-human-centred-framework-for-designing-complex-ai-solutions-for-strategic-decision-making", "content": "The practical framework helps designers, data scientists, and engineers find common ground, aligning the voice and needs of users with the design of AI systems."}
+{"idx": 9, "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."}

data/sampled_jsons/AERO_model_sharding_blockchain_deep_reinforcement_learning_learning_rate_year_2023.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "MIT 6.S091: Introduction to Deep Reinforcement Learning ... - YouTube", "date": "", "ddg_snippet": "First lecture of MIT course 6.S091: Deep Reinforcement Learning , introducing the fascinating field of Deep RL.", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=zR11FLZ-O9M", "content": "First lecture of MIT course 6.S091: Deep Reinforcement Learning , introducing the fascinating field of Deep RL."}
+{"idx": 1, "title": "Payment Routing Across IoT Blockchain Shards using Deep ...", "date": "", "ddg_snippet": "Shard configurations are decided by a deep Q- learning -based genetic algorithm (DQGA), which assists in deciding optimal shard length and merging temporally unused shards . These decisions allow the proposed model to reduce mining delay by up to...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/390250786_Payment_Routing_Across_IoT_Blockchain_Shards_using_Deep_Reinforcement_Learning", "content": "Shard configurations are decided by a deep Q- learning -based genetic algorithm (DQGA), which assists in deciding optimal shard length and merging temporally unused shards . These decisions allow the proposed model to reduce mining delay by up to..."}
+{"idx": 2, "title": "SmartChain: A Dynamic and Self-Adaptive Sharding Framework for...", "date": "", "ddg_snippet": "Learning Algorithm, Malicious Nodes, Deep Reinforcement Learning Agent, Byzantine Fault Tolerance, Successful Defense, Replay Memory, Blockchain Nodes, Internet Of Things Nodes, Message Authentication Code, Time Varying Environment, Shannons Information Theory...", "subpage_snippet": "", "source": "www.computer.org", "link": "https://www.computer.org/csdl/journal/sc/2024/02/10468552/1VpXOUcfXEs", "content": "Learning Algorithm, Malicious Nodes, Deep Reinforcement Learning Agent, Byzantine Fault Tolerance, Successful Defense, Replay Memory, Blockchain Nodes, Internet Of Things Nodes, Message Authentication Code, Time Varying Environment, Shannons Information Theory..."}
+{"idx": 3, "title": "(PDF) Secure Trust-Based Delegated Consensus for Blockchain ...", "date": "", "ddg_snippet": "C. DEEP REINFORCEMENT LEARNING BASED BLOCKCHAINS DRL is a machine learning technology that combines deep learning with reinforcement learning (RL). DRL helps the agent to make optimal decisions under dynamic states.", "subpage_snippet": "", "source": "www.academia.edu", "link": "https://www.academia.edu/98817727/Secure_Trust_Based_Delegated_Consensus_for_Blockchain_Frameworks_Using_Deep_Reinforcement_Learning", "content": "C. DEEP REINFORCEMENT LEARNING BASED BLOCKCHAINS DRL is a machine learning technology that combines deep learning with reinforcement learning (RL). DRL helps the agent to make optimal decisions under dynamic states."}
+{"idx": 4, "title": "Stable Blockchain Sharding under Adversarial Transaction Generation", "date": "", "ddg_snippet": "Sharding is used to improve the scalability and performance of blockchain systems. We investigate the stability of blockchain sharding , where transactions are continuously generated by an adversarial model .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2404.04438", "content": "Sharding is used to improve the scalability and performance of blockchain systems. We investigate the stability of blockchain sharding , where transactions are continuously generated by an adversarial model ."}
+{"idx": 5, "title": "What Is Blockchain Sharding ? - 101 Blockchains", "date": "", "ddg_snippet": "Sharding is the process of breaking down a blockchain network’s workload into smaller pieces. Learn more about blockchain sharding in this guide now.", "subpage_snippet": "", "source": "101blockchains.com", "link": "https://101blockchains.com/what-is-blockchain-sharding/", "content": "Sharding is the process of breaking down a blockchain network’s workload into smaller pieces. Learn more about blockchain sharding in this guide now."}
+{"idx": 6, "title": "Harnessing Deep Reinforcement Learning for Algorithmic Trading", "date": "", "ddg_snippet": "Simulating Reinforcement Learning Model .Every time the model ’s parameters are updated, the learning _ rate argument is set to 0.0005. With ent_coef set to 0.01, exploration and exploitation are traded off during training.", "subpage_snippet": "", "source": "readmedium.com", "link": "https://readmedium.com/harnessing-deep-reinforcement-learning-for-algorithmic-trading-b4c67534b33a", "content": "Simulating Reinforcement Learning Model .Every time the model ’s parameters are updated, the learning _ rate argument is set to 0.0005. With ent_coef set to 0.01, exploration and exploitation are traded off during training."}
+{"idx": 7, "title": "Dynamic Learning Rate for Deep Reinforcement Learning : A Bandit...", "date": "", "ddg_snippet": "Inthis work, we propose dynamic Learning Rate for deep Reinforcement Learning (LRRL), a meta- learning approach that selects the learning rate based on theagent's performance during training.", "subpage_snippet": "", "source": "trendtoknow.com", "link": "https://trendtoknow.com/arxiv/1300/dynamic-learning-rate-for-deep-reinforcement-learning:-a-bandit-approach", "content": "Inthis work, we propose dynamic Learning Rate for deep Reinforcement Learning (LRRL), a meta- learning approach that selects the learning rate based on theagent's performance during training."}
+{"idx": 8, "title": "Sharding Types - Everything You Need to Know | Shardeum", "date": "", "ddg_snippet": "Sharding is a method for dividing up a single dataset into many databases, which can then be kept on working sites. Read what are sharding types in this blog.", "subpage_snippet": "", "source": "shardeum.org", "link": "https://shardeum.org/blog/sharding-types/", "content": "Sharding is a method for dividing up a single dataset into many databases, which can then be kept on working sites. Read what are sharding types in this blog."}
+{"idx": 9, "title": "Reinforcement Learning Real-world examples - Analytics Yogi", "date": "", "ddg_snippet": "Reinforcement learning , Data Science, Machine Learning , Deep Learning , Data Analytics,Tutorials, AI, real-life, real-world, examples.The reinforcement learning model calculates weights at each time step, and then updates them in real-time according to reinforcement signals.", "subpage_snippet": "", "source": "vitalflux.com", "link": "https://vitalflux.com/reinforcement-learning-real-world-examples/", "content": "Reinforcement learning , Data Science, Machine Learning , Deep Learning , Data Analytics,Tutorials, AI, real-life, real-world, examples.The reinforcement learning model calculates weights at each time step, and then updates them in real-time according to reinforcement signals."}

data/sampled_jsons/AI_alignment_framework_checks_balances_executive_branch.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Routine: A Structural Planning Framework for LLM Agent System", "date": "", "ddg_snippet": "... a multi-agent framework that leverages GraphFlow to model execution as a DAG of tool calls, ensuring traceable and reliable process flows [ 20 ] .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.14447v1", "content": "... a multi-agent framework that leverages GraphFlow to model execution as a DAG of tool calls, ensuring traceable and reliable process flows [ 20 ] ."}
+{"idx": 1, "title": "Strategic Alignment Patterns in National AI Policies", "date": "", "ddg_snippet": "... of literature: strategic foresight in technology policy, policy instrument theory, comparative AI governance, and alignment analysis frameworks .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.05400v2", "content": "... of literature: strategic foresight in technology policy, policy instrument theory, comparative AI governance, and alignment analysis frameworks ."}
+{"idx": 2, "title": "A Framework to Govern AI Innovation | Lawfare", "date": "", "ddg_snippet": "... framework below details how best to facilitate that sort of policy experimentation in a manner that aligns with our federal system — which ...", "subpage_snippet": "", "source": "www.lawfaremedia.org", "link": "https://www.lawfaremedia.org/article/a-framework-to-govern-ai-innovation", "content": "... framework below details how best to facilitate that sort of policy experimentation in a manner that aligns with our federal system — which ..."}
+{"idx": 3, "title": "What is it to solve the alignment problem? (Notes) — EA Forum", "date": "", "ddg_snippet": "Finally, I express skepticism that solving the alignment problem requires imbuing a superintelligent AI with intrinsic concern for our ...", "subpage_snippet": "", "source": "forum.effectivealtruism.org", "link": "https://forum.effectivealtruism.org/posts/eCAfDGaouomgsojdt/what-is-it-to-solve-the-alignment-problem", "content": "Finally, I express skepticism that solving the alignment problem requires imbuing a superintelligent AI with intrinsic concern for our ..."}
+{"idx": 4, "title": "Integrating Reasoning and Agentic Frameworks for LLMs: A", "date": "", "ddg_snippet": "In summary, Tree-of-Thought frameworks extend CoT by introducing a search paradigm: the model can branch into multiple reasoning paths and backtrack ...", "subpage_snippet": "", "source": "artsen.h3x.xyz", "link": "https://artsen.h3x.xyz/blog/integrating-reasoning-and-agentic-frameworks-for-llms-a-comprehensive-review-and-unified-proposal/", "content": "In summary, Tree-of-Thought frameworks extend CoT by introducing a search paradigm: the model can branch into multiple reasoning paths and backtrack ..."}
+{"idx": 5, "title": "SyGra: A Unified Graph-Based Framework for Scalable Generation,", "date": "", "ddg_snippet": "It enables the reuse of graphs as subgraphs, ensures reliable execution through integrated validation and checkpointing, and natively supports ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.15432v2", "content": "It enables the reuse of graphs as subgraphs, ensures reliable execution through integrated validation and checkpointing, and natively supports ..."}
+{"idx": 6, "title": "Securing the Digital Future: Atul Luthra on AI, Compliance", "date": "", "ddg_snippet": "AI -Powered Social Engineering: AI can craft hyper-realistic phishing emails, clone executive voices, and create deepfake videos that mimic real ...", "subpage_snippet": "", "source": "www.smartstateindia.com", "link": "https://www.smartstateindia.com/securing-the-digital-future-atul-luthra-on-ai-compliance-the-cyber-threats-of-2025/", "content": "AI -Powered Social Engineering: AI can craft hyper-realistic phishing emails, clone executive voices, and create deepfake videos that mimic real ..."}
+{"idx": 7, "title": "Scaling Mobile App Development: Insights from Amit Samsukha |", "date": "", "ddg_snippet": "... Co-Founder and CTO of EmizenTech, shared his insights on proven strategies for building and managing global mobile development teams to balance code ...", "subpage_snippet": "", "source": "clutch.co", "link": "https://clutch.co/resources/scaling-mobile-app-development-from-amit-samsukha", "content": "... Co-Founder and CTO of EmizenTech, shared his insights on proven strategies for building and managing global mobile development teams to balance code ..."}
+{"idx": 8, "title": "Lean Agents: The Agile Workforce of Agentic AI - Architecture", "date": "", "ddg_snippet": "... to essentials, they reduce operational friction, make real-time auditing straightforward, and align with today ’ s demands for responsible AI ...", "subpage_snippet": "", "source": "www.architectureandgovernance.com", "link": "https://www.architectureandgovernance.com/uncategorized/lean-agents-the-agile-workforce-of-agentic-ai/", "content": "... to essentials, they reduce operational friction, make real-time auditing straightforward, and align with today ’ s demands for responsible AI ..."}
+{"idx": 9, "title": "Reality Check: Accenture Research Shows Enterprises Face a", "date": "", "ddg_snippet": "The clear takeaway is that enterprises need to balance their AI infrastructure investments with their security spending to ensure the most protected ...", "subpage_snippet": "", "source": "itcblogs.currentanalysis.com", "link": "https://itcblogs.currentanalysis.com/2025/06/30/reality-check-accenture-research-shows-enterprises-face-a-security-deficit-in-the-ai-era/", "content": "The clear takeaway is that enterprises need to balance their AI infrastructure investments with their security spending to ensure the most protected ..."}

data/sampled_jsons/A_First_Look_at_Public_Service_Websites_A_Framework_for_Improving_Web_Affordability_and_Inclusivenes.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Framework for Improving Web Affordability and Inclusiveness", "date": "", "ddg_snippet": "A Framework for Improving Web Affordability and Inclusiveness . Authors ... A First Look at Public Service Websites from the Affordability Lens. WWW '23 ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3603269.3604872", "content": "A Framework for Improving Web Affordability and Inclusiveness . Authors ... A First Look at Public Service Websites from the Affordability Lens. WWW '23 ..."}
+{"idx": 1, "title": "Rethinking Web for Affordability and Inclusion", "date": "", "ddg_snippet": "by IA Qazi · 2021 · Cited by 12 — A First Look at Public Service Websites from the Affordability Lens. WWW '23 ... A Framework for Improving Web Affordability and Inclusiveness . ACM ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3484266.3487376", "content": "by IA Qazi · 2021 · Cited by 12 — A First Look at Public Service Websites from the Affordability Lens. WWW '23 ... A Framework for Improving Web Affordability and Inclusiveness . ACM ..."}
+{"idx": 2, "title": "Publications", "date": "", "ddg_snippet": "A Framework for Improving Web Affordability and Inclusiveness code · SIGCOMM '23 ; A First Look at Public Service Websites from the Affordability Lens code ...", "subpage_snippet": "", "source": "rumaisahabib.com", "link": "https://rumaisahabib.com/publications/", "content": "A Framework for Improving Web Affordability and Inclusiveness code · SIGCOMM '23 ; A First Look at Public Service Websites from the Affordability Lens code ..."}
+{"idx": 3, "title": "Dr. Ihsan Ayyub Qazi @ LUMS - Publications", "date": "", "ddg_snippet": "A Framework for Improving Web Affordability and Inclusiveness . Rumaisa ... A First Look at Public Service Websites from the Affordability Lens. Rumaisa ...", "subpage_snippet": "", "source": "www.ihsanqazi.com", "link": "https://www.ihsanqazi.com/publications", "content": "A Framework for Improving Web Affordability and Inclusiveness . Rumaisa ... A First Look at Public Service Websites from the Affordability Lens. Rumaisa ..."}
+{"idx": 4, "title": "Rumaisa Habib", "date": "", "ddg_snippet": "A framework for improving web affordability and inclusiveness . R Habib, S ... A First Look at Public Service Websites from the Affordability Lens. R ...", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=FEM0WXwAAAAJ&hl=en", "content": "A framework for improving web affordability and inclusiveness . R Habib, S ... A First Look at Public Service Websites from the Affordability Lens. R ..."}
+{"idx": 5, "title": "Aimen Inam (0000-0002-9725-1900)", "date": "", "ddg_snippet": "Works (2). sort. A Framework for Improving Web Affordability and Inclusiveness ... A First Look at Public Service Websites from the Affordability Lens. 2023-04 ...", "subpage_snippet": "", "source": "orcid.org", "link": "https://orcid.org/0000-0002-9725-1900", "content": "Works (2). sort. A Framework for Improving Web Affordability and Inclusiveness ... A First Look at Public Service Websites from the Affordability Lens. 2023-04 ..."}
+{"idx": 6, "title": "Zafar Ayyub Qazi", "date": "", "ddg_snippet": "A framework for improving web affordability and inclusiveness . R Habib, S ... 2022. A First Look at Public Service Websites from the Affordability Lens. R ...", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=O5uXfioAAAAJ&hl=en", "content": "A framework for improving web affordability and inclusiveness . R Habib, S ... 2022. A First Look at Public Service Websites from the Affordability Lens. R ..."}
+{"idx": 7, "title": "Ihsan Ayyub Qazi", "date": "", "ddg_snippet": "A First Look at Public Service Websites from the Affordability Lens; PACMNET ... A Framework for Improving Web Affordability and Inclusiveness ; PACMNET ...", "subpage_snippet": "", "source": "figshare.com", "link": "https://figshare.com/authors/Ihsan_Ayyub_Qazi/22241953", "content": "A First Look at Public Service Websites from the Affordability Lens; PACMNET ... A Framework for Improving Web Affordability and Inclusiveness ; PACMNET ..."}
+{"idx": 8, "title": "Rumaisa Habib", "date": "", "ddg_snippet": "13 Apr 2025 — BS - Computer Science (Senior Thesis: A Framework for Improving Web Affordability and Inclusiveness ) ... A First Look at Public Service Websites ... 2 pages", "subpage_snippet": "", "source": "rumaisahabib.com", "link": "https://rumaisahabib.com/assets/habib.pdf", "content": "13 Apr 2025 — BS - Computer Science (Senior Thesis: A Framework for Improving Web Affordability and Inclusiveness ) ... A First Look at Public Service Websites ... 2 pages"}
+{"idx": 9, "title": "Ayesha Ali (0000-0003-1051-2264)", "date": "", "ddg_snippet": "A Framework for Improving Web Affordability and Inclusiveness . 2023-09-10 ... A First Look at Public Service Websites from the Affordability Lens. 2023 ...", "subpage_snippet": "", "source": "orcid.org", "link": "https://orcid.org/0000-0003-1051-2264", "content": "A Framework for Improving Web Affordability and Inclusiveness . 2023-09-10 ... A First Look at Public Service Websites from the Affordability Lens. 2023 ..."}

data/sampled_jsons/Algorithm_1_Parallel_Picard_Method_for_sampling_input_x0_approximate_score_function.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PCM : Picard Consistency Model for Fast Parallel Sampling of Diffusion ...", "date": "", "ddg_snippet": "Recently, ParaDiGMS [38] tackled this challenge with a parallel sampling method based on Picard iteration, reducing the sequential steps in diffusion sampling by performing more computations in parallel .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.19731", "content": "Recently, ParaDiGMS [38] tackled this challenge with a parallel sampling method based on Picard iteration, reducing the sequential steps in diffusion sampling by performing more computations in parallel ."}
+{"idx": 1, "title": "Parallel Simulation for Sampling Under Isoperimetry and Score Based ...", "date": "", "ddg_snippet": "In recent years, there has been a surge of interest in proving discretization bounds for sampling under isoperimetry and for diffusion models. As data size grows, reducing the iteration cost becomes an important goal. Inspired by the great success of the parallel simulation of the initial value problem in scientific computation, we propose parallel Picard methods for sampling tasks. Rigorous ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=6Gb7VfTKY7", "content": "In recent years, there has been a surge of interest in proving discretization bounds for sampling under isoperimetry and for diffusion models. As data size grows, reducing the iteration cost becomes an important goal. Inspired by the great success of the parallel simulation of the initial value problem in scientific computation, we propose parallel Picard methods for sampling tasks. Rigorous ..."}
+{"idx": 2, "title": "PDF Parallel Sampling of Diffusion Models - NeurIPS", "date": "", "ddg_snippet": "With this insight, we present ParaDiGMS, a novel method to accelerate the sampling of pretrained diffusion models by denoising multiple steps in parallel . ParaDiGMS is the first diffusion sampling method that enables trading compute for speed and is even compatible with existing fast sampling techniques such as DDIM and DPM-Solver.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2023/file/0d1986a61e30e5fa408c81216a616e20-Paper-Conference.pdf", "content": "With this insight, we present ParaDiGMS, a novel method to accelerate the sampling of pretrained diffusion models by denoising multiple steps in parallel . ParaDiGMS is the first diffusion sampling method that enables trading compute for speed and is even compatible with existing fast sampling techniques such as DDIM and DPM-Solver."}
+{"idx": 3, "title": "Parallel simulation for sampling under isoperimetry and score-based ...", "date": "", "ddg_snippet": "As data size grows, reducing the iteration cost becomes an important goal. Inspired by the great success of the parallel simulation of the initial value problem in scientific computation, we propose parallel Picard methods for sampling tasks.", "subpage_snippet": "", "source": "bohrium.dp.tech", "link": "https://bohrium.dp.tech/paper/arxiv/2412.07435", "content": "As data size grows, reducing the iteration cost becomes an important goal. Inspired by the great success of the parallel simulation of the initial value problem in scientific computation, we propose parallel Picard methods for sampling tasks."}
+{"idx": 4, "title": "PDF Fast parallel sampling under isoperimetry", "date": "", "ddg_snippet": "1 . Introduction In this paper, we study the problem of designing fast parallel algorithms for sampling from continuous distributions π(x) ∝ exp(−V (x)) over x ∈ Rd. Designing eficient sampling algorithms is a ubiquitous problem, but the focus of most prior works has been to minimize sequential eficiency criteria, such as the total number of arithmetic operations or total queries to V ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v247/anari24a/anari24a.pdf", "content": "1 . Introduction In this paper, we study the problem of designing fast parallel algorithms for sampling from continuous distributions π(x) ∝ exp(−V (x)) over x ∈ Rd. Designing eficient sampling algorithms is a ubiquitous problem, but the focus of most prior works has been to minimize sequential eficiency criteria, such as the total number of arithmetic operations or total queries to V ..."}
+{"idx": 5, "title": "PDF PCM : Picard Consistency Model for Fast Parallel Sampling of Diffusion ...", "date": "", "ddg_snippet": "Re-cently, ParaDiGMS [38] tackled this challenge with a par-allel sampling method based on Picard iteration, reducing the sequential steps in diffusion sampling by performing more computations in parallel .", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/So_PCM__Picard_Consistency_Model_for_Fast_Parallel_Sampling_of_CVPR_2025_paper.pdf", "content": "Re-cently, ParaDiGMS [38] tackled this challenge with a par-allel sampling method based on Picard iteration, reducing the sequential steps in diffusion sampling by performing more computations in parallel ."}
+{"idx": 6, "title": "PDF Parallel Numerical Picard Iteration Methods - Springer", "date": "", "ddg_snippet": "We show that the numerical Picard iteration methods admit a min(J M , 1 )-order rate of convergence, where J denotes the number of Picard iterations and M 1 is the number of collocation points. We then propose a class of parallel + solvers so that J Picard iterations can be proceeded simultaneously and nearly constantly.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/content/pdf/10.1007/s10915-023-02156-y.pdf", "content": "We show that the numerical Picard iteration methods admit a min(J M , 1 )-order rate of convergence, where J denotes the number of Picard iterations and M 1 is the number of collocation points. We then propose a class of parallel + solvers so that J Picard iterations can be proceeded simultaneously and nearly constantly."}
+{"idx": 7, "title": "Parallel simulation for sampling under isoperimetry and score-based ...", "date": "", "ddg_snippet": "Technical novelty. Balance between time and Picard directions. Realed works in scientific computation. 4 Parallel Picard method for sampling under isoperimetry 4.1 Algorithm 4.2 Theoretical Guarantees 4.3 Proof sketch of Theorem 4.2: Performance analysis of Algorithm 1", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2412.07435", "content": "Technical novelty. Balance between time and Picard directions. Realed works in scientific computation. 4 Parallel Picard method for sampling under isoperimetry 4.1 Algorithm 4.2 Theoretical Guarantees 4.3 Proof sketch of Theorem 4.2: Performance analysis of Algorithm 1"}
+{"idx": 8, "title": "hands-on-B04-picard.ipynb - Colab", "date": "", "ddg_snippet": "The method generates a sequence of increasingly precise algebraic approximations of the specific exact solution of the first-order differential equation with initial value. As described by Ricardo (2020), in the Picard's Successive Approximation Method an iteration scheme guarantees the solution of the equation y(x) = y0 +∫x x0 f(x, y(x))dx ( 1 ) with IVP (initial-value problem) dy dx = f(x, y ...", "subpage_snippet": "", "source": "colab.research.google.com", "link": "https://colab.research.google.com/github/efurlanm/418/blob/master/hands-on-B04-picard.ipynb", "content": "The method generates a sequence of increasingly precise algebraic approximations of the specific exact solution of the first-order differential equation with initial value. As described by Ricardo (2020), in the Picard's Successive Approximation Method an iteration scheme guarantees the solution of the equation y(x) = y0 +∫x x0 f(x, y(x))dx ( 1 ) with IVP (initial-value problem) dy dx = f(x, y ..."}
+{"idx": 9, "title": "PDF Parallel Simulation for Log-concave Sampling and Score-based Diffusion ...", "date": "", "ddg_snippet": "Algorithm 1 Parallel Picard Method for sampling 1 : Input : x0 ∼ μ0, approximate score function s ≈ ∇f, the number of the iterations in outer loop J, the number of the iteration in inner loop P, the number of time slices N, the length of time slices h, the number of points on each time slices M. 2: for n = 0, . . .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/attachment?id=qtuxDy2qEB&name=pdf", "content": "Algorithm 1 Parallel Picard Method for sampling 1 : Input : x0 ∼ μ0, approximate score function s ≈ ∇f, the number of the iterations in outer loop J, the number of the iteration in inner loop P, the number of time slices N, the length of time slices h, the number of points on each time slices M. 2: for n = 0, . . ."}

data/sampled_jsons/Arun_Reddy_Alexander_Martin_Video-ColBERT_equation_final_similarity_score.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2503.19009] Video-ColBERT: Contextualized Late Interaction ... Video-ColBERT: Contextualized Late Interaction for Text-to ... Video-ColBERT: Contextualized Late Interaction for Text-to ... Publications | Alexander Martin GitHub - yogesh-iitj/Video-ColBERT ColBERT: A complete guide. Me: BERT, can you please ... - Medium CVPR 2025 Open Access Repository", "date": "", "ddg_snippet": "Mar 24, 2025 · Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy , Alexander Martin , Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M. de Melo, Benjamin Van Durme, Rama Chellappa Abstract In this work, we tackle the problem of text-to- video re-trieval (T2VR). Inspired by the success of late interaction techniques in text-document, text-image, and text- video re-trieval, our approach, Video-ColBERT , introduces a simple and eficient mechanism for fine-grained similarity assess-ment between queries and videos . Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy1,2* Alexander Martin2* Eugene Yang2,3 Andrew Yates2,3 Kate Sanders2 Kenton Murray2,3 Reno Kriz2,3 Celso M. de Melo4 Benjamin Van Durme2,3 Rama Chellappa2 Aug 20, 2025 · Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy *, Alexander Martin *, Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M Melo, Benjamin Van Durme, and Rama Chellappa In IEEE Conference on Computer Vision and Pattern Recognition, Jun 2025 Abs PDF This repository implements Video-ColBERT , a contextualized late interaction model for text-to- video retrieval. Video-ColBERT performs fine-grained token-wise interactions between text queries and video content. This script demonstrates the model with random inputs, showing how similarity matrices ... Using Eq and Ed, ColBERT computes the relevance score between q and d via late interaction, which is defined as a summation of maximum similarity (MaxSim) operators. Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy , Alexander Martin , Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M. de Melo, Benjamin Van Durme, Rama Chellappa; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025, pp. 19691-19701", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.19009", "content": "Mar 24, 2025 · Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy , Alexander Martin , Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M. de Melo, Benjamin Van Durme, Rama Chellappa Abstract In this work, we tackle the problem of text-to- video re-trieval (T2VR). Inspired by the success of late interaction techniques in text-document, text-image, and text- video re-trieval, our approach, Video-ColBERT , introduces a simple and eficient mechanism for fine-grained similarity assess-ment between queries and videos . Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy1,2* Alexander Martin2* Eugene Yang2,3 Andrew Yates2,3 Kate Sanders2 Kenton Murray2,3 Reno Kriz2,3 Celso M. de Melo4 Benjamin Van Durme2,3 Rama Chellappa2 Aug 20, 2025 · Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy *, Alexander Martin *, Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M Melo, Benjamin Van Durme, and Rama Chellappa In IEEE Conference on Computer Vision and Pattern Recognition, Jun 2025 Abs PDF This repository implements Video-ColBERT , a contextualized late interaction model for text-to- video retrieval. Video-ColBERT performs fine-grained token-wise interactions between text queries and video content. This script demonstrates the model with random inputs, showing how similarity matrices ... Using Eq and Ed, ColBERT computes the relevance score between q and d via late interaction, which is defined as a summation of maximum similarity (MaxSim) operators. Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy , Alexander Martin , Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M. de Melo, Benjamin Van Durme, Rama Chellappa; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025, pp. 19691-19701"}
+{"idx": 1, "title": "Video-ColBERT: Contextualized Late Interaction for Text-to ...", "date": "", "ddg_snippet": "Abstract In this work, we tackle the problem of text-to- video re-trieval (T2VR). Inspired by the success of late interaction techniques in text-document, text-image, and text- video re-trieval, our approach, Video-ColBERT , introduces a simple and eficient mechanism for fine-grained similarity assess-ment between queries and videos .", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Reddy_Video-ColBERT_Contextualized_Late_Interaction_for_Text-to-Video_Retrieval_CVPR_2025_paper.pdf", "content": "Abstract In this work, we tackle the problem of text-to- video re-trieval (T2VR). Inspired by the success of late interaction techniques in text-document, text-image, and text- video re-trieval, our approach, Video-ColBERT , introduces a simple and eficient mechanism for fine-grained similarity assess-ment between queries and videos ."}
+{"idx": 2, "title": "Video-ColBERT: Contextualized Late Interaction for Text-to ...", "date": "", "ddg_snippet": "Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy1,2* Alexander Martin2* Eugene Yang2,3 Andrew Yates2,3 Kate Sanders2 Kenton Murray2,3 Reno Kriz2,3 Celso M. de Melo4 Benjamin Van Durme2,3 Rama Chellappa2", "subpage_snippet": "", "source": "www.celsodemelo.net", "link": "http://www.celsodemelo.net/static/publications/Video_ColBERT_CVPR_2025_DistA.pdf", "content": "Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy1,2* Alexander Martin2* Eugene Yang2,3 Andrew Yates2,3 Kate Sanders2 Kenton Murray2,3 Reno Kriz2,3 Celso M. de Melo4 Benjamin Van Durme2,3 Rama Chellappa2"}
+{"idx": 3, "title": "Publications | Alexander Martin", "date": "", "ddg_snippet": "Aug 20, 2025 · Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy *, Alexander Martin *, Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M Melo, Benjamin Van Durme, and Rama Chellappa In IEEE Conference on Computer Vision and Pattern Recognition, Jun 2025 Abs PDF", "subpage_snippet": "", "source": "alexmartin1722.github.io", "link": "https://alexmartin1722.github.io/publications/", "content": "Aug 20, 2025 · Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy *, Alexander Martin *, Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M Melo, Benjamin Van Durme, and Rama Chellappa In IEEE Conference on Computer Vision and Pattern Recognition, Jun 2025 Abs PDF"}
+{"idx": 4, "title": "GitHub - yogesh-iitj/Video-ColBERT", "date": "", "ddg_snippet": "This repository implements Video-ColBERT , a contextualized late interaction model for text-to- video retrieval. Video-ColBERT performs fine-grained token-wise interactions between text queries and video content. This script demonstrates the model with random inputs, showing how similarity matrices ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/yogesh-iitj/Video-ColBERT", "content": "This repository implements Video-ColBERT , a contextualized late interaction model for text-to- video retrieval. Video-ColBERT performs fine-grained token-wise interactions between text queries and video content. This script demonstrates the model with random inputs, showing how similarity matrices ..."}
+{"idx": 5, "title": "ColBERT: A complete guide. Me: BERT, can you please ... - Medium", "date": "", "ddg_snippet": "Using Eq and Ed, ColBERT computes the relevance score between q and d via late interaction, which is defined as a summation of maximum similarity (MaxSim) operators.", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/@varun030403/colbert-a-complete-guide-1552468335ae", "content": "Using Eq and Ed, ColBERT computes the relevance score between q and d via late interaction, which is defined as a summation of maximum similarity (MaxSim) operators."}
+{"idx": 6, "title": "Contextualized Late Interaction for Text-to-Video Retrieval", "date": "", "ddg_snippet": "Video - ColBERT is built upon 3 main components: a fine-grained spatial and temporal token-wise interaction, query and visual expansions, and a dual sigmoid loss ...", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/paper/153378", "content": "Video - ColBERT is built upon 3 main components: a fine-grained spatial and temporal token-wise interaction, query and visual expansions, and a dual sigmoid loss ..."}
+{"idx": 7, "title": "CVPR 2025 Open Access Repository", "date": "", "ddg_snippet": "Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy , Alexander Martin , Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M. de Melo, Benjamin Van Durme, Rama Chellappa; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025, pp. 19691-19701", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/html/Reddy_Video-ColBERT_Contextualized_Late_Interaction_for_Text-to-Video_Retrieval_CVPR_2025_paper.html", "content": "Video-ColBERT : Contextualized Late Interaction for Text-to- Video Retrieval Arun Reddy , Alexander Martin , Eugene Yang, Andrew Yates, Kate Sanders, Kenton Murray, Reno Kriz, Celso M. de Melo, Benjamin Van Durme, Rama Chellappa; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025, pp. 19691-19701"}
+{"idx": 8, "title": "A Scientific Question Answering Dataset from Peer Reviews", "date": "", "ddg_snippet": "19 Feb 2025 — We analyze the semantic similarity between the final and original questions, finding that 90 % percent 90 90\\% 90 % of questions have a ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.13668v1", "content": "19 Feb 2025 — We analyze the semantic similarity between the final and original questions, finding that 90 % percent 90 90\\% 90 % of questions have a ..."}
+{"idx": 9, "title": "Computer Vision and Pattern Recognition Mar 2025", "date": "", "ddg_snippet": "Title: Video - ColBERT : Contextualized Late Interaction for Text-to-Video Retrieval. Arun Reddy , Alexander Martin , Eugene Yang, Andrew Yates, Kate Sanders ...", "subpage_snippet": "", "source": "www.arxiv.org", "link": "https://www.arxiv.org/list/cs.CV/2025-03?skip=1650&show=1000", "content": "Title: Video - ColBERT : Contextualized Late Interaction for Text-to-Video Retrieval. Arun Reddy , Alexander Martin , Eugene Yang, Andrew Yates, Kate Sanders ..."}

data/sampled_jsons/BIT-VO_Murai_binary_features_focal_plane_visual_odometry.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Bit - Wikipedia", "date": "", "ddg_snippet": "The bit represents a logical state with one of two possible values. These values are most commonly represented as either \"1\" or \"0\", but other representations such as true / false, yes / no, on / off, or + / − are also widely used.", "subpage_snippet": "", "source": "en.m.wikipedia.org", "link": "https://en.m.wikipedia.org/wiki/Bit", "content": "The bit represents a logical state with one of two possible values. These values are most commonly represented as either \"1\" or \"0\", but other representations such as true / false, yes / no, on / off, or + / − are also widely used."}
+{"idx": 1, "title": "BIT Definition & Meaning - Merriam-Webster", "date": "", "ddg_snippet": "The meaning of BIT is the biting or cutting edge or part of a tool. How to use bit in a sentence.", "subpage_snippet": "", "source": "www.merriam-webster.com", "link": "https://www.merriam-webster.com/dictionary/bit", "content": "The meaning of BIT is the biting or cutting edge or part of a tool. How to use bit in a sentence."}
+{"idx": 2, "title": "What is bit (binary digit) in computing? - TechTarget", "date": "", "ddg_snippet": "Jun 6, 2025 · Bits are stored in memory through the use of capacitors that hold electrical charges. The charge determines the state of each bit which, in turn, determines the bit 's value. Various combinations of bits -- combinations of 0s and 1s -- are used to represent numbers larger than 1.", "subpage_snippet": "", "source": "www.techtarget.com", "link": "https://www.techtarget.com/whatis/definition/bit-binary-digit", "content": "Jun 6, 2025 · Bits are stored in memory through the use of capacitors that hold electrical charges. The charge determines the state of each bit which, in turn, determines the bit 's value. Various combinations of bits -- combinations of 0s and 1s -- are used to represent numbers larger than 1."}
+{"idx": 3, "title": "Bit Definition - What is a bit in data storage? - TechTerms.com", "date": "", "ddg_snippet": "Apr 20, 2013 · A bit (short for \" binary digit \") is the smallest unit of measurement used to quantify computer data. It contains a single binary value of 0 or 1. While a single bit can define a boolean value of True (1) or False (0), an individual bit has little other use.", "subpage_snippet": "", "source": "techterms.com", "link": "https://techterms.com/definition/bit", "content": "Apr 20, 2013 · A bit (short for \" binary digit \") is the smallest unit of measurement used to quantify computer data. It contains a single binary value of 0 or 1. While a single bit can define a boolean value of True (1) or False (0), an individual bit has little other use."}
+{"idx": 4, "title": "What is BIT (Binary DigIT)? - Computer Hope", "date": "", "ddg_snippet": "Sep 7, 2025 · Sometimes abbreviated as b (lowercase), bit is short for binary digit . It's a single unit of information with a value of either 0 or 1 (off or on, false or true, low or high).", "subpage_snippet": "", "source": "www.computerhope.com", "link": "https://www.computerhope.com/jargon/b/bit.htm", "content": "Sep 7, 2025 · Sometimes abbreviated as b (lowercase), bit is short for binary digit . It's a single unit of information with a value of either 0 or 1 (off or on, false or true, low or high)."}
+{"idx": 5, "title": "Bits and Bytes", "date": "", "ddg_snippet": "Everything in a computer is 0's and 1's. The bit stores just a 0 or 1: it's the smallest building block of storage.", "subpage_snippet": "", "source": "web.stanford.edu", "link": "https://web.stanford.edu/class/cs101/bits-bytes.html", "content": "Everything in a computer is 0's and 1's. The bit stores just a 0 or 1: it's the smallest building block of storage."}
+{"idx": 6, "title": "Bit - definition of bit by The Free Dictionary", "date": "", "ddg_snippet": "Define bit . bit synonyms, bit pronunciation, bit translation, English dictionary definition of bit . n. 1. A small portion, degree, or amount: a bit of lint; a bit of luck.", "subpage_snippet": "", "source": "www.thefreedictionary.com", "link": "https://www.thefreedictionary.com/bit", "content": "Define bit . bit synonyms, bit pronunciation, bit translation, English dictionary definition of bit . n. 1. A small portion, degree, or amount: a bit of lint; a bit of luck."}
+{"idx": 7, "title": "Bits (binary digits ) (article) | Khan Academy", "date": "", "ddg_snippet": "Computers store information using bits . A bit (short for \"binary digit\") stores either the value 0 or 1 .", "subpage_snippet": "", "source": "www.khanacademy.org", "link": "https://www.khanacademy.org/computing/computers-and-internet/xcae6f4a7ff015e7d:digital-information/xcae6f4a7ff015e7d:bits-and-bytes/a/bits-binary-digits", "content": "Computers store information using bits . A bit (short for \"binary digit\") stores either the value 0 or 1 ."}
+{"idx": 8, "title": "BIT | definition in the Cambridge English Dictionary", "date": "", "ddg_snippet": "For the competition they had to write, shoot, and edit a one-minute comedy bit . Bits are basically jokes, but in the context of a play or movie, they usually involve a physical element and more than one person.", "subpage_snippet": "", "source": "dictionary.cambridge.org", "link": "https://dictionary.cambridge.org/us/dictionary/english/bit", "content": "For the competition they had to write, shoot, and edit a one-minute comedy bit . Bits are basically jokes, but in the context of a play or movie, they usually involve a physical element and more than one person."}
+{"idx": 9, "title": "What is a bit? Bits and bytes explained - IONOS", "date": "", "ddg_snippet": "Dec 8, 2022 · A bit is the smallest unit of electronic information; multiple bits form a byte. Whereas the storage capacity of hard drives is given in bytes, data transfer rates are shown in bits.", "subpage_snippet": "", "source": "www.ionos.com", "link": "https://www.ionos.com/digitalguide/websites/web-development/what-is-a-bit/", "content": "Dec 8, 2022 · A bit is the smallest unit of electronic information; multiple bits form a byte. Whereas the storage capacity of hard drives is given in bytes, data transfer rates are shown in bits."}

data/sampled_jsons/Bach_et_al._2023_'The_impact_of_modeling_decisions_in_statistical_profiling'_abstract_year_2023.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "(PDF) The impact of modeling decisions in statistical profiling", "date": "", "ddg_snippet": "Abstract and Figures. Statistical profiling of job seekers is an attractive option to guide the activities of public employment services. statistical profiling of job seekers as an empirical use case, we show that modeling decisions in a typical data.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/374392867_The_impact_of_modeling_decisions_in_statistical_profiling", "content": "Abstract and Figures. Statistical profiling of job seekers is an attractive option to guide the activities of public employment services. statistical profiling of job seekers as an empirical use case, we show that modeling decisions in a typical data."}
+{"idx": 1, "title": "Ruben L. Bach - Google Scholar", "date": "", "ddg_snippet": "2020. The impact of modeling decisions in statistical profiling . RL Bach , C Kern, H Mautner, F Kreuter. Data & Policy 5, e32, 2023 .", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=KczTzXEAAAAJ&hl=en", "content": "2020. The impact of modeling decisions in statistical profiling . RL Bach , C Kern, H Mautner, F Kreuter. Data & Policy 5, e32, 2023 ."}
+{"idx": 2, "title": "Fairness in Algorithmic Profiling : The AMAS Case | Minds and Machines", "date": "", "ddg_snippet": "In their study on algorithmic profiling , Kern et al . (2024) applied different classification methods to predict the risk of becoming LTU with German data. They could show that although the statistical models had a similar level of accuracy they had very different fairness implications.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s11023-024-09706-9", "content": "In their study on algorithmic profiling , Kern et al . (2024) applied different classification methods to predict the risk of becoming LTU with German data. They could show that although the statistical models had a similar level of accuracy they had very different fairness implications."}
+{"idx": 3, "title": "Statistical Profiling as a Targeting Tool: Can It Enhance the Efficiency...", "date": "", "ddg_snippet": "Abstract Digitization has spurred interest in the potential of statistical profiling to improve the tar-geting of active labor market policies. Bach , R. L., Kern, C., Mautner, H., & Kreuter, F. ( 2023 ). The Impact of Modeling Decisions in Statistical Profiling .", "subpage_snippet": "", "source": "www.wifo.ac.at", "link": "https://www.wifo.ac.at/wp-content/uploads/upload-4573/wp_2025_694.pdf", "content": "Abstract Digitization has spurred interest in the potential of statistical profiling to improve the tar-geting of active labor market policies. Bach , R. L., Kern, C., Mautner, H., & Kreuter, F. ( 2023 ). The Impact of Modeling Decisions in Statistical Profiling ."}
+{"idx": 4, "title": "Reconsidering Fairness Through Unawareness From the Perspective...", "date": "", "ddg_snippet": "2023 . The impact of modeling decisions in statistical profiling . Data & Policy 5 ( 2023 ), e32. Barocas et al .2019. Fairness and abstraction in sociotechnical systems. In Proceedings of the conference on fairness, accountability, and transparency. 59–68.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2505.16638v2", "content": "2023 . The impact of modeling decisions in statistical profiling . Data & Policy 5 ( 2023 ), e32. Barocas et al .2019. Fairness and abstraction in sociotechnical systems. In Proceedings of the conference on fairness, accountability, and transparency. 59–68."}
+{"idx": 5, "title": "Ruben Bach (@rub3n_luc) | Aguea", "date": "", "ddg_snippet": "The impact of modeling decisions in statistical profiling - Volume 5.Ruben Bach @rub3n_luc. 27 Aug 2023 . Main question we tackle: how can we optimize the distribution of several treatment options with #DML algorithms while avoiding to treat only those who are already doing fine?", "subpage_snippet": "", "source": "aguea.net", "link": "https://aguea.net/rub3n_luc", "content": "The impact of modeling decisions in statistical profiling - Volume 5.Ruben Bach @rub3n_luc. 27 Aug 2023 . Main question we tackle: how can we optimize the distribution of several treatment options with #DML algorithms while avoiding to treat only those who are already doing fine?"}
+{"idx": 6, "title": "The Value of Prediction in Identifying the Worst-Off", "date": "", "ddg_snippet": "Bach , R. L., Kern, C., Mautner, H., and Kreuter, F. The impact of modeling decisions in statistical profiling .Kern, C., Bach , R., Mautner, H., and Kreuter, F. When Small Decisions Have Big Impact : Fairness Implica-tions of Algorithmic Profiling Schemes.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=26JsumCG0z", "content": "Bach , R. L., Kern, C., Mautner, H., and Kreuter, F. The impact of modeling decisions in statistical profiling .Kern, C., Bach , R., Mautner, H., and Kreuter, F. When Small Decisions Have Big Impact : Fairness Implica-tions of Algorithmic Profiling Schemes."}
+{"idx": 7, "title": "When Small Decisions Have Big Impact : Fairness Implications of...", "date": "", "ddg_snippet": "Additional Key Words and Phrases: Algorithmic fairness, modeling decisions , statistical profiling , machine learning pipeline. ACM Reference Format: Christoph Kern, Ruben Bach , Hannah Mautner, and Frauke Kreuter. 2024. When Small Decisions Have Big Impact : Fairness...", "subpage_snippet": "", "source": "epub.ub.uni-muenchen.de", "link": "https://epub.ub.uni-muenchen.de/122528/1/3689485.pdf", "content": "Additional Key Words and Phrases: Algorithmic fairness, modeling decisions , statistical profiling , machine learning pipeline. ACM Reference Format: Christoph Kern, Ruben Bach , Hannah Mautner, and Frauke Kreuter. 2024. When Small Decisions Have Big Impact : Fairness..."}
+{"idx": 8, "title": "When Small Decisions Have Big Impact : Fairness Implications of...", "date": "", "ddg_snippet": "A variety of statistical profiling systems were developed in several countries. Comprehensive reviews of existing profiling implementations are presented in Loxha and Morgandi [63], Desiere et al . 2023 . Fairness and Machine Learning: Limitations and Opportunities. MIT Press.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1145/3689485", "content": "A variety of statistical profiling systems were developed in several countries. Comprehensive reviews of existing profiling implementations are presented in Loxha and Morgandi [63], Desiere et al . 2023 . Fairness and Machine Learning: Limitations and Opportunities. MIT Press."}
+{"idx": 9, "title": "Int. j. adv. multidisc. res. stud. 2023 ; 3(6):2117-2123", "date": "", "ddg_snippet": "Modeling the Climate Impact of Early Leak Detection via Continuous Monitoring. 1.Understanding the modeling of these impacts is essential for quantifying benefits and guiding investment and policy decisions (Stolaroff et al ., 2012, Ocko and Hamburg, 2022) [53, 32].", "subpage_snippet": "", "source": "www.multiresearchjournal.com", "link": "https://www.multiresearchjournal.com/admin/uploads/archives/archive-1754480899.pdf", "content": "Modeling the Climate Impact of Early Leak Detection via Continuous Monitoring. 1.Understanding the modeling of these impacts is essential for quantifying benefits and guiding investment and policy decisions (Stolaroff et al ., 2012, Ocko and Hamburg, 2022) [53, 32]."}

data/sampled_jsons/Beautiful_Soup_Python_library_primary_function.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Beautiful Soup Documentation — Beautiful Soup 4.13.0 documentation", "date": "", "ddg_snippet": "Beautiful Soup is a Python library for parsing HTML and XML documents, offering tools to navigate, search, and modify parse trees.", "subpage_snippet": "", "source": "www.crummy.com", "link": "https://www.crummy.com/software/BeautifulSoup/bs4/doc/", "content": "Beautiful Soup is a Python library for parsing HTML and XML documents, offering tools to navigate, search, and modify parse trees."}
+{"idx": 1, "title": "beautifulsoup4 · PyPI", "date": "", "ddg_snippet": "BeautifulSoup4 is a screen-scraping library for parsing HTML and XML documents.", "subpage_snippet": "", "source": "pypi.org", "link": "https://pypi.org/project/beautifulsoup4/", "content": "BeautifulSoup4 is a screen-scraping library for parsing HTML and XML documents."}
+{"idx": 2, "title": "Implementing Web Scraping in Python with BeautifulSoup", "date": "", "ddg_snippet": "BeautifulSoup is a Python library used for web scraping. It helps parse HTML and XML documents making it easy to navigate and extract specific parts of a webpage. This article explains the steps of web scraping using BeautifulSoup . Steps involved in web scraping Send an HTTP Request: Use the requests library to send a request to the webpage URL and get the HTML content in response. Parse the ...", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/python/implementing-web-scraping-python-beautiful-soup/", "content": "BeautifulSoup is a Python library used for web scraping. It helps parse HTML and XML documents making it easy to navigate and extract specific parts of a webpage. This article explains the steps of web scraping using BeautifulSoup . Steps involved in web scraping Send an HTTP Request: Use the requests library to send a request to the webpage URL and get the HTML content in response. Parse the ..."}
+{"idx": 3, "title": "10 Most Important Functions in BeautifulSoup - CodersLegacy", "date": "", "ddg_snippet": "Beautiful Soup is a Python library that is commonly used for web scraping purposes. It is a very powerful tool for extracting and parsing data from HTML and XML files. Beautiful Soup provides several functions that make web scraping a lot easier. In this article, we will look at the 10 most important BeautifulSoup functions and how to use them to parse data.", "subpage_snippet": "", "source": "coderslegacy.com", "link": "https://coderslegacy.com/10-most-important-functions-in-beautifulsoup/", "content": "Beautiful Soup is a Python library that is commonly used for web scraping purposes. It is a very powerful tool for extracting and parsing data from HTML and XML files. Beautiful Soup provides several functions that make web scraping a lot easier. In this article, we will look at the 10 most important BeautifulSoup functions and how to use them to parse data."}
+{"idx": 4, "title": "The Complete BeautifulSoup Cheatsheet with Examples", "date": "", "ddg_snippet": "This cheatsheet covers the full BeautifulSoup 4 API with practical examples. It provides a comprehensive guide to web scraping and HTML parsing using Python's BeautifulSoup library .", "subpage_snippet": "", "source": "proxiesapi.com", "link": "https://proxiesapi.com/articles/the-complete-beautifulsoup-cheatsheet-with-examples", "content": "This cheatsheet covers the full BeautifulSoup 4 API with practical examples. It provides a comprehensive guide to web scraping and HTML parsing using Python's BeautifulSoup library ."}
+{"idx": 5, "title": "beautifulsoup4 - Documentation - Technical Manuals", "date": "", "ddg_snippet": "What is Beautiful Soup ? Beautiful Soup is a Python library for parsing HTML and XML documents. It creates a parse tree from the document and provides methods to navigate and search through the parse tree. Essentially, it makes it easy to extract data from HTML and XML files, even if those files are poorly formatted or incomplete.", "subpage_snippet": "", "source": "manuals.muthu.co", "link": "https://manuals.muthu.co/posts/python-modules/beautifulsoup4.html", "content": "What is Beautiful Soup ? Beautiful Soup is a Python library for parsing HTML and XML documents. It creates a parse tree from the document and provides methods to navigate and search through the parse tree. Essentially, it makes it easy to extract data from HTML and XML files, even if those files are poorly formatted or incomplete."}
+{"idx": 6, "title": "BeautifulSoup Cheatsheet with Code Samples | ScrapingAnt", "date": "", "ddg_snippet": "Introduction BeautifulSoup is a powerful library in Python used for web scraping and parsing HTML and XML documents. If you're looking to extract data from web pages, BeautifulSoup is an essential tool to learn. In this tutorial, we will explore the core concepts of BeautifulSoup with detailed code samples and explanations to help you get started.", "subpage_snippet": "", "source": "scrapingant.com", "link": "https://scrapingant.com/blog/beautifulsoup-cheatsheet", "content": "Introduction BeautifulSoup is a powerful library in Python used for web scraping and parsing HTML and XML documents. If you're looking to extract data from web pages, BeautifulSoup is an essential tool to learn. In this tutorial, we will explore the core concepts of BeautifulSoup with detailed code samples and explanations to help you get started."}
+{"idx": 7, "title": "PDF Beautiful Soup Documentation — Beautiful Soup v4.0.0 documentation", "date": "", "ddg_snippet": "Beautiful Soup Documentation Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work.", "subpage_snippet": "", "source": "sethc23.github.io", "link": "https://sethc23.github.io/wiki/Python/Beautiful_Soup_Documentation.pdf", "content": "Beautiful Soup Documentation Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work."}
+{"idx": 8, "title": "Beautiful Soup: Python Web Scraping Code Explained | AnSoup", "date": "", "ddg_snippet": "Beautiful Soup is a library designed for screen-scraping HTML and XML and sits atop an HTML or XML parser, providing Pythonic idioms for iterating, searching, and modifying the parse tree. The code for Beautiful Soup is packaged as Python 2 code and is automatically converted to Python 3 code upon installation.", "subpage_snippet": "", "source": "ansoup.com", "link": "https://ansoup.com/article/what-does-beautiful-soup-code-look-like", "content": "Beautiful Soup is a library designed for screen-scraping HTML and XML and sits atop an HTML or XML parser, providing Pythonic idioms for iterating, searching, and modifying the parse tree. The code for Beautiful Soup is packaged as Python 2 code and is automatically converted to Python 3 code upon installation."}
+{"idx": 9, "title": "BeautifulSoup4 Module - Python - GeeksforGeeks", "date": "", "ddg_snippet": "BeautifulSoup4 is a user-friendly Python library designed for parsing HTML and XML documents. It simplifies the process of web scraping by allowing developers to effortlessly navigate, search and modify the parse tree of a webpage. With BeautifulSoup4, we can extract specific elements, attributes and text from complex web pages using intuitive methods. This library abstracts away the ...", "subpage_snippet": "", "source": "www.geeksforgeeks.org", "link": "https://www.geeksforgeeks.org/python/beautifulsoup4-module-python/", "content": "BeautifulSoup4 is a user-friendly Python library designed for parsing HTML and XML documents. It simplifies the process of web scraping by allowing developers to effortlessly navigate, search and modify the parse tree of a webpage. With BeautifulSoup4, we can extract specific elements, attributes and text from complex web pages using intuitive methods. This library abstracts away the ..."}

data/sampled_jsons/Beimel_Dynamic_Algorithms_Adaptive_Adversary_returns_cost_solution_optimization.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "The Cost of Compression: Tight Quadratic Black-Box Attacks on", "date": "", "ddg_snippet": "... adaptive setting is well studied across multiple areas, including statistical queries [ 18 , 26 , 29 , 23 , 16 , 6 ] , sketching and streaming ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.16345v1", "content": "... adaptive setting is well studied across multiple areas, including statistical queries [ 18 , 26 , 29 , 23 , 16 , 6 ] , sketching and streaming ..."}
+{"idx": 1, "title": "STOC 1999", "date": "", "ddg_snippet": "Gen-Huey Chen , Ming-Yang Kao , Yuh-Dauh Lyuu , Hsing-Kuo Wong : Optimal Buy-and-Hold Strategies for Financial Markets with Bounded Daily Returns .", "subpage_snippet": "", "source": "sigmod.org", "link": "https://sigmod.org/publications/dblp/db/conf/stoc/stoc1999.html", "content": "Gen-Huey Chen , Ming-Yang Kao , Yuh-Dauh Lyuu , Hsing-Kuo Wong : Optimal Buy-and-Hold Strategies for Financial Markets with Bounded Daily Returns ."}
+{"idx": 2, "title": "A Simple and Robust Protocol for Distributed Counting", "date": "", "ddg_snippet": "... a precise way) the dependencies between the internal randomness of the algorithm and its inputs, thereby making it easier to argue about the adaptive ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.05870v1", "content": "... a precise way) the dependencies between the internal randomness of the algorithm and its inputs, thereby making it easier to argue about the adaptive ..."}
+{"idx": 3, "title": "STOC 2020: Proceedings of the 52nd Annual ACM SIGACT Symposium", "date": "", "ddg_snippet": "... through a variety of new techniques, including a novel way to set up a recursive dynamic program to guess significant parts of an optimal solution ...", "subpage_snippet": "", "source": "acm-stoc.org", "link": "https://acm-stoc.org/stoc2020/toc.html", "content": "... through a variety of new techniques, including a novel way to set up a recursive dynamic program to guess significant parts of an optimal solution ..."}
+{"idx": 4, "title": "COLT 2025 Book of Abstracts", "date": "", "ddg_snippet": "... sampling in relative Fisher information via the Proximal Sampler algorithm , which is an approximate proximal discretization of the Langevin dynamics ...", "subpage_snippet": "", "source": "learningtheory.org", "link": "https://learningtheory.org/colt2025/abstracts.html", "content": "... sampling in relative Fisher information via the Proximal Sampler algorithm , which is an approximate proximal discretization of the Langevin dynamics ..."}
+{"idx": 5, "title": "CRYPTO 2010: Program", "date": "", "ddg_snippet": "We also show that in most cryptographic applications, the algorithm 's efficiency comes at almost no cost in asymptotic security.", "subpage_snippet": "", "source": "www.iacr.org", "link": "https://www.iacr.org/conferences/crypto2010/accepted.html", "content": "We also show that in most cryptographic applications, the algorithm 's efficiency comes at almost no cost in asymptotic security."}
+{"idx": 6, "title": "Shota Yamada", "date": "", "ddg_snippet": "... techniques to prove adaptive ... In more detail, our adversary is not restricted to use an honest evaluation algorithm to run pirated software.", "subpage_snippet": "", "source": "www.iacr.org", "link": "https://www.iacr.org/cryptodb/data/author.php?authorkey=7516", "content": "... techniques to prove adaptive ... In more detail, our adversary is not restricted to use an honest evaluation algorithm to run pirated software."}
+{"idx": 7, "title": "ECCC - Reports by year", "date": "", "ddg_snippet": "... measure of cost for algorithms with infrequent spikes in memory usage in the context of technologies such as cloud computing that allow dynamic ...", "subpage_snippet": "", "source": "eccc.weizmann.ac.il", "link": "https://eccc.weizmann.ac.il/year/2023/", "content": "... measure of cost for algorithms with infrequent spikes in memory usage in the context of technologies such as cloud computing that allow dynamic ..."}
+{"idx": 8, "title": "Kasper Green Larsen", "date": "", "ddg_snippet": "... successful boosting algorithms , such as the iconic AdaBoost, produce voting classifiers, their theoretical performance has long remained sub-optimal ...", "subpage_snippet": "", "source": "cs.au.dk", "link": "https://cs.au.dk/~larsen/", "content": "... successful boosting algorithms , such as the iconic AdaBoost, produce voting classifiers, their theoretical performance has long remained sub-optimal ..."}
+{"idx": 9, "title": "Giuseppe Persiano | Chatting and drinking in Florence, March", "date": "", "ddg_snippet": "... algorithm and the preceding membership algorithm are optimal, and in particular that there is an inherent complexity gap in these problems between no ...", "subpage_snippet": "", "source": "giuper.github.io", "link": "https://giuper.github.io/", "content": "... algorithm and the preceding membership algorithm are optimal, and in particular that there is an inherent complexity gap in these problems between no ..."}

data/sampled_jsons/Beimel_differential_privacy_adaptive_queries_abstract_year_2022.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "TPDP 2020 – Theory and Practice of Differential Privacy", "date": "", "ddg_snippet": "Differentially Private Normalizing Flows for Privacy -Preserving Density Estimation, by Chris Waites and Rachel Cummings", "subpage_snippet": "", "source": "tpdp.journalprivacyconfidentiality.org", "link": "https://tpdp.journalprivacyconfidentiality.org/2020/", "content": "Differentially Private Normalizing Flows for Privacy -Preserving Density Estimation, by Chris Waites and Rachel Cummings"}
+{"idx": 1, "title": "privacy | An Ergodic Walk", "date": "", "ddg_snippet": "SCOPE The focus of this special issue is on distributed information acquisition, estimation, and adaptive learning for security and privacy in the ...", "subpage_snippet": "", "source": "ergodicity.net", "link": "https://ergodicity.net/tag/privacy/", "content": "SCOPE The focus of this special issue is on distributed information acquisition, estimation, and adaptive learning for security and privacy in the ..."}
+{"idx": 2, "title": "COLT 2025 Book of Abstracts", "date": "", "ddg_snippet": "Abstract : Existing data-dependent and best-of-both-worlds regret bounds for multi-armed bandits problems have limited adaptivity as they are either ...", "subpage_snippet": "", "source": "learningtheory.org", "link": "https://learningtheory.org/colt2025/abstracts.html", "content": "Abstract : Existing data-dependent and best-of-both-worlds regret bounds for multi-armed bandits problems have limited adaptivity as they are either ..."}
+{"idx": 3, "title": "One Attack to Rule Them All: Tight Quadratic Bounds for", "date": "", "ddg_snippet": "... queries (Steinke and Ullman, 2015) and specific MinHash cardinality sketches (Ahmadian and Cohen, 2024) established that this is tight in that they ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.06370v2", "content": "... queries (Steinke and Ullman, 2015) and specific MinHash cardinality sketches (Ahmadian and Cohen, 2024) established that this is tight in that they ..."}
+{"idx": 4, "title": "Piquant𝜀: Private Quantile Estimation in the Two-Server Model", "date": "", "ddg_snippet": "Local differential privacy (LDP) offers strong protection but lower accuracy than central DP, which assumes a trusted aggregator.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.14035v1", "content": "Local differential privacy (LDP) offers strong protection but lower accuracy than central DP, which assumes a trusted aggregator."}
+{"idx": 5, "title": "Giuseppe Persiano | Chatting and drinking in Florence, March", "date": "", "ddg_snippet": "Our data structure supports storing a set of n key-value pairs from [u]X[u] using s words of space and answering key lookup queries in t=O(lg( u/n ...", "subpage_snippet": "", "source": "giuper.github.io", "link": "https://giuper.github.io/", "content": "Our data structure supports storing a set of n key-value pairs from [u]X[u] using s words of space and answering key lookup queries in t=O(lg( u/n ..."}
+{"idx": 6, "title": "Iftach Haitner", "date": "", "ddg_snippet": "In distributed differential privacy , multiple parties collaborate to analyze their combined data while each party protects the confidentiality of its ...", "subpage_snippet": "", "source": "www.iacr.org", "link": "https://www.iacr.org/cryptodb/data/author.php?authorkey=1707", "content": "In distributed differential privacy , multiple parties collaborate to analyze their combined data while each party protects the confidentiality of its ..."}
+{"idx": 7, "title": "Papers from EUROCRYPT 2020", "date": "", "ddg_snippet": "Our adaptively secure ABE for DFA relies on a new combinatorial mechanism avoiding the exponential security loss in the number of states when naively ...", "subpage_snippet": "", "source": "www.iacr.org", "link": "https://www.iacr.org/cryptodb/data/conf.php?year=2020&venue=eurocrypt", "content": "Our adaptively secure ABE for DFA relies on a new combinatorial mechanism avoiding the exponential security loss in the number of states when naively ..."}
+{"idx": 8, "title": "US9141824B2 - Dynamic database update in multi-server private", "date": "", "ddg_snippet": "... and in particular to enabling database updates to occur concurrently with user queries , without allowing the update process to compromise the privacy ...", "subpage_snippet": "", "source": "patents.google.com", "link": "https://patents.google.com/patent/US9141824B2/en", "content": "... and in particular to enabling database updates to occur concurrently with user queries , without allowing the update process to compromise the privacy ..."}
+{"idx": 9, "title": "Yishay Mansour", "date": "", "ddg_snippet": "Black-Box Differential Privacy for Interactive ML. ... Concurrent Shuffle Differential Privacy Under Continual Observation.", "subpage_snippet": "", "source": "www.csauthors.net", "link": "https://www.csauthors.net/yishay-mansour/", "content": "Black-Box Differential Privacy for Interactive ML. ... Concurrent Shuffle Differential Privacy Under Continual Observation."}

data/sampled_jsons/Black_et_al._(2023)_diffusion_models.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "Diffusion models are a class of flexible generative models trained with an approximation to the log-likelihood objective. However, most use cases of diffusion models are not concerned with likelihoods, but instead with downstream objectives such as human-perceived image quality or drug effectiveness. In this paper, we investigate reinforcement learning methods for directly optimizing diffusion ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2305.13301", "content": "Diffusion models are a class of flexible generative models trained with an approximation to the log-likelihood objective. However, most use cases of diffusion models are not concerned with likelihoods, but instead with downstream objectives such as human-perceived image quality or drug effectiveness. In this paper, we investigate reinforcement learning methods for directly optimizing diffusion ..."}
+{"idx": 1, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "This post is based on the following paper: Training Diffusion Models with Reinforcement Learning Kevin Black *, Michael Janner *, Yilun Du, Ilya Kostrikov, and Sergey Levine arXiv Preprint. If you want to learn more about DDPO, you can check out the paper, website, original code, or get the model weights on Hugging Face. If you want to use DDPO in your own project, check out my PyTorch + LoRA ...", "subpage_snippet": "", "source": "bair.berkeley.edu", "link": "https://bair.berkeley.edu/blog/2023/07/14/ddpo/", "content": "This post is based on the following paper: Training Diffusion Models with Reinforcement Learning Kevin Black *, Michael Janner *, Yilun Du, Ilya Kostrikov, and Sergey Levine arXiv Preprint. If you want to learn more about DDPO, you can check out the paper, website, original code, or get the model weights on Hugging Face. If you want to use DDPO in your own project, check out my PyTorch + LoRA ..."}
+{"idx": 2, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "1. Introduction Diffusion probabilistic models (Sohl-Dickstein et al ., 2015) have recently emerged as the de facto standard for genera-tive modeling in continuous domains. Their flexibility in representing complex, high-dimensional distributions has led to the adoption of diffusion models in applications in-cluding image and video synthesis (Ramesh et al ., 2021; Saharia et al ., 2022; Ho et al ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=pBN8CgrDhE", "content": "1. Introduction Diffusion probabilistic models (Sohl-Dickstein et al ., 2015) have recently emerged as the de facto standard for genera-tive modeling in continuous domains. Their flexibility in representing complex, high-dimensional distributions has led to the adoption of diffusion models in applications in-cluding image and video synthesis (Ramesh et al ., 2021; Saharia et al ., 2022; Ho et al ..."}
+{"idx": 3, "title": "Training Diffusion Models with Reinforcement Learning - DeepAI", "date": "", "ddg_snippet": "Training Diffusion Models with Reinforcement Learning 05/22/ 2023 ∙ by Kevin Black , et al. ∙ ∙", "subpage_snippet": "", "source": "deepai.org", "link": "https://deepai.org/publication/training-diffusion-models-with-reinforcement-learning", "content": "Training Diffusion Models with Reinforcement Learning 05/22/ 2023 ∙ by Kevin Black , et al. ∙ ∙"}
+{"idx": 4, "title": "Training Diffusion Models with Reinforcement Learning", "date": "", "ddg_snippet": "Summary We train diffusion models directly on downstream objectives using reinforcement learning (RL). We do this by posing denoising diffusion as a multi-step decision-making problem, enabling a class of policy gradient algorithms that we call denoising diffusion policy optimization (DDPO).", "subpage_snippet": "", "source": "rl-diffusion.github.io", "link": "https://rl-diffusion.github.io/", "content": "Summary We train diffusion models directly on downstream objectives using reinforcement learning (RL). We do this by posing denoising diffusion as a multi-step decision-making problem, enabling a class of policy gradient algorithms that we call denoising diffusion policy optimization (DDPO)."}
+{"idx": 5, "title": "An unofficial implementation of \"Training Diffusion Models with ...", "date": "", "ddg_snippet": "This repo is an unofficial implementation of \"Training Diffusion Models with Reinforcement Learning\" ( Black et al ., 2023 ). This project is on pause — I underestimated the training time required and I currently do not have the capacity to train this model (lol, noob).", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/superolly/reinforcement-diffusion", "content": "This repo is an unofficial implementation of \"Training Diffusion Models with Reinforcement Learning\" ( Black et al ., 2023 ). This project is on pause — I underestimated the training time required and I currently do not have the capacity to train this model (lol, noob)."}
+{"idx": 6, "title": "[2305.11089] Blackout Diffusion: Generative Diffusion Models in ...", "date": "", "ddg_snippet": "Typical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used to generate samples from Gaussian noise. However, real world data often takes place in discrete-state spaces, including many scientific applications. Here, we develop a theoretical formulation for arbitrary discrete-state Markov processes in the forward ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2305.11089", "content": "Typical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used to generate samples from Gaussian noise. However, real world data often takes place in discrete-state spaces, including many scientific applications. Here, we develop a theoretical formulation for arbitrary discrete-state Markov processes in the forward ..."}
+{"idx": 7, "title": "PDF 1 I Training Diffusion Models With Reinforcement Lear", "date": "", "ddg_snippet": "1 INTRODUCTION Diffusion probabilistic models (Sohl-Dickstein et al ., 2015) have recently emerged as the de facto standard for generative modeling in continuous domains. Their flexibility in representing complex, high-dimensional distributions has led to the adoption of diffusion models in applications including image and video synthesis (Ramesh et al ., 2021; Saharia et al ., 2022; Ho et al ...", "subpage_snippet": "", "source": "rl-diffusion.github.io", "link": "https://rl-diffusion.github.io/files/paper.pdf", "content": "1 INTRODUCTION Diffusion probabilistic models (Sohl-Dickstein et al ., 2015) have recently emerged as the de facto standard for generative modeling in continuous domains. Their flexibility in representing complex, high-dimensional distributions has led to the adoption of diffusion models in applications including image and video synthesis (Ramesh et al ., 2021; Saharia et al ., 2022; Ho et al ..."}
+{"idx": 8, "title": "(PDF) Diffusion Models for Black-Box Optimization - ResearchGate", "date": "", "ddg_snippet": "We propose Denoising Diffusion Optimization Models (DDOM), a new inverse approach for offline black -box optimization based on diffusion models .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/371506196_Diffusion_Models_for_Black-Box_Optimization", "content": "We propose Denoising Diffusion Optimization Models (DDOM), a new inverse approach for offline black -box optimization based on diffusion models ."}
+{"idx": 9, "title": "Diffusion Research Timeline - GitHub", "date": "", "ddg_snippet": "SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis - Podell et al ., 2023 ⚡ Enhanced Stable Diffusion XL (SDXL) for improved detail, diversity, and efficiency. 📑 Cited 1,596 times since 2023", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/jeffreybarry/Diffusion-Research-Timeline", "content": "SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis - Podell et al ., 2023 ⚡ Enhanced Stable Diffusion XL (SDXL) for improved detail, diversity, and efficiency. 📑 Cited 1,596 times since 2023"}

data/sampled_jsons/Blink_of_an_eye_a_simple_theory_for_feature_localization_in_generative_models_Table_1_MMLU.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Blink of an eye: a simple theory for feature localization in generative ...", "date": "", "ddg_snippet": "This phenomenon is not unique to autoregressive models : in diffusion models , key features of the final output are decided in narrow ``critical windows'' of the generation process. In this work we develop a simple , unifying theory to explain this phenomenon using the formalism of stochastic localization samplers.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00921", "content": "This phenomenon is not unique to autoregressive models : in diffusion models , key features of the final output are decided in narrow ``critical windows'' of the generation process. In this work we develop a simple , unifying theory to explain this phenomenon using the formalism of stochastic localization samplers."}
+{"idx": 1, "title": "Blink of an eye: a simple theory for feature localization in generative ...", "date": "", "ddg_snippet": "In this work we de- velop a simple , unifying theory to explain this phenomenon. Using the formalism of stochastic localization for generative models , we show that it emerges generically as the generation process localizes to a sub-population of the distribution it models .", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=QvqnPVGWAN", "content": "In this work we de- velop a simple , unifying theory to explain this phenomenon. Using the formalism of stochastic localization for generative models , we show that it emerges generically as the generation process localizes to a sub-population of the distribution it models ."}
+{"idx": 2, "title": "(PDF) 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. We show that it emerges generically as the generation process localizes to a sub-population of the distribution it models .", "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": "In this work we develop a simple , unifying theory to explain this phenomenon. We show that it emerges generically as the generation process localizes to a sub-population of the distribution it models ."}
+{"idx": 3, "title": "In the Blink of an Eye: A Unified Theory for Feature Emergence in ...", "date": "", "ddg_snippet": "The key insight of our approach is to exploit the powerful formalism for generative models of stochastic localization , which has roots as a proof technique in probability theory . Leveraging our consolidated theory for critical windows, we apply it to different examples of critical windows in theoretical and empirical contexts.", "subpage_snippet": "", "source": "dash.harvard.edu", "link": "https://dash.harvard.edu/items/f3795c57-8ff8-44d2-ae92-1fc5525aeb39", "content": "The key insight of our approach is to exploit the powerful formalism for generative models of stochastic localization , which has roots as a proof technique in probability theory . Leveraging our consolidated theory for critical windows, we apply it to different examples of critical windows in theoretical and empirical contexts."}
+{"idx": 4, "title": "dblp: Blink of an eye: a simple theory for feature localization in ...", "date": "", "ddg_snippet": "Bibliographic details on Blink of an eye : a simple theory for feature localization in generative models .", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/journals/corr/abs-2502-00921", "content": "Bibliographic details on Blink of an eye : a simple theory for feature localization in generative models ."}
+{"idx": 5, "title": "Blink of an eye: a simple theory for feature localization in generative ...", "date": "", "ddg_snippet": "Poster in Workshop: Frontiers in Probabilistic Inference: learning meets Sampling Blink of an eye : a simple theory for feature localization in generative models Marvin Li · Aayush Karan · Sitan Chen", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2025/36105", "content": "Poster in Workshop: Frontiers in Probabilistic Inference: learning meets Sampling Blink of an eye : a simple theory for feature localization in generative models Marvin Li · Aayush Karan · Sitan Chen"}
+{"idx": 6, "title": "Blink of an Eye: A Simple Theory for Feature Localization in Generative ...", "date": "", "ddg_snippet": "We present a concise theoretical framework that explains sudden feature localization events—\"blinks of an eye\"—in diffusion and autoregressive generative models .", "subpage_snippet": "", "source": "marvinfli.github.io", "link": "https://marvinfli.github.io/publication/2025-blink-eye", "content": "We present a concise theoretical framework that explains sudden feature localization events—\"blinks of an eye\"—in diffusion and autoregressive generative models ."}
+{"idx": 7, "title": "Blink of an eye: a simple theory for feature localization in generative ...", "date": "", "ddg_snippet": "This phenomenon is not unique to autoregressive models : in diffusion models , key features of the final output are decided in narrow \"critical windows\" of the generation process. In this work we develop a simple , unifying theory to explain this phenomenon.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2502.00921v1", "content": "This phenomenon is not unique to autoregressive models : in diffusion models , key features of the final output are decided in narrow \"critical windows\" of the generation process. In this work we develop a simple , unifying theory to explain this phenomenon."}
+{"idx": 8, "title": "Blink of an eye: a simple theory for feature localization in generative ...", "date": "", "ddg_snippet": "Large language models can exhibit undesirable and unexpected behavior in the blink of an eye . In a recent Anthropic demo, Claude switched from coding to Googling pictures of Yellowstone, and these...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=nodyP4FLrM", "content": "Large language models can exhibit undesirable and unexpected behavior in the blink of an eye . In a recent Anthropic demo, Claude switched from coding to Googling pictures of Yellowstone, and these..."}
+{"idx": 9, "title": "Sitan Chen June 10, 2025 arXiv:2502.00921v2 [cs.LG] 5 Jun 2025", "date": "", "ddg_snippet": "Blink of an eye : a simple theory for feature localization in generative models", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.00921v2", "content": "Blink of an eye : a simple theory for feature localization in generative models"}

data/sampled_jsons/Blink_of_an_eye_feature_localization_generative_models_ARC_Easy_accuracy_drop.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Learning Localized Generative Models for 3D Point... | OpenReview", "date": "", "ddg_snippet": "This paper studies the unsupervised problem of a generative model exploiting graph convolution. We focus on the generator of a GAN and define methods for graph convolution when the graph is not known in advance as it is the very output of the generator.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=SJeXSo09FQ", "content": "This paper studies the unsupervised problem of a generative model exploiting graph convolution. We focus on the generator of a GAN and define methods for graph convolution when the graph is not known in advance as it is the very output of the generator."}
+{"idx": 1, "title": "Open Closed Eyes in Photos - Online Free Tool", "date": "", "ddg_snippet": "Open Eyes is a web-based service designed to automatically open closed eyes in your photographs. Simply select an image, and our sophisticated AI technology will generate a new photo with naturally open eyes .", "subpage_snippet": "", "source": "overflow.ai", "link": "https://overflow.ai/open-eyes-using-ai", "content": "Open Eyes is a web-based service designed to automatically open closed eyes in your photographs. Simply select an image, and our sophisticated AI technology will generate a new photo with naturally open eyes ."}
+{"idx": 2, "title": "Free Eye Color Change Online", "date": "", "ddg_snippet": "This ensures that the eye color change looks natural and blends seamlessly with the rest of the photo. Use Natural Lighting: Photos taken in natural light tend to have better color accuracy . This makes it easier for the tool to detect and change the eye color effectively.", "subpage_snippet": "", "source": "openart.ai", "link": "https://openart.ai/features/eye-color-change", "content": "This ensures that the eye color change looks natural and blends seamlessly with the rest of the photo. Use Natural Lighting: Photos taken in natural light tend to have better color accuracy . This makes it easier for the tool to detect and change the eye color effectively."}
+{"idx": 3, "title": "Image Animation (Animate Photo) Online Free | GoEnhance AI", "date": "", "ddg_snippet": "From subtle eye - blinks to full-frame camera moves, create scroll-stopping videos with zero editing skills.1. Upload Your Image. Drop a JPG, JPEG, PNG, or WebP up to 4096×4096 px into the editor.", "subpage_snippet": "", "source": "www.goenhance.ai", "link": "https://www.goenhance.ai/ai-video-generator/animate-a-picture", "content": "From subtle eye - blinks to full-frame camera moves, create scroll-stopping videos with zero editing skills.1. Upload Your Image. Drop a JPG, JPEG, PNG, or WebP up to 4096×4096 px into the editor."}
+{"idx": 4, "title": "Gemini - Google DeepMind", "date": "", "ddg_snippet": "Gemini 2.5 is our most intelligent AI model , capable of reasoning through its thoughts before responding, resulting in enhanced performance and improved accuracy .", "subpage_snippet": "", "source": "deepmind.google", "link": "https://deepmind.google/models/gemini/", "content": "Gemini 2.5 is our most intelligent AI model , capable of reasoning through its thoughts before responding, resulting in enhanced performance and improved accuracy ."}
+{"idx": 5, "title": "The Best Free AI Undress Tool for Realistic Photo Transformation", "date": "", "ddg_snippet": "Key Features of the Best Undress AI Platform. Our undress AI app is built to provide excellent service, as well as being easy to use. We stand out by offering a combination of power, precision, and security.", "subpage_snippet": "", "source": "makefilm.ai", "link": "https://makefilm.ai/tools/ai-undresser", "content": "Key Features of the Best Undress AI Platform. Our undress AI app is built to provide excellent service, as well as being easy to use. We stand out by offering a combination of power, precision, and security."}
+{"idx": 6, "title": "DevTalk | After the Nexus Bond Test Launch Honkai... | HoYoLAB", "date": "", "ddg_snippet": "Improve the models and expressions of some characters. The variety of character customization options will be expanded to include additional appearances, clothing, accessories, and other customizable features , along with improvements to animations an...", "subpage_snippet": "", "source": "www.hoyolab.com", "link": "https://www.hoyolab.com/article/41269675", "content": "Improve the models and expressions of some characters. The variety of character customization options will be expanded to include additional appearances, clothing, accessories, and other customizable features , along with improvements to animations an..."}
+{"idx": 7, "title": "Your Perfect Hairstyle is Just a Click Away", "date": "", "ddg_snippet": "Explore infinite possibilities. Lightning fast. Transform your hair in the blink of an eye . Secure and Private. Your pictures are your business.", "subpage_snippet": "", "source": "www.barbergpt.ai", "link": "https://www.barbergpt.ai/", "content": "Explore infinite possibilities. Lightning fast. Transform your hair in the blink of an eye . Secure and Private. Your pictures are your business."}
+{"idx": 8, "title": "Delta Force War Ablaze Update First Console Patch 1.037.105", "date": "", "ddg_snippet": "Deploy immediately to investigate—but remember, your own safety comes first! Mode Roulette Update. PC & Console: Core maps now include Zero Dam ( Easy /Normal) and Layali Grove ( Easy ). Layali Grove (Normal) is temporarily out of rotation.", "subpage_snippet": "", "source": "mp1st.com", "link": "https://mp1st.com/title-updates-and-patches/delta-force-new-season-update-war-ablaze-console-patch-1-037-105", "content": "Deploy immediately to investigate—but remember, your own safety comes first! Mode Roulette Update. PC & Console: Core maps now include Zero Dam ( Easy /Normal) and Layali Grove ( Easy ). Layali Grove (Normal) is temporarily out of rotation."}
+{"idx": 9, "title": "Technical Account Manager at Altium", "date": "", "ddg_snippet": "Proactively generate hypotheses for new apps, internal tools, protocol-facing features , or value-adding extensions to STON.fi. Design and run fast, focused experiments (MVPs, fake door tests, waitlists, landing pages, Wizard of Oz prototypes, etc.).", "subpage_snippet": "", "source": "www.remocate.app", "link": "https://www.remocate.app/jobs/technical-account-manager-3", "content": "Proactively generate hypotheses for new apps, internal tools, protocol-facing features , or value-adding extensions to STON.fi. Design and run fast, focused experiments (MVPs, fake door tests, waitlists, landing pages, Wizard of Oz prototypes, etc.)."}

data/sampled_jsons/Buchholz_causal_representation_learning_2023.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "NeurIPS'24 Workshop on Causal Representation Learning", "date": "", "ddg_snippet": "... world situations where causal effects occur in latent spaces when handling images, videos, and possibly text.Recently, causal representation learning ...", "subpage_snippet": "", "source": "neurips.cc", "link": "https://neurips.cc/virtual/2024/workshop/84746", "content": "... world situations where causal effects occur in latent spaces when handling images, videos, and possibly text.Recently, causal representation learning ..."}
+{"idx": 1, "title": "CausalML", "date": "", "ddg_snippet": "ICLR 2024 (Spotlight; top 3%) (also at: Workshop on Causal Representation Learning @ NeurIPS 2023 , Oral ) ... Causal Representation Learning @ ...", "subpage_snippet": "", "source": "sites.google.com", "link": "https://sites.google.com/view/julius-von-kuegelgen/home/", "content": "ICLR 2024 (Spotlight; top 3%) (also at: Workshop on Causal Representation Learning @ NeurIPS 2023 , Oral ) ... Causal Representation Learning @ ..."}
+{"idx": 2, "title": "Learning Robust Intervention Representations with Delta", "date": "", "ddg_snippet": "Causal representation learning has attracted significant research interest during the past few years, as a means for improving model generalization ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.04492v1", "content": "Causal representation learning has attracted significant research interest during the past few years, as a means for improving model generalization ..."}
+{"idx": 3, "title": "Identifying Weight-Variant Latent Causal Models", "date": "", "ddg_snippet": "Causal representation learning avoids the aforementioned limitation, as it aims to learn a representation that exposes the unknown high-level causal ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2208.14153v6", "content": "Causal representation learning avoids the aforementioned limitation, as it aims to learn a representation that exposes the unknown high-level causal ..."}
+{"idx": 4, "title": "CausalML", "date": "", "ddg_snippet": "ICLR 2024 (Spotlight; top 3%) (also at: Workshop on Causal Representation Learning @ NeurIPS 2023 , Oral ) ... Causal Representation Learning @ ...", "subpage_snippet": "", "source": "www.juliusvonkugelgen.com", "link": "https://www.juliusvonkugelgen.com/", "content": "ICLR 2024 (Spotlight; top 3%) (also at: Workshop on Causal Representation Learning @ NeurIPS 2023 , Oral ) ... Causal Representation Learning @ ..."}
+{"idx": 5, "title": "Bauer team - Helmholtz - Gemeinschaft deutscher", "date": "", "ddg_snippet": "... across environments and tasks in real-world settings is a fundamental, yet unsolved problem and our team aims to develop algorithms that learn causal ...", "subpage_snippet": "", "source": "www.helmholtz.ai", "link": "https://www.helmholtz.ai/applied-ai/ai-research-labs/bauer-team/", "content": "... across environments and tasks in real-world settings is a fundamental, yet unsolved problem and our team aims to develop algorithms that learn causal ..."}
+{"idx": 6, "title": "Stefan Bauer", "date": "", "ddg_snippet": "Diffusion-Based Causal Representation Learning . ... Proceedings of the Eleventh International Conference on Learning Representations , 2023", "subpage_snippet": "", "source": "www.csauthors.net", "link": "https://www.csauthors.net/stefan-bauer/", "content": "Diffusion-Based Causal Representation Learning . ... Proceedings of the Eleventh International Conference on Learning Representations , 2023"}
+{"idx": 7, "title": "Pradeep Ravikumar", "date": "", "ddg_snippet": "Abstract: We consider the linear causal representation learning setting where we observe a linear mixing of $d$ unknown latent factors, which follow ...", "subpage_snippet": "", "source": "www.catalyzex.com", "link": "https://www.catalyzex.com/author/Pradeep+Ravikumar", "content": "Abstract: We consider the linear causal representation learning setting where we observe a linear mixing of $d$ unknown latent factors, which follow ..."}
+{"idx": 8, "title": "Bryon Aragam // University of Chicago", "date": "", "ddg_snippet": "This is the goal of the emerging field of causal representation learning (CRL) that uses causality as a vector for building flexible, interpretable ...", "subpage_snippet": "", "source": "www.bryonaragam.com", "link": "http://www.bryonaragam.com/", "content": "This is the goal of the emerging field of causal representation learning (CRL) that uses causality as a vector for building flexible, interpretable ..."}
+{"idx": 9, "title": "Bryon Aragam // University of Chicago", "date": "", "ddg_snippet": "We revisit this classic method from the comparatively new perspective given by advancements in causal discovery and deep learning , introducing a ...", "subpage_snippet": "", "source": "www.bryonaragam.com", "link": "https://www.bryonaragam.com/", "content": "We revisit this classic method from the comparatively new perspective given by advancements in causal discovery and deep learning , introducing a ..."}

data/sampled_jsons/CALF_Causal_Attention-based_Language_Forecasting_Liu_et_al_2024_abstract.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CALF: Aligning LLMs for Time Series Forecasting via Cross ... CALF | Proceedings of the Thirty-Ninth AAAI Conference on ... dblp: CALF: Aligning LLMs for Time Series Forecasting via ... Large Language Models and Causal Inference in Collaboration ... Are Language Models Actually Useful for Time Series Forecasting? CALF: Aligning LLMs for Time Series Forecasting Are Language Models Actually Useful for Time Series Forecasting ? dblp: CALF : Aligning LLMs for Time Series Forecasting via Cross-modal CALF : Aligning LLMs for Time Series Forecasting Are Language Models Actually Useful for Time Series Forecasting ? CALF : Aligning LLMs for Time Series Forecasting Are Language Models Actually Useful for Time Series Forecasting ? arXiv:2505.02583v1 [cs.LG] 5 May 2025", "date": "", "ddg_snippet": "Mar 12, 2024 · View PDF HTML (experimental) Abstract : Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially ... Aug 5, 2025 · Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data. However ... Apr 17, 2025 · Peiyuan Liu , Hang Guo, Tao Dai, Naiqi Li, Jigang Bao, Xudong Ren, Yong Jiang, Shu-Tao Xia: CALF : Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning. Sep 15, 2025 · Abstract Causal inference has demonstrated significant potential to enhance Natural Language Processing (NLP) models in areas such as predictive accuracy, fairness, robustness, and explainability by capturing causal relationships among variables. Abstract Large language models (LLMs) are being applied to time series forecasting . But are language models actually useful for time series? In a series of ablation studies on three recent and popular LLM- based time series forecasting methods, we find that removing the LLM component or replacing it with a basic attention layer does not degrade forecasting performance—in most cases, the ... To relieve such issues, some pioneering works attempt to introduce the powerful Large Language Models (LLMs) models in time series forecasting by employing the strong context modeling ability of LLMs. For example, Zhou et al . [13] proposed a unified time series analysis framework by adapting and fine-tuning LLMs. Are large language models useful for time series forecasting? Large language models (LLMs) are being applied to time series forecasting . But are language models actually useful for time series? What is calf & AAI 2025? CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning. AAAI 2025: 18915-18923 To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. Does the calf framework improve time series forecasting? Our work on the CALF framework for time series forecasting primarily focuses on enhancing predictive accuracy and generalization . While the positive societal impacts include improved forecasting for critical applications such as weather prediction, energy management, and financial modeling, potential negative impacts should be considered. Does language model pretraining improve performance on time series forecasting tasks? In conclusion, the computational intensity of LLMs in time series forecasting tasks does not result in a corresponding performance improvement. 4.3 Does language model pretraining help performance on forecasting tasks? (RQ3) Our evaluation in this section indicates that pretraining with language datasets is unnecessary for time series forecasting . What are the input and prediction lengths for calf? The input and prediction lengths are both set to 96 . As shown in Tab. 5, our proposed CALF shows significant improvements in both efficiency and accuracy compared with other LLM-based methods. We also provide theoretical complexity analysis for various Transformer-based methods in Appendix E. Ablation on Different Loss Functions. Do LLMs help forecasting in a few-shot setting? Finally, we show that LLMs do not even help forecasting in few-shot settings with 10% of the training data. We discuss the implications of our findings and suggest that time series methods that use large language models are better left to multimodal applications [4, 12, 38] that require textual reasoning. olely on the distilled student model. Recent works have been proposed to address the cross-modal misalignment problem with knowledge distillation [ Liu and Zhang, 2025], which can generally be categorized into black-box distillation [ Liu et al ., 2024a] and white-box distillation[ Liu et al ., 2025a] based on the accessibility of the teacher model ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2403.07300", "content": "Mar 12, 2024 · View PDF HTML (experimental) Abstract : Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially ... Aug 5, 2025 · Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data. However ... Apr 17, 2025 · Peiyuan Liu , Hang Guo, Tao Dai, Naiqi Li, Jigang Bao, Xudong Ren, Yong Jiang, Shu-Tao Xia: CALF : Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning. Sep 15, 2025 · Abstract Causal inference has demonstrated significant potential to enhance Natural Language Processing (NLP) models in areas such as predictive accuracy, fairness, robustness, and explainability by capturing causal relationships among variables. Abstract Large language models (LLMs) are being applied to time series forecasting . But are language models actually useful for time series? In a series of ablation studies on three recent and popular LLM- based time series forecasting methods, we find that removing the LLM component or replacing it with a basic attention layer does not degrade forecasting performance—in most cases, the ... To relieve such issues, some pioneering works attempt to introduce the powerful Large Language Models (LLMs) models in time series forecasting by employing the strong context modeling ability of LLMs. For example, Zhou et al . [13] proposed a unified time series analysis framework by adapting and fine-tuning LLMs. Are large language models useful for time series forecasting? Large language models (LLMs) are being applied to time series forecasting . But are language models actually useful for time series? What is calf & AAI 2025? CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning. AAAI 2025: 18915-18923 To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. Does the calf framework improve time series forecasting? Our work on the CALF framework for time series forecasting primarily focuses on enhancing predictive accuracy and generalization . While the positive societal impacts include improved forecasting for critical applications such as weather prediction, energy management, and financial modeling, potential negative impacts should be considered. Does language model pretraining improve performance on time series forecasting tasks? In conclusion, the computational intensity of LLMs in time series forecasting tasks does not result in a corresponding performance improvement. 4.3 Does language model pretraining help performance on forecasting tasks? (RQ3) Our evaluation in this section indicates that pretraining with language datasets is unnecessary for time series forecasting . What are the input and prediction lengths for calf? The input and prediction lengths are both set to 96 . As shown in Tab. 5, our proposed CALF shows significant improvements in both efficiency and accuracy compared with other LLM-based methods. We also provide theoretical complexity analysis for various Transformer-based methods in Appendix E. Ablation on Different Loss Functions. Do LLMs help forecasting in a few-shot setting? Finally, we show that LLMs do not even help forecasting in few-shot settings with 10% of the training data. We discuss the implications of our findings and suggest that time series methods that use large language models are better left to multimodal applications [4, 12, 38] that require textual reasoning. olely on the distilled student model. Recent works have been proposed to address the cross-modal misalignment problem with knowledge distillation [ Liu and Zhang, 2025], which can generally be categorized into black-box distillation [ Liu et al ., 2024a] and white-box distillation[ Liu et al ., 2025a] based on the accessibility of the teacher model ..."}
+{"idx": 1, "title": "CALF | Proceedings of the Thirty-Ninth AAAI Conference on ...", "date": "", "ddg_snippet": "Aug 5, 2025 · Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data. However ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.1609/aaai.v39i18.34082", "content": "Aug 5, 2025 · Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data. However ..."}
+{"idx": 2, "title": "dblp: CALF: Aligning LLMs for Time Series Forecasting via ...", "date": "", "ddg_snippet": "Apr 17, 2025 · Peiyuan Liu , Hang Guo, Tao Dai, Naiqi Li, Jigang Bao, Xudong Ren, Yong Jiang, Shu-Tao Xia: CALF : Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning.", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/conf/aaai/LiuG0LBR0X25", "content": "Apr 17, 2025 · Peiyuan Liu , Hang Guo, Tao Dai, Naiqi Li, Jigang Bao, Xudong Ren, Yong Jiang, Shu-Tao Xia: CALF : Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning."}
+{"idx": 3, "title": "Large Language Models and Causal Inference in Collaboration ...", "date": "", "ddg_snippet": "Sep 15, 2025 · Abstract Causal inference has demonstrated significant potential to enhance Natural Language Processing (NLP) models in areas such as predictive accuracy, fairness, robustness, and explainability by capturing causal relationships among variables.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.findings-naacl.427/", "content": "Sep 15, 2025 · Abstract Causal inference has demonstrated significant potential to enhance Natural Language Processing (NLP) models in areas such as predictive accuracy, fairness, robustness, and explainability by capturing causal relationships among variables."}
+{"idx": 4, "title": "Are Language Models Actually Useful for Time Series Forecasting?", "date": "", "ddg_snippet": "Abstract Large language models (LLMs) are being applied to time series forecasting . But are language models actually useful for time series? In a series of ablation studies on three recent and popular LLM- based time series forecasting methods, we find that removing the LLM component or replacing it with a basic attention layer does not degrade forecasting performance—in most cases, the ...", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/6ed5bf446f59e2c6646d23058c86424b-Paper-Conference.pdf", "content": "Abstract Large language models (LLMs) are being applied to time series forecasting . But are language models actually useful for time series? In a series of ablation studies on three recent and popular LLM- based time series forecasting methods, we find that removing the LLM component or replacing it with a basic attention layer does not degrade forecasting performance—in most cases, the ..."}
+{"idx": 5, "title": "CALF: Aligning LLMs for Time Series Forecasting", "date": "", "ddg_snippet": "To relieve such issues, some pioneering works attempt to introduce the powerful Large Language Models (LLMs) models in time series forecasting by employing the strong context modeling ability of LLMs. For example, Zhou et al . [13] proposed a unified time series analysis framework by adapting and fine-tuning LLMs.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2403.07300v2", "content": "To relieve such issues, some pioneering works attempt to introduce the powerful Large Language Models (LLMs) models in time series forecasting by employing the strong context modeling ability of LLMs. For example, Zhou et al . [13] proposed a unified time series analysis framework by adapting and fine-tuning LLMs."}
+{"idx": 6, "title": "LangTime: A Language-Guided Unified Model for Time ...", "date": "", "ddg_snippet": "To address this, CALF (Liu et al., 2024c ) applies knowledge distillation, S2IP-LLM (Pan et al., 2024) aligns semantic and time series spaces with ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/attachment?id=VfoKOD65Zq&name=pdf", "content": "To address this, CALF (Liu et al., 2024c ) applies knowledge distillation, S2IP-LLM (Pan et al., 2024) aligns semantic and time series spaces with ..."}
+{"idx": 7, "title": "A novel LLM time series forecasting method based on ...", "date": "", "ddg_snippet": "by L Wang · 2025 — Similarly, CALF, introduced by Liu et al . achieved efficient cross-modal alignment by separately processing text prototypes and time ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12217866/", "content": "by L Wang · 2025 — Similarly, CALF, introduced by Liu et al . achieved efficient cross-modal alignment by separately processing text prototypes and time ..."}
+{"idx": 8, "title": "LangTime: A Language-Guided Unified Model for Time ...", "date": "", "ddg_snippet": "1 Jul 2025 — To address this, CALF ( Liu et al ., 2024c ) applies knowledge distillation, S 2 IP-LLM (Pan et al ., 2024 ) aligns semantic and time series ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.08271", "content": "1 Jul 2025 — To address this, CALF ( Liu et al ., 2024c ) applies knowledge distillation, S 2 IP-LLM (Pan et al ., 2024 ) aligns semantic and time series ..."}
+{"idx": 9, "title": "arXiv:2411.02941v1 [cs.LG] 5 Nov 2024", "date": "", "ddg_snippet": "by H Ma · 2024 · Cited by 6 — Additionally, we incorporate large language models (LLMs) like GPT4TS. (Zhou et al ., 2023) and CALF ( Liu et al ., 2024a ), as well as other recent ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2411.02941", "content": "by H Ma · 2024 · Cited by 6 — Additionally, we incorporate large language models (LLMs) like GPT4TS. (Zhou et al ., 2023) and CALF ( Liu et al ., 2024a ), as well as other recent ..."}

data/sampled_jsons/CALF_Liu_2024_time_series_forecasting_language_model.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2403.07300] CALF: Aligning LLMs for Time Series Forecasting via Cross ...", "date": "", "ddg_snippet": "Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data. However ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2403.07300", "content": "Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data. However ..."}
+{"idx": 1, "title": "CALF: Aligning LLMs for Time Series Forecasting via Cross ... - GitHub", "date": "", "ddg_snippet": "Current LLM-based methods either use linear layers to project time series to the LLM's feature dimension or employ cross-attention and contrastive learning techniques, which address only the input side and overlook alignment in the deeper layers. Our CALF achieves better alignment through multi-level cross-modal fine-tuning.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Hank0626/CALF", "content": "Current LLM-based methods either use linear layers to project time series to the LLM's feature dimension or employ cross-attention and contrastive learning techniques, which address only the input side and overlook alignment in the deeper layers. Our CALF achieves better alignment through multi-level cross-modal fine-tuning."}
+{"idx": 2, "title": "Paper page - CALF: Aligning LLMs for Time Series Forecasting via Cross ...", "date": "", "ddg_snippet": "Abstract A novel Cross-Modal LLM Fine-Tuning ( CALF ) framework reduces distribution discrepancy between text and time series data for improved multivariate time series forecasting , achieving state-of-the-art performance with low computational complexity.", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/papers/2403.07300", "content": "Abstract A novel Cross-Modal LLM Fine-Tuning ( CALF ) framework reduces distribution discrepancy between text and time series data for improved multivariate time series forecasting , achieving state-of-the-art performance with low computational complexity."}
+{"idx": 3, "title": "Taming Pre-trained LLMs for Generalised Time Series Forecasting via ...", "date": "", "ddg_snippet": "Abstract: Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=LSgJYc4kg8", "content": "Abstract: Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data ..."}
+{"idx": 4, "title": "PDF Are Language Models Actually Useful for Time Series Forecasting?", "date": "", "ddg_snippet": "This hypothesis is unsurprising given language models are now pervasive in machine learning research. However, direct connections between language modeling and time series forecasting remain largely undefined. So to what extent is language modeling really beneficial for traditional time series tasks?", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/6ed5bf446f59e2c6646d23058c86424b-Paper-Conference.pdf", "content": "This hypothesis is unsurprising given language models are now pervasive in machine learning research. However, direct connections between language modeling and time series forecasting remain largely undefined. So to what extent is language modeling really beneficial for traditional time series tasks?"}
+{"idx": 5, "title": "CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning", "date": "", "ddg_snippet": "Despite this promising prop-erty, previous LLM-based time series methods often over-look this distribution, instead projecting the time series data to match the input dimensions of the language model (Zhou et al. 2023; Cao et al. 2024 ; Chang, Peng, and Chen 2023).", "subpage_snippet": "", "source": "ojs.aaai.org", "link": "https://ojs.aaai.org/index.php/AAAI/article/view/34082/36237", "content": "Despite this promising prop-erty, previous LLM-based time series methods often over-look this distribution, instead projecting the time series data to match the input dimensions of the language model (Zhou et al. 2023; Cao et al. 2024 ; Chang, Peng, and Chen 2023)."}
+{"idx": 6, "title": "CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine ...", "date": "", "ddg_snippet": "LLM Share on Twitter Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model (ICCV 2023) Periodicity Decoupling Framework for Long-term Series Forecasting (ICLR 2024 )", "subpage_snippet": "", "source": "naiqili.github.io", "link": "https://naiqili.github.io/2024/03/23/calf.html", "content": "LLM Share on Twitter Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model (ICCV 2023) Periodicity Decoupling Framework for Long-term Series Forecasting (ICLR 2024 )"}
+{"idx": 7, "title": "CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning", "date": "", "ddg_snippet": "To relieve such issues, some pioneering works attempt to introduce the powerful Large Language Models (LLMs) models in time series forecasting by employing the strong context modeling ability of LLMs. For example, Zhou et al. (Zhou et al. 2023) proposed a unified time series analysis framework by adapting and fine-tuning LLMs.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2403.07300v3", "content": "To relieve such issues, some pioneering works attempt to introduce the powerful Large Language Models (LLMs) models in time series forecasting by employing the strong context modeling ability of LLMs. For example, Zhou et al. (Zhou et al. 2023) proposed a unified time series analysis framework by adapting and fine-tuning LLMs."}
+{"idx": 8, "title": "CALF/README.md at main · Hank0626/CALF · GitHub", "date": "", "ddg_snippet": "Official implementation of \" CALF : Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning\" (AAAI 2025) - Hank0626/ CALF", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/Hank0626/CALF/blob/main/README.md", "content": "Official implementation of \" CALF : Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning\" (AAAI 2025) - Hank0626/ CALF"}
+{"idx": 9, "title": "dblp: CALF: Aligning LLMs for Time Series Forecasting via Cross-modal ...", "date": "", "ddg_snippet": "Bibliographic details on CALF : Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning.", "subpage_snippet": "", "source": "dblp.org", "link": "https://dblp.org/rec/conf/aaai/LiuG0LBR0X25", "content": "Bibliographic details on CALF : Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning."}

data/sampled_jsons/CALF_model_Liu_et_al_2024_time_series_forecasting_abstract.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Foundation Models for Time Series Analysis: A Tutorial and Survey", "date": "", "ddg_snippet": "Liu et al . [64] discuss that while the encoder-only model is favored in time series forecasting for its effectiveness on small datasets, the decoder-only architecture, with its strong generalization and capacity, could be preferred for large-scale time series models .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2403.14735", "content": "Liu et al . [64] discuss that while the encoder-only model is favored in time series forecasting for its effectiveness on small datasets, the decoder-only architecture, with its strong generalization and capacity, could be preferred for large-scale time series models ."}
+{"idx": 1, "title": "LSTPrompt: Large Language Models as Zero-Shot Time Series ...", "date": "", "ddg_snippet": "Abstract . Time - series forecasting (TSF) finds broad applications in real-world scenarios.@inproceedings{ liu - etal - 2024 -lstprompt, title = \"{LSTP}rompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting\", author = \" Liu , Haoxin and.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2024.findings-acl.466/", "content": "Abstract . Time - series forecasting (TSF) finds broad applications in real-world scenarios.@inproceedings{ liu - etal - 2024 -lstprompt, title = \"{LSTP}rompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting\", author = \" Liu , Haoxin and."}
+{"idx": 2, "title": "Modeling spatio-temporal locality in multi-step forecasting of...", "date": "", "ddg_snippet": "2.1 Spatio-temporal forecasting of multiple time series . In the literature, several forecasting approaches able to model the temporal and the spatial dimensions have been proposed, and applied to several different domains.", "subpage_snippet": "", "source": "link.springer.com", "link": "https://link.springer.com/article/10.1007/s10994-025-06875-1", "content": "2.1 Spatio-temporal forecasting of multiple time series . In the literature, several forecasting approaches able to model the temporal and the spatial dimensions have been proposed, and applied to several different domains."}
+{"idx": 3, "title": "(PDF) Autoregressive Moving-average Attention Mechanism for Time ...", "date": "", "ddg_snippet": "(Gruver et al .,2023;Jin et al ., 2024 ;Das et al ., 2024 ; Liu . et al ., 2024 b), with little research directly evaluating their. TSF performance in end-to-end training.foundation model for time - series forecasting . In Forty", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/384680475_Autoregressive_Moving-average_Attention_Mechanism_for_Time_Series_Forecasting", "content": "(Gruver et al .,2023;Jin et al ., 2024 ;Das et al ., 2024 ; Liu . et al ., 2024 b), with little research directly evaluating their. TSF performance in end-to-end training.foundation model for time - series forecasting . In Forty"}
+{"idx": 4, "title": "TSKANMixer: Kolmogorov–Arnold Networks with MLP-Mixer Model for...", "date": "", "ddg_snippet": "Xu et al . (Xu, Chen, and Wang 2024 ) in-vestigated the use of KANs for time series forecasting and demonstrated that two KAN models significantly out-performed traditional forecasting methods.", "subpage_snippet": "", "source": "assets.amazon.science", "link": "https://assets.amazon.science/a0/21/bd791012491fa94f79cd7fd26dae/tskanmixer-kolmogorov-arnold-networks-with-mlp-mixer-model-for-time-series-forecasting.pdf", "content": "Xu et al . (Xu, Chen, and Wang 2024 ) in-vestigated the use of KANs for time series forecasting and demonstrated that two KAN models significantly out-performed traditional forecasting methods."}
+{"idx": 5, "title": "Machine Learning Forecasting of Time Series - Train in Data's Blog", "date": "", "ddg_snippet": "Discover how to implement machine learning forecasting of time series data with Python, by using recursive and direct forecasting .", "subpage_snippet": "", "source": "www.blog.trainindata.com", "link": "https://www.blog.trainindata.com/machine-learning-forecasting/", "content": "Discover how to implement machine learning forecasting of time series data with Python, by using recursive and direct forecasting ."}
+{"idx": 6, "title": "Approaching Human-Level Forecasting with Language Models", "date": "", "ddg_snippet": "Time -LLM: Time series forecasting by reprogramming large language models .", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/arxiv/2402.18563/paper", "content": "Time -LLM: Time series forecasting by reprogramming large language models ."}
+{"idx": 7, "title": "Two new time -variant methods for fuzzy time series forecasting (2013)", "date": "", "ddg_snippet": "TL;DR: A fuzzy time series based multi-step-ahead forecasting model is established and the multi-point (trend) association FLRs effective in capturing the associations of time series and improving forecasting accuracy are established.", "subpage_snippet": "", "source": "scispace.com", "link": "https://scispace.com/papers/two-new-time-variant-methods-for-fuzzy-time-series-1j138kvf7j", "content": "TL;DR: A fuzzy time series based multi-step-ahead forecasting model is established and the multi-point (trend) association FLRs effective in capturing the associations of time series and improving forecasting accuracy are established."}
+{"idx": 8, "title": "[PDF] Deep Transformer Models for Time Series Forecasting : The...", "date": "", "ddg_snippet": "Deep Time Series Forecasting Models : A Comprehensive Survey.This study explores multivariate time series forecasting , centering on the transformer model , and introduces a novel approach that employs the transformer’s architecture for effective feature selection in time series data.", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Deep-Transformer-Models-for-Time-Series-The-Case-Wu-Green/f5a28db512357b700b62fb655ef4a90864e2fe7e", "content": "Deep Time Series Forecasting Models : A Comprehensive Survey.This study explores multivariate time series forecasting , centering on the transformer model , and introduces a novel approach that employs the transformer’s architecture for effective feature selection in time series data."}
+{"idx": 9, "title": "Multivariate Timeseries Forecast with Lead and Lag... | Medium", "date": "", "ddg_snippet": "Time series forecast plays a critical role in taking decisions in most industries.This is when the multivariate timeseries forecast comes into picture. Let us understand the multivariate forecast using below images. Figure 1: Multivariate Timeseries Forecast with lag data (lag=5 steps).", "subpage_snippet": "", "source": "medium.com", "link": "https://medium.com/towards-data-science/multivariate-timeseries-forecast-with-lead-and-lag-timesteps-using-lstm-1a34915f08a", "content": "Time series forecast plays a critical role in taking decisions in most industries.This is when the multivariate timeseries forecast comes into picture. Let us understand the multivariate forecast using below images. Figure 1: Multivariate Timeseries Forecast with lag data (lag=5 steps)."}

data/sampled_jsons/CRAB_arxiv_2407.01511_abstract_multimodal_language_model_agents.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CRAB: Cross-environment Agent Benchmark for Multimodal ... GitHub - camel-ai/crab: ️ CRAB: Cross-environment Agent ... CRAB: Cross-environment Agent Benchmark for Multimodal ... CRAB: Cross-Environment Agent Benchmark Introducing CRAB: A New Benchmark for Language Models CRAB: Cross-environment Agent Benchmark for Multimodal ... CRAB: Cross-environment Agent Benchmark for Multimodal ...", "date": "", "ddg_snippet": "Jul 1, 2024 · Abstract page for arXiv paper 2407.01511 : CRAB : Cross-environment Agent Benchmark for Multimodal Language Model Agents 🦀 CRAB : Cross-platform Agent Benchmark for Multimodal Embodied Language Model Agents Sep 15, 2025 · Abstract The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. Abstract : The development of autonomous agents increasingly relies on Multimodal LLMs (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by their focus on a single environment, lack of detailed and generalized evaluation methods, and the ... Jul 21, 2025 · Original Source Title: CRAB : Cross-environment Agent Benchmark for Multimodal Language Model Agents Abstract : The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. CRAB aims to become a general-purpose agent benchmark framework for Multimodal Language Model (MLM) agents . CRAB provides an end-to-end while easy-to-use framework to build agents , operate environments, and create benchmarks to evaluate them, featuring three key components: cross-environment support, a graph evaluator, and task generation. The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as web- sites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by their focus on a single environment, lack of detailed and generalized evaluation methods, and the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2407.01511", "content": "Jul 1, 2024 · Abstract page for arXiv paper 2407.01511 : CRAB : Cross-environment Agent Benchmark for Multimodal Language Model Agents 🦀 CRAB : Cross-platform Agent Benchmark for Multimodal Embodied Language Model Agents Sep 15, 2025 · Abstract The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. Abstract : The development of autonomous agents increasingly relies on Multimodal LLMs (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by their focus on a single environment, lack of detailed and generalized evaluation methods, and the ... Jul 21, 2025 · Original Source Title: CRAB : Cross-environment Agent Benchmark for Multimodal Language Model Agents Abstract : The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. CRAB aims to become a general-purpose agent benchmark framework for Multimodal Language Model (MLM) agents . CRAB provides an end-to-end while easy-to-use framework to build agents , operate environments, and create benchmarks to evaluate them, featuring three key components: cross-environment support, a graph evaluator, and task generation. The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as web- sites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by their focus on a single environment, lack of detailed and generalized evaluation methods, and the ..."}
+{"idx": 1, "title": "GitHub - camel-ai/crab: ️ CRAB: Cross-environment Agent ...", "date": "", "ddg_snippet": "🦀 CRAB : Cross-platform Agent Benchmark for Multimodal Embodied Language Model Agents", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/camel-ai/crab", "content": "🦀 CRAB : Cross-platform Agent Benchmark for Multimodal Embodied Language Model Agents"}
+{"idx": 2, "title": "CRAB: Cross-environment Agent Benchmark for Multimodal ...", "date": "", "ddg_snippet": "Sep 15, 2025 · Abstract The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.findings-acl.1113/", "content": "Sep 15, 2025 · Abstract The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones."}
+{"idx": 3, "title": "CRAB: Cross-Environment Agent Benchmark", "date": "", "ddg_snippet": "Abstract : The development of autonomous agents increasingly relies on Multimodal LLMs (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by their focus on a single environment, lack of detailed and generalized evaluation methods, and the ...", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/papers/2407.01511", "content": "Abstract : The development of autonomous agents increasingly relies on Multimodal LLMs (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by their focus on a single environment, lack of detailed and generalized evaluation methods, and the ..."}
+{"idx": 4, "title": "Introducing CRAB: A New Benchmark for Language Models", "date": "", "ddg_snippet": "Jul 21, 2025 · Original Source Title: CRAB : Cross-environment Agent Benchmark for Multimodal Language Model Agents Abstract : The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones.", "subpage_snippet": "", "source": "scisimple.com", "link": "https://scisimple.com/en/articles/2025-07-21-introducing-crab-a-new-benchmark-for-language-models--a3184y8", "content": "Jul 21, 2025 · Original Source Title: CRAB : Cross-environment Agent Benchmark for Multimodal Language Model Agents Abstract : The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones."}
+{"idx": 5, "title": "CRAB: Cross-environment Agent Benchmark for Multimodal ...", "date": "", "ddg_snippet": "CRAB aims to become a general-purpose agent benchmark framework for Multimodal Language Model (MLM) agents . CRAB provides an end-to-end while easy-to-use framework to build agents , operate environments, and create benchmarks to evaluate them, featuring three key components: cross-environment support, a graph evaluator, and task generation.", "subpage_snippet": "", "source": "crab.camel-ai.org", "link": "https://crab.camel-ai.org/", "content": "CRAB aims to become a general-purpose agent benchmark framework for Multimodal Language Model (MLM) agents . CRAB provides an end-to-end while easy-to-use framework to build agents , operate environments, and create benchmarks to evaluate them, featuring three key components: cross-environment support, a graph evaluator, and task generation."}
+{"idx": 6, "title": "CRAB: Cross-environment Agent Benchmark for Multimodal ...", "date": "", "ddg_snippet": "The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as web- sites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by their focus on a single environment, lack of detailed and generalized evaluation methods, and the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2407.01511", "content": "The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as web- sites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by their focus on a single environment, lack of detailed and generalized evaluation methods, and the ..."}
+{"idx": 7, "title": "CRAB: Cross-environment Agent Benchmark for Multimodal Language", "date": "", "ddg_snippet": "With the rapid development of multimodal large language models (MLLM), many agents capable of operating graphical user interfaces (GUIs) have emerged ...", "subpage_snippet": "", "source": "www.camel-ai.org", "link": "https://www.camel-ai.org/blogs/crab-cross-platform-agent-benchmark", "content": "With the rapid development of multimodal large language models (MLLM), many agents capable of operating graphical user interfaces (GUIs) have emerged ..."}
+{"idx": 8, "title": "COMMA: A Communicative Multimodal Multi-Agent Benchmark", "date": "", "ddg_snippet": "The rapid advances of multimodal agents built on large foundation models have largely overlooked their potential for language -based communication ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.07553v3", "content": "The rapid advances of multimodal agents built on large foundation models have largely overlooked their potential for language -based communication ..."}
+{"idx": 9, "title": "ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat", "date": "", "ddg_snippet": "... advancement of Large Language Models (LLMs) has enabled astonishing achievements in complex tasks [ 54 , 14 , 45 , 47 , 46 ] , that LLM agents can ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.14201v1", "content": "... advancement of Large Language Models (LLMs) has enabled astonishing achievements in complex tasks [ 54 , 14 , 45 , 47 , 46 ] , that LLM agents can ..."}

data/sampled_jsons/CVE-Bench_arxiv2503.17332_T-Agent_results_table_figure_success_rates_year_2025.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CVE - Bench : A Benchmark for AI Agents ' Ability to Exploit Real-World...", "date": "", "ddg_snippet": "arXiv : 2503 . 17332 v4 [cs.CR] 24 Jun 2025. Result ( success ). status: True attack: File access. Figure 1. Illustration of the sandbox framework in CVE - Bench as applied to a WordPress web application.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.17332", "content": "arXiv : 2503 . 17332 v4 [cs.CR] 24 Jun 2025. Result ( success ). status: True attack: File access. Figure 1. Illustration of the sandbox framework in CVE - Bench as applied to a WordPress web application."}
+{"idx": 1, "title": "CVE - Bench : A Benchmark for AI Agents ' Ability to Exploit... | alphaXiv", "date": "", "ddg_snippet": "CVE - Bench Framework Figure 1: Overview of the CVE - Bench framework showing how AI agents interact with vulnerable web applications in target containers and are evaluated based on standardized attack vectors.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2503.17332v1", "content": "CVE - Bench Framework Figure 1: Overview of the CVE - Bench framework showing how AI agents interact with vulnerable web applications in target containers and are evaluated based on standardized attack vectors."}
+{"idx": 2, "title": "uiuc-kang-lab/ cve - bench : CVE - Bench : A Benchmark for AI Agents ...", "date": "", "ddg_snippet": "arxiv .org/abs/ 2503 . 17332 . License. CVE - Bench includes 40 critical-severity Common Vulnerability and Exposures (CVE) with the reference automatic exploits available on requests. For each CVE, given a target web application and necessary information, an AI agent is tasked with...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/uiuc-kang-lab/cve-bench", "content": "arxiv .org/abs/ 2503 . 17332 . License. CVE - Bench includes 40 critical-severity Common Vulnerability and Exposures (CVE) with the reference automatic exploits available on requests. For each CVE, given a target web application and necessary information, an AI agent is tasked with..."}
+{"idx": 3, "title": "uiuc-kang-lab cve - bench issues - Githubissues", "date": "", "ddg_snippet": "uiuc-kang-lab / cve - bench . CVE - Bench : A Benchmark for AI Agents ’ Ability to Exploit Real-World Web Application Vulnerabilities .Can you disclose how to reproduce the results with Auto-GPT on CVE - Bench .", "subpage_snippet": "", "source": "githubissues.com", "link": "https://githubissues.com/uiuc-kang-lab/cve-bench", "content": "uiuc-kang-lab / cve - bench . CVE - Bench : A Benchmark for AI Agents ’ Ability to Exploit Real-World Web Application Vulnerabilities .Can you disclose how to reproduce the results with Auto-GPT on CVE - Bench ."}
+{"idx": 4, "title": "Show HN: CVE - Bench , the first LLM benchmark using real-world web...", "date": "", "ddg_snippet": "To our knowledge CVE - bench is the first benchmark using real-world web vulnerabilities to evaluate AI agents ' cyberattack capabilities. We included 40 CVEs from NIST's database, focusing on critical-severity vulnerability (CVSS > 9.0).", "subpage_snippet": "", "source": "www.gpt-5.com", "link": "https://www.gpt-5.com/80434572/show-hn-cve-bench-the-first-llm-benchmark-using-real-world-web-vulnerabilities", "content": "To our knowledge CVE - bench is the first benchmark using real-world web vulnerabilities to evaluate AI agents ' cyberattack capabilities. We included 40 CVEs from NIST's database, focusing on critical-severity vulnerability (CVSS > 9.0)."}
+{"idx": 5, "title": "BountyBench: The Design of Environments and Rewards for...", "date": "", "ddg_snippet": "Figure 1: BountyBench consists of Detect, Exploit, and Patch tasks, which each pass a distinct task input to the agent . Table 1: For each agent , we display the Success Rate per task.", "subpage_snippet": "", "source": "cs224r.stanford.edu", "link": "https://cs224r.stanford.edu/projects/pdfs/CS224R_Final_Report+(1)1.pdf", "content": "Figure 1: BountyBench consists of Detect, Exploit, and Patch tasks, which each pass a distinct task input to the agent . Table 1: For each agent , we display the Success Rate per task."}
+{"idx": 6, "title": "(PDF) Agent Identity Evals: Measuring Agentic Identity", "date": "", "ddg_snippet": "Cve - bench : A benchmark for ai agents ’ ability to. exploit real-world web application vulnerabilities . arXiv preprint arXiv : 2503 . 17332 , 2025.Output. Task success rate across 8 interactive environments. (commercial LLMs vs. OSS). GAIA [31] Tool Invocation & Results ; Final.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/393965533_Agent_Identity_Evals_Measuring_Agentic_Identity", "content": "Cve - bench : A benchmark for ai agents ’ ability to. exploit real-world web application vulnerabilities . arXiv preprint arXiv : 2503 . 17332 , 2025.Output. Task success rate across 8 interactive environments. (commercial LLMs vs. OSS). GAIA [31] Tool Invocation & Results ; Final."}
+{"idx": 7, "title": "Revolutionizing Cybersecurity: How AI Accelerates Exploit...", "date": "", "ddg_snippet": "1. Introduction: The Shifting Dynamics of Vulnerability Exploitation The cybersecurity industry faces relentless pressure, defined by a continuous race between identifying and patching vulnerabilities and exploiting them.", "subpage_snippet": "", "source": "www.linkedin.com", "link": "https://www.linkedin.com/pulse/revolutionizing-cybersecurity-how-ai-accelerates-exploit-merton-aseqc", "content": "1. Introduction: The Shifting Dynamics of Vulnerability Exploitation The cybersecurity industry faces relentless pressure, defined by a continuous race between identifying and patching vulnerabilities and exploiting them."}
+{"idx": 8, "title": "Richard Fang - Google Scholar | University of Illinois - Cited by 275", "date": "", "ddg_snippet": "5. CVE - Bench : A Benchmark for AI Agents ' Ability to Exploit Real-World Web Application Vulnerabilities . Y Zhu, A Kellermann, D Bowman, P Li, A Gupta, A Danda, R Fang, ... arXiv preprint arXiv : 2503 . 17332 , 2025.", "subpage_snippet": "", "source": "scholar.google.co.in", "link": "https://scholar.google.co.in/citations?user=l7Ra9p8AAAAJ&hl=en", "content": "5. CVE - Bench : A Benchmark for AI Agents ' Ability to Exploit Real-World Web Application Vulnerabilities . Y Zhu, A Kellermann, D Bowman, P Li, A Gupta, A Danda, R Fang, ... arXiv preprint arXiv : 2503 . 17332 , 2025."}
+{"idx": 9, "title": "Мечты робота – Telegram", "date": "", "ddg_snippet": "...понимающую геолокации и оживляющую GPS-координаты рассказами о местных достопримечательностях: http:// arxiv .org/abs/2503.16423v1 Второй захватывающий проект, OpenVLThinker, развивает комплексные способности рассуждения у моделей...", "subpage_snippet": "", "source": "t.me", "link": "https://t.me/robodream/773", "content": "...понимающую геолокации и оживляющую GPS-координаты рассказами о местных достопримечательностях: http:// arxiv .org/abs/2503.16423v1 Второй захватывающий проект, OpenVLThinker, развивает комплексные способности рассуждения у моделей..."}

data/sampled_jsons/CVE-Bench_paper_'Insufficient_Exploration'_failure_mode_description.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "GitHub - uiuc-kang-lab/cve-bench: CVE-Bench: A Benchmark for AI Agents ...", "date": "", "ddg_snippet": "This repository contains data and code used in the CVE-Bench ( paper , blog), which is for evaluating AI agents on real world web vulnerabilities and exploits collected from National Vulnerability Database. CVE-Bench includes 40 critical-severity Common Vulnerability and Exposures ( CVE ) with the reference automatic exploits available on requests.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/uiuc-kang-lab/cve-bench", "content": "This repository contains data and code used in the CVE-Bench ( paper , blog), which is for evaluating AI agents on real world web vulnerabilities and exploits collected from National Vulnerability Database. CVE-Bench includes 40 critical-severity Common Vulnerability and Exposures ( CVE ) with the reference automatic exploits available on requests."}
+{"idx": 1, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web ...", "date": "", "ddg_snippet": "CVE-Bench is designed to simulate different stages in a vulnerability lifecycle. Under the zero-day setting, we only provide the LLM agents with task descriptions The agents must independently identify the vulnerability and execute a successful attack.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.17332v4", "content": "CVE-Bench is designed to simulate different stages in a vulnerability lifecycle. Under the zero-day setting, we only provide the LLM agents with task descriptions The agents must independently identify the vulnerability and execute a successful attack."}
+{"idx": 2, "title": "PDF CVE-Bench: Benchmarking LLM-based Software Engineering Agent's Ability ...", "date": "", "ddg_snippet": "In this paper , we introduce CVE-Bench (§2), a benchmark that evaluates LLM-based agents in a realisticvulnerability-repairingsetting. CVE-Bench contains three unique characteristics: (1) Instead of input-output evaluation, CVE-Bench supports agent-based evaluation by offering real-world interactive execution-guided programming environments .", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2025.naacl-long.212.pdf", "content": "In this paper , we introduce CVE-Bench (§2), a benchmark that evaluates LLM-based agents in a realisticvulnerability-repairingsetting. CVE-Bench contains three unique characteristics: (1) Instead of input-output evaluation, CVE-Bench supports agent-based evaluation by offering real-world interactive execution-guided programming environments ."}
+{"idx": 3, "title": "[2503.17332] CVE-Bench: A Benchmark for AI Agents' Ability to Exploit ...", "date": "", "ddg_snippet": "Large language model (LLM) agents are increasingly capable of autonomously conducting cyberattacks, posing significant threats to existing applications. This growing risk highlights the urgent need for a real-world benchmark to evaluate the ability of LLM agents to exploit web application vulnerabilities. However, existing benchmarks fall short as they are limited to abstracted Capture the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2503.17332", "content": "Large language model (LLM) agents are increasingly capable of autonomously conducting cyberattacks, posing significant threats to existing applications. This growing risk highlights the urgent need for a real-world benchmark to evaluate the ability of LLM agents to exploit web application vulnerabilities. However, existing benchmarks fall short as they are limited to abstracted Capture the ..."}
+{"idx": 4, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web ...", "date": "", "ddg_snippet": "Abstract Large language model (LLM) agents are increas-ingly capable of autonomously conducting cy-berattacks, posing significant threats to existing applications. This growing risk highlights the ur-gent need for a real-world benchmark to evaluate the ability of LLM agents to exploit web appli-cation vulnerabilities. However, existing bench -marks fall short as they are limited to abstracted ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2503.17332", "content": "Abstract Large language model (LLM) agents are increas-ingly capable of autonomously conducting cy-berattacks, posing significant threats to existing applications. This growing risk highlights the ur-gent need for a real-world benchmark to evaluate the ability of LLM agents to exploit web appli-cation vulnerabilities. However, existing bench -marks fall short as they are limited to abstracted ..."}
+{"idx": 5, "title": "CVE: Common Vulnerabilities and Exposures", "date": "", "ddg_snippet": "At cve .org, we provide the authoritative reference method for publicly known information-security vulnerabilities and exposures", "subpage_snippet": "", "source": "www.cve.org", "link": "https://www.cve.org/", "content": "At cve .org, we provide the authoritative reference method for publicly known information-security vulnerabilities and exposures"}
+{"idx": 6, "title": "uiuc-kang-lab/cve-bench | DeepWiki", "date": "", "ddg_snippet": "Overview Relevant source files CVE-Bench is a comprehensive benchmark designed to evaluate AI agents' capabilities in exploiting real-world web application vulnerabilities. This document provides a high-level introduction to the CVE-Bench repository structure, architecture, and core components. For detailed setup instructions, see Getting Started.", "subpage_snippet": "", "source": "deepwiki.com", "link": "https://deepwiki.com/uiuc-kang-lab/cve-bench/1-overview", "content": "Overview Relevant source files CVE-Bench is a comprehensive benchmark designed to evaluate AI agents' capabilities in exploiting real-world web application vulnerabilities. This document provides a high-level introduction to the CVE-Bench repository structure, architecture, and core components. For detailed setup instructions, see Getting Started."}
+{"idx": 7, "title": "cve-bench/README.md at main · uiuc-kang-lab/cve-bench · GitHub", "date": "", "ddg_snippet": "This repository contains data and code used in the CVE-Bench ( paper , blog), which is for evaluating AI agents on real world web vulnerabilities and exploits collected from National Vulnerability Database. CVE-Bench includes 40 critical-severity Common Vulnerability and Exposures ( CVE ) with the reference automatic exploits available on requests.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/uiuc-kang-lab/cve-bench/blob/main/README.md", "content": "This repository contains data and code used in the CVE-Bench ( paper , blog), which is for evaluating AI agents on real world web vulnerabilities and exploits collected from National Vulnerability Database. CVE-Bench includes 40 critical-severity Common Vulnerability and Exposures ( CVE ) with the reference automatic exploits available on requests."}
+{"idx": 8, "title": "CVE security vulnerability database. Security vulnerabilities, exploits ...", "date": "", "ddg_snippet": "CVEDetails.com is a vulnerability intelligence solution providing CVE security vulnerability database, exploits, advisories, product and CVE risk scores, attack surface intelligence, open source vulnerabilities, code changes, vulnerabilities affecting your attack surface and software inventory/tech stack. You can view CVE vulnerability details, exploits, references, metasploit modules, full ...", "subpage_snippet": "", "source": "www.cvedetails.com", "link": "https://www.cvedetails.com/", "content": "CVEDetails.com is a vulnerability intelligence solution providing CVE security vulnerability database, exploits, advisories, product and CVE risk scores, attack surface intelligence, open source vulnerabilities, code changes, vulnerabilities affecting your attack surface and software inventory/tech stack. You can view CVE vulnerability details, exploits, references, metasploit modules, full ..."}
+{"idx": 9, "title": "CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web ...", "date": "", "ddg_snippet": "To address this challenge, we introduce CVE-Bench , a real-world cybersecurity benchmark based on critical-severity Common Vulnerabilities and Exposures. In CVE-Bench , we design a sandbox framework that enables LLM agents to exploit vulnerable web applications in scenarios that mimic real-world conditions, while also providing effective ...", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/overview/2503.17332v4", "content": "To address this challenge, we introduce CVE-Bench , a real-world cybersecurity benchmark based on critical-severity Common Vulnerabilities and Exposures. In CVE-Bench , we design a sandbox framework that enables LLM agents to exploit vulnerable web applications in scenarios that mimic real-world conditions, while also providing effective ..."}

data/sampled_jsons/CVPR_2025_DART_paper_Table_2_F1_score_MIMIC-CXR.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PDF DART: Disease-aware Image-Text Alignment and Self-correcting Re ...", "date": "", "ddg_snippet": "Table 2 presents a comparison of the clinical eficacy (CE) metrics between our proposed framework and state-of-the-art meth-ods on the MIMIC-CXR dataset, evaluated by F1 score , pre-cision, and recall.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Park_DART_Disease-aware_Image-Text_Alignment_and_Self-correcting_Re-alignment_for_Trustworthy_Radiology_CVPR_2025_paper.pdf", "content": "Table 2 presents a comparison of the clinical eficacy (CE) metrics between our proposed framework and state-of-the-art meth-ods on the MIMIC-CXR dataset, evaluated by F1 score , pre-cision, and recall."}
+{"idx": 1, "title": "GitHub - mk-runner/MLRG: [CVPR'25] Enhanced Contrastive Learning with ...", "date": "", "ddg_snippet": "MIMIC-CXR / MIMIC -ABN — PhysioNet, with data systematically organized under root directories labeled p10 through p19, maintaining consistency with MIMIC-CXR's default configuration.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/mk-runner/MLRG", "content": "MIMIC-CXR / MIMIC -ABN — PhysioNet, with data systematically organized under root directories labeled p10 through p19, maintaining consistency with MIMIC-CXR's default configuration."}
+{"idx": 2, "title": "Mimic-cxr: a Large Publicly Available Database of Labeled Chest Radiographs", "date": "", "ddg_snippet": "Table 2 : Frequency of labels in MIMIC-CXR on the training subset of 369,188 images, corresponding to 222,952 unique radiologic studies. ... negative. The harmonic mean of the sensitivity and positive predictive value, referred to as the F1 score , was calculated for each group independently. Table 3 shows the performance across labels.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/1901.07042v1", "content": "Table 2 : Frequency of labels in MIMIC-CXR on the training subset of 369,188 images, corresponding to 222,952 unique radiologic studies. ... negative. The harmonic mean of the sensitivity and positive predictive value, referred to as the F1 score , was calculated for each group independently. Table 3 shows the performance across labels."}
+{"idx": 3, "title": "CVPR 2025 Accepted Paper List - Paper Copilot", "date": "", "ddg_snippet": "How to use the paper list below: - Overview: This table presents papers from the CVPR conference, year 2025 . - Filtering: By default, the table loads the first 100 records. You can use the filter box under each column header to search within these loaded entries.", "subpage_snippet": "", "source": "papercopilot.com", "link": "https://papercopilot.com/paper-list/cvpr-paper-list/cvpr-2025-paper-list/", "content": "How to use the paper list below: - Overview: This table presents papers from the CVPR conference, year 2025 . - Filtering: By default, the table loads the first 100 records. You can use the filter box under each column header to search within these loaded entries."}
+{"idx": 4, "title": "CVPR 2025 Open Access Repository", "date": "", "ddg_snippet": "In this study, we propose a Disease-aware image-text Alignment and self-correcting Re-alignment for Trustworthy radiology report generation ( DART ) framework. In the first stage, we generate initial reports based on image-to-text retrieval with disease-matching, embedding both images and texts in a shared embedding space through contrastive ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/html/Park_DART_Disease-aware_Image-Text_Alignment_and_Self-correcting_Re-alignment_for_Trustworthy_Radiology_CVPR_2025_paper.html", "content": "In this study, we propose a Disease-aware image-text Alignment and self-correcting Re-alignment for Trustworthy radiology report generation ( DART ) framework. In the first stage, we generate initial reports based on image-to-text retrieval with disease-matching, embedding both images and texts in a shared embedding space through contrastive ..."}
+{"idx": 5, "title": "GitHub - mk-runner/Awesome-Radiology-Report-Generation: paper list ...", "date": "", "ddg_snippet": "MIMIC - CXR -JPG, a large publicly available database of labeled chest radiographs ( MIMIC-CXR ) [ paper ] [data]. Preparing a collection of radiology examinations for distribution and retrieval (IU X-ray) [ paper ] [data].", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/mk-runner/Awesome-Radiology-Report-Generation", "content": "MIMIC - CXR -JPG, a large publicly available database of labeled chest radiographs ( MIMIC-CXR ) [ paper ] [data]. Preparing a collection of radiology examinations for distribution and retrieval (IU X-ray) [ paper ] [data]."}
+{"idx": 6, "title": "DART: Disease-aware Image-Text Alignment and Self-correcting Re ...", "date": "", "ddg_snippet": "Table 2 : A comparison of the clinical efficacy (CE) metrics between our proposed framework (Ours) and state-of-the-art methods using F1 score , precision, and recall on the MIMIC-CXR dataset. Also, we evaluate the disease classifier performance.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.11786v1", "content": "Table 2 : A comparison of the clinical efficacy (CE) metrics between our proposed framework (Ours) and state-of-the-art methods using F1 score , precision, and recall on the MIMIC-CXR dataset. Also, we evaluate the disease classifier performance."}
+{"idx": 7, "title": "MIMIC-CXR: Chest X-ray Image Classification and Report Generation", "date": "", "ddg_snippet": "This repository contains the implementation and results of the research paper \" MIMIC-CXR : Chest X-ray Image Classification and Report Generation\". The project leverages the MIMIC-CXR dataset, which includes chest X-ray images along with corresponding radiology reports.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/yuanditang/MIMIC-CXR", "content": "This repository contains the implementation and results of the research paper \" MIMIC-CXR : Chest X-ray Image Classification and Report Generation\". The project leverages the MIMIC-CXR dataset, which includes chest X-ray images along with corresponding radiology reports."}
+{"idx": 8, "title": "CVPR Poster Enhanced Contrastive Learning with Multi-view Longitudinal ...", "date": "", "ddg_snippet": "Extensive experiments on MIMIC-CXR , MIMIC -ABN, and Two-view CXR datasets demonstrate that our MLRG outperforms recent state-of-the-art methods, achieving a 2.3\\% BLEU-4 improvement on MIMIC-CXR , a 5.5\\% F1 score improvement on MIMIC -ABN, and a 2.7\\% F1 RadGraph improvement on Two-view CXR .", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/34086", "content": "Extensive experiments on MIMIC-CXR , MIMIC -ABN, and Two-view CXR datasets demonstrate that our MLRG outperforms recent state-of-the-art methods, achieving a 2.3\\% BLEU-4 improvement on MIMIC-CXR , a 5.5\\% F1 score improvement on MIMIC -ABN, and a 2.7\\% F1 RadGraph improvement on Two-view CXR ."}
+{"idx": 9, "title": "CVPR Poster DART: Disease-aware Image-Text Alignment and Self ...", "date": "", "ddg_snippet": "Our proposed framework achieves state-of-the-art results on the MIMIC-CXR and IU X-ray benchmarks, surpassing previous approaches in both report generation and disease classification, thereby enhancing the trustworthiness of radiology reports.", "subpage_snippet": "", "source": "cvpr.thecvf.com", "link": "https://cvpr.thecvf.com/virtual/2025/poster/32986", "content": "Our proposed framework achieves state-of-the-art results on the MIMIC-CXR and IU X-ray benchmarks, surpassing previous approaches in both report generation and disease classification, thereby enhancing the trustworthiness of radiology reports."}

data/sampled_jsons/Catoni_Contextual_Bandits_Heavy-tailed_Rewards_Theorem_3.1_Theorem_3.4_regret_bounds.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards Catoni Contextual Bandits are Robust to Heavy-tailed Rewards Catoni Contextual Bandits are Robust to Heavy-tailed Rewards ICML Poster Catoni Contextual Bandits are Robust to Heavy ... Abstract arXiv:2502.02486v1 [stat.ML] 4 Feb 2025 Stochastic Graphical Bandits with Heavy-Tailed Rewards ϵ,u -Adaptive Regret Minimization in Heavy-Tailed Bandit", "date": "", "ddg_snippet": "Feb 4 , 2025 · However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni 's estimator from robust statistics, and apply it to contextual bandits with general function approximation. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this pa-per, we develop an algorithmic approach building on Catoni ’s estimator from robust statistics, and apply it to contextual bandits with general func-tion approximation. This paper develops an algorithmic approach building on Catoni 's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ... However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni 's estimator from robust statistics, and apply it to contextual bandits with general function approximation. Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range [0, R], and their regret scales polynomially with this reward range R. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni ... To settle this issue, we investigate stochastic graph-ical bandits with heavy-tailed rewards , where the distributions have finite moments of order 1 + , for some 2 (0; 1]. Firstly, we develop one UCB-type algorithm, whose expected regret is upper bounded by a sum of gap-based quantities over the clique covering of the feedback graph. Abstract Heavy-tailed distributions naturally arise in several settings, from finance to telecommunications. While regret minimization under subgaussian or bounded rewards has been widely studied, learning with heavy-tailed distributions only gained popularity over the last decade. In this paper, we consider the setting in which the reward distributions have finite absolute raw moments of ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.02486", "content": "Feb 4 , 2025 · However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni 's estimator from robust statistics, and apply it to contextual bandits with general function approximation. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this pa-per, we develop an algorithmic approach building on Catoni ’s estimator from robust statistics, and apply it to contextual bandits with general func-tion approximation. This paper develops an algorithmic approach building on Catoni 's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ... However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni 's estimator from robust statistics, and apply it to contextual bandits with general function approximation. Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range [0, R], and their regret scales polynomially with this reward range R. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni ... To settle this issue, we investigate stochastic graph-ical bandits with heavy-tailed rewards , where the distributions have finite moments of order 1 + , for some 2 (0; 1]. Firstly, we develop one UCB-type algorithm, whose expected regret is upper bounded by a sum of gap-based quantities over the clique covering of the feedback graph. Abstract Heavy-tailed distributions naturally arise in several settings, from finance to telecommunications. While regret minimization under subgaussian or bounded rewards has been widely studied, learning with heavy-tailed distributions only gained popularity over the last decade. In this paper, we consider the setting in which the reward distributions have finite absolute raw moments of ..."}
+{"idx": 1, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this pa-per, we develop an algorithmic approach building on Catoni ’s estimator from robust statistics, and apply it to contextual bandits with general func-tion approximation.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=5IpVe9PH14", "content": "However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this pa-per, we develop an algorithmic approach building on Catoni ’s estimator from robust statistics, and apply it to contextual bandits with general func-tion approximation."}
+{"idx": 2, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "This paper develops an algorithmic approach building on Catoni 's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Catoni-Contextual-Bandits-are-Robust-to-Rewards-Ye-Jin/125154c306493f2c7af8e8c09c0e58c22106e6fe", "content": "This paper develops an algorithmic approach building on Catoni 's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ..."}
+{"idx": 3, "title": "ICML Poster Catoni Contextual Bandits are Robust to Heavy ...", "date": "", "ddg_snippet": "However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni 's estimator from robust statistics, and apply it to contextual bandits with general function approximation.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46438", "content": "However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni 's estimator from robust statistics, and apply it to contextual bandits with general function approximation."}
+{"idx": 4, "title": "Stochastic Graphical Bandits with Heavy-Tailed Rewards", "date": "", "ddg_snippet": "To settle this issue, we investigate stochastic graph-ical bandits with heavy-tailed rewards , where the distributions have finite moments of order 1 + , for some 2 (0; 1]. Firstly, we develop one UCB-type algorithm, whose expected regret is upper bounded by a sum of gap-based quantities over the clique covering of the feedback graph.", "subpage_snippet": "", "source": "ai.nju.edu.cn", "link": "https://ai.nju.edu.cn/zlj/pdf/UAI-2023-Gou.pdf", "content": "To settle this issue, we investigate stochastic graph-ical bandits with heavy-tailed rewards , where the distributions have finite moments of order 1 + , for some 2 (0; 1]. Firstly, we develop one UCB-type algorithm, whose expected regret is upper bounded by a sum of gap-based quantities over the clique covering of the feedback graph."}
+{"idx": 5, "title": "ϵ,u -Adaptive Regret Minimization in Heavy-Tailed Bandit", "date": "", "ddg_snippet": "Abstract Heavy-tailed distributions naturally arise in several settings, from finance to telecommunications. While regret minimization under subgaussian or bounded rewards has been widely studied, learning with heavy-tailed distributions only gained popularity over the last decade. In this paper, we consider the setting in which the reward distributions have finite absolute raw moments of ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v247/genalti24a/genalti24a.pdf", "content": "Abstract Heavy-tailed distributions naturally arise in several settings, from finance to telecommunications. While regret minimization under subgaussian or bounded rewards has been widely studied, learning with heavy-tailed distributions only gained popularity over the last decade. In this paper, we consider the setting in which the reward distributions have finite absolute raw moments of ..."}
+{"idx": 6, "title": "Heavy-Tailed Linear Bandits: Huber Regression with One-Pass", "date": "", "ddg_snippet": "Table 1 : Comparisons of our regret bounds and computational complexity to previous best-known results for heavy - tailed linear bandits .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2503.00419v1", "content": "Table 1 : Comparisons of our regret bounds and computational complexity to previous best-known results for heavy - tailed linear bandits ."}
+{"idx": 7, "title": "Abstract arXiv:2502.02486v1 [stat.ML] 4 Feb 2025", "date": "", "ddg_snippet": "Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range [0, R], and their regret scales polynomially with this reward range R. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.02486", "content": "Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range [0, R], and their regret scales polynomially with this reward range R. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni ..."}
+{"idx": 8, "title": "ICML 2022 Papers", "date": "", "ddg_snippet": "SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One -shot Graph Generators ... Versatile Dueling Bandits : Best-of-both ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2022/papers.html", "content": "SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One -shot Graph Generators ... Versatile Dueling Bandits : Best-of-both ..."}
+{"idx": 9, "title": "Extended UCB Policies for Multi-Armed Bandit Problems", "date": "", "ddg_snippet": "... 4 p= 4 and q = 2 q=2 ) to arbitrarily chosen p > q > 1 p > q > 1 as long as the two moments have a known controlled relationship, while ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/1112.1768v5", "content": "... 4 p= 4 and q = 2 q=2 ) to arbitrarily chosen p > q > 1 p > q > 1 as long as the two moments have a known controlled relationship, while ..."}

data/sampled_jsons/Catoni_Contextual_Bandits_OFUL_implementation_difficult_conclusion.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range [0, R], and their regret scales polynomially with this reward range R. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.02486", "content": "Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range [0, R], and their regret scales polynomially with this reward range R. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni ..."}
+{"idx": 1, "title": "PDF Lecture 4: Contextual Bandits - UMass", "date": "", "ddg_snippet": "The protocol is known as contextual bandits . The main new feature is that on each round the learner observes some \\ contextual information\" which it may use to inform its choice of action.", "subpage_snippet": "", "source": "people.cs.umass.edu", "link": "https://people.cs.umass.edu/~akshay/courses/coms6998-11/files/lec4.pdf", "content": "The protocol is known as contextual bandits . The main new feature is that on each round the learner observes some \\ contextual information\" which it may use to inform its choice of action."}
+{"idx": 2, "title": "PDF Contextual Bandits", "date": "", "ddg_snippet": "Recall: Contextual bandit environment Context at time t encoded into a variable xt that we see before choosing our action xt is drawn i.i.d. at each time point from a distribution νx on sample space xt", "subpage_snippet": "", "source": "lucasjanson.fas.harvard.edu", "link": "https://lucasjanson.fas.harvard.edu/courses/22.pdf", "content": "Recall: Contextual bandit environment Context at time t encoded into a variable xt that we see before choosing our action xt is drawn i.i.d. at each time point from a distribution νx on sample space xt"}
+{"idx": 3, "title": "PDF A Contextual Bandit Bake-o - Journal of Machine Learning Research", "date": "", "ddg_snippet": "1. Introduction At a practical level, how should contextual bandit learning and exploration be done? In the contextual bandit problem, a learner repeatedly observes a context, chooses an action, and observes a loss for the chosen action only. Many real-world interactive machine learning tasks are well-suited to this setting: a movie recommendation system selects a movie for a given user and ...", "subpage_snippet": "", "source": "jmlr.org", "link": "https://jmlr.org/papers/volume22/18-863/18-863.pdf", "content": "1. Introduction At a practical level, how should contextual bandit learning and exploration be done? In the contextual bandit problem, a learner repeatedly observes a context, chooses an action, and observes a loss for the chosen action only. Many real-world interactive machine learning tasks are well-suited to this setting: a movie recommendation system selects a movie for a given user and ..."}
+{"idx": 4, "title": "ICML Poster Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "This makes it difficult for standard learning algorithms to make good decisions, since they are designed assuming rewards are relatively well-behaved and bounded.We tackle this problem by designing new algorithms for contextual bandits , a type of learning model that helps an agent choose actions based on observed data.", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46438", "content": "This makes it difficult for standard learning algorithms to make good decisions, since they are designed assuming rewards are relatively well-behaved and bounded.We tackle this problem by designing new algorithms for contextual bandits , a type of learning model that helps an agent choose actions based on observed data."}
+{"idx": 5, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "This paper develops an algorithmic approach building on Catoni's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Catoni-Contextual-Bandits-are-Robust-to-Rewards-Ye-Jin/125154c306493f2c7af8e8c09c0e58c22106e6fe", "content": "This paper develops an algorithmic approach building on Catoni's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ..."}
+{"idx": 6, "title": "Offline Contextual Bandit: Theory and Large Scale Applications", "date": "", "ddg_snippet": "The offline contextual bandit setting is particularly interesting for industrial applications. It provides more control to practitioners, as they can evaluate and learn new policies, and fully decideonwhethertodeploythemonlineornot.", "subpage_snippet": "", "source": "theses.hal.science", "link": "https://theses.hal.science/tel-04417936v1/document", "content": "The offline contextual bandit setting is particularly interesting for industrial applications. It provides more control to practitioners, as they can evaluate and learn new policies, and fully decideonwhethertodeploythemonlineornot."}
+{"idx": 7, "title": "Taking a hint: How to leverage loss predictors in contextual bandits?", "date": "", "ddg_snippet": "3 ) is achievable; 3) with M predictors, a linear dependence on M is necessary, even though logarithmic dependence is possible for non- contextual problems. We also develop several novel algorithmic techniques to achieve matching upper bounds, in-cluding 1) a key action remapping technique for optimal regret with known E, 2) computationally efficient implementation of Catoni's robust mean ...", "subpage_snippet": "", "source": "par.nsf.gov", "link": "https://par.nsf.gov/servlets/purl/10207168", "content": "3 ) is achievable; 3) with M predictors, a linear dependence on M is necessary, even though logarithmic dependence is possible for non- contextual problems. We also develop several novel algorithmic techniques to achieve matching upper bounds, in-cluding 1) a key action remapping technique for optimal regret with known E, 2) computationally efficient implementation of Catoni's robust mean ..."}
+{"idx": 8, "title": "PDF Improving Ofline Contextual Bandits with Distributional Robustness", "date": "", "ddg_snippet": "Improving Ofline Contextual Bandits with Distributional Robustness OTMANE SAKHI∗, LOUIS FAURY∗, Criteo AI Lab, France. and FLAVIAN VASILE,", "subpage_snippet": "", "source": "louisfaury.github.io", "link": "https://louisfaury.github.io/_papers/dro_reveal.pdf", "content": "Improving Ofline Contextual Bandits with Distributional Robustness OTMANE SAKHI∗, LOUIS FAURY∗, Criteo AI Lab, France. and FLAVIAN VASILE,"}
+{"idx": 9, "title": "Abstract arXiv:2502.02486v1 [stat.ML] 4 Feb 2025", "date": "", "ddg_snippet": "Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range [0, R], and their regret scales polynomially with this reward range R. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.02486", "content": "Typical contextual bandit algorithms assume that the rewards at each round lie in some fixed range [0, R], and their regret scales polynomially with this reward range R. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this paper, we develop an algorithmic approach building on Catoni ..."}

data/sampled_jsons/Catoni_Contextual_Bandits_Table_1_comparison_algorithms_stochastic_contextual_bandits.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Abstract arXiv:2502.02486v1 [stat.ML] 4 Feb 2025 Catoni Cont", "date": "", "ddg_snippet": "Table 1 : Comparison between different algorithms for stochastic contextual bandits , where d denotes the dimension for linear function approximation, dF, ̃dF capture the complexity of the function space for reward estimation, T is the number of rounds, σt is the variance of the observed reward at round F used t, σ is a uniform bound on reward ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.02486", "content": "Table 1 : Comparison between different algorithms for stochastic contextual bandits , where d denotes the dimension for linear function approximation, dF, ̃dF capture the complexity of the function space for reward estimation, T is the number of rounds, σt is the variance of the observed reward at round F used t, σ is a uniform bound on reward ..."}
+{"idx": 1, "title": "Contexts can be Cheap: Solving Stochastic Contextual Bandits ...", "date": "", "ddg_snippet": "We show in this paper the surprising result that, provided the context comes from a distribution D ( stochastic context ), contextual linear bandit problems can be reduced to solving (single context ) √ linear bandit problem when the context distribution D is known, and to linear bandits with ̃O( 1 / T ) misspecification when the distribution D is unknown. These results are presented in the ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v195/hanna23a/hanna23a.pdf", "content": "We show in this paper the surprising result that, provided the context comes from a distribution D ( stochastic context ), contextual linear bandit problems can be reduced to solving (single context ) √ linear bandit problem when the context distribution D is known, and to linear bandits with ̃O( 1 / T ) misspecification when the distribution D is unknown. These results are presented in the ..."}
+{"idx": 2, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "The Goal • : obtain performance guarantees depending on the reward vari-ance, not the worst-case range Table : Comparison between different algorithms for stochastic contextual", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/media/icml-2025/Slides/46438.pdf", "content": "The Goal • : obtain performance guarantees depending on the reward vari-ance, not the worst-case range Table : Comparison between different algorithms for stochastic contextual"}
+{"idx": 3, "title": "Contextual Bandits with Stochastic Experts Catoni Contextual Bandits are Robust to Heavy-tailed Rewards Optimal Algorithms for Stochastic Contextual Preference Bandits Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "A Tier 1 USDOT University Transportation Center at The University of Texas at Austin D-STOP is a collaborative initiative by researchers at the Center for Transportation Research and the Wireless Networking and Communications Group at The University of Texas at Austin. See full list on ctr.utexas.edu The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the U.S. Department of Transportation’s University Transportation Centers Program, in the interest of information exchange. The U.S. Government a... See full list on ctr.utexas.edu The authors recognize that support for this research was provided by a grant from the U.S. Department of Transportation, University Transportation Centers. See full list on ctr.utexas.edu Abstract We consider the problem of contextual bandits with stochastic experts, which is a variation of the traditional stochastic contextual bandit with experts problem. In our problem setting, we assume access to a class of stochastic experts, where each expert is a conditional distribution over the arms given a context. We propose upper-con denc... See full list on ctr.utexas.edu In this section, we propose a general upper-con dence bound (UCB) style strategy that utilizes the structure of the problem to converge to the best expert much faster than a naive UCB strategy that treats each expert as an arm of the bandit problem. One of the key observations in this framework is that rewards collected under one expert can give us... See full list on ctr.utexas.edu In this section we de ne two estimators for estimating the mean rewards under a given expert. Both these estimators can e ectively leverage the information leakage between samples collected under various experts, through importance sampling. One key observation that enables us in doing so is the following equation, See full list on ctr.utexas.edu We study the problem of contextual bandits with stochastic experts. We propose two UCB style algorithms , that use two di erent importance sampling estimators, which can leverage information leakage between the stochastic experts. We provide instance-dependent regret guarantees for our UCB based algorithms . Our algorithms show strong empirical perfo... See full list on ctr.utexas.edu This paper develops an algorithmic approach building on Catoni 's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ... 1 Introduction Sequential decision-making problems with side information (in the form of features or attributes), have been popular in machine learning as contextual bandits [16, 13, 26]. A contextual bandit learner, at each round, observes a context before taking action based on it. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this pa-per, we develop an algorithmic approach building on Catoni ’s estimator from robust statistics, and apply it to contextual bandits with general func-tion approximation.", "subpage_snippet": "", "source": "ctr.utexas.edu", "link": "https://ctr.utexas.edu/wp-content/uploads/146.pdf", "content": "A Tier 1 USDOT University Transportation Center at The University of Texas at Austin D-STOP is a collaborative initiative by researchers at the Center for Transportation Research and the Wireless Networking and Communications Group at The University of Texas at Austin. See full list on ctr.utexas.edu The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the U.S. Department of Transportation’s University Transportation Centers Program, in the interest of information exchange. The U.S. Government a... See full list on ctr.utexas.edu The authors recognize that support for this research was provided by a grant from the U.S. Department of Transportation, University Transportation Centers. See full list on ctr.utexas.edu Abstract We consider the problem of contextual bandits with stochastic experts, which is a variation of the traditional stochastic contextual bandit with experts problem. In our problem setting, we assume access to a class of stochastic experts, where each expert is a conditional distribution over the arms given a context. We propose upper-con denc... See full list on ctr.utexas.edu In this section, we propose a general upper-con dence bound (UCB) style strategy that utilizes the structure of the problem to converge to the best expert much faster than a naive UCB strategy that treats each expert as an arm of the bandit problem. One of the key observations in this framework is that rewards collected under one expert can give us... See full list on ctr.utexas.edu In this section we de ne two estimators for estimating the mean rewards under a given expert. Both these estimators can e ectively leverage the information leakage between samples collected under various experts, through importance sampling. One key observation that enables us in doing so is the following equation, See full list on ctr.utexas.edu We study the problem of contextual bandits with stochastic experts. We propose two UCB style algorithms , that use two di erent importance sampling estimators, which can leverage information leakage between the stochastic experts. We provide instance-dependent regret guarantees for our UCB based algorithms . Our algorithms show strong empirical perfo... See full list on ctr.utexas.edu This paper develops an algorithmic approach building on Catoni 's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ... 1 Introduction Sequential decision-making problems with side information (in the form of features or attributes), have been popular in machine learning as contextual bandits [16, 13, 26]. A contextual bandit learner, at each round, observes a context before taking action based on it. However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this pa-per, we develop an algorithmic approach building on Catoni ’s estimator from robust statistics, and apply it to contextual bandits with general func-tion approximation."}
+{"idx": 4, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "This paper develops an algorithmic approach building on Catoni 's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ...", "subpage_snippet": "", "source": "www.semanticscholar.org", "link": "https://www.semanticscholar.org/paper/Catoni-Contextual-Bandits-are-Robust-to-Rewards-Ye-Jin/125154c306493f2c7af8e8c09c0e58c22106e6fe", "content": "This paper develops an algorithmic approach building on Catoni 's estimator from robust statistics, and applies it to contextual bandits with general function approximation and establishes a regret bound that depends only on the cumulative reward variance and logarithmically on the reward range as well as the number of rounds. Typical contextual bandit algorithms assume that the rewards at each ..."}
+{"idx": 5, "title": "Optimal Algorithms for Stochastic Contextual Preference Bandits", "date": "", "ddg_snippet": "1 Introduction Sequential decision-making problems with side information (in the form of features or attributes), have been popular in machine learning as contextual bandits [16, 13, 26]. A contextual bandit learner, at each round, observes a context before taking action based on it.", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper/2021/file/fc3cf452d3da8402bebb765225ce8c0e-Paper.pdf", "content": "1 Introduction Sequential decision-making problems with side information (in the form of features or attributes), have been popular in machine learning as contextual bandits [16, 13, 26]. A contextual bandit learner, at each round, observes a context before taking action based on it."}
+{"idx": 6, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed Rewards", "date": "", "ddg_snippet": "However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this pa-per, we develop an algorithmic approach building on Catoni ’s estimator from robust statistics, and apply it to contextual bandits with general func-tion approximation.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=5IpVe9PH14", "content": "However, many practical scenarios naturally involve heavy-tailed rewards or rewards where the worst-case range can be substantially larger than the variance. In this pa-per, we develop an algorithmic approach building on Catoni ’s estimator from robust statistics, and apply it to contextual bandits with general func-tion approximation."}
+{"idx": 7, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed ...", "date": "", "ddg_snippet": "by C Ye · 2025 · Cited by 1 — 1. Page 2. Table 1: Comparison between different algorithms for stochastic contextual bandits , where d denotes the dimension for linear ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2502.02486?", "content": "by C Ye · 2025 · Cited by 1 — 1. Page 2. Table 1: Comparison between different algorithms for stochastic contextual bandits , where d denotes the dimension for linear ..."}
+{"idx": 8, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed ...", "date": "", "ddg_snippet": "In this paper, we study the design of contextual bandit algorithms that can leverage such structures to have regret guarantees dependent polynomially on the ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46438", "content": "In this paper, we study the design of contextual bandit algorithms that can leverage such structures to have regret guarantees dependent polynomially on the ..."}
+{"idx": 9, "title": "Catoni Contextual Bandits are Robust to Heavy-tailed ...", "date": "", "ddg_snippet": "Most of the claims are well-supported. Extensive comparisons (see Table 1) with existing algorithms highlight the advantages of the proposed methods in heavy- ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=5IpVe9PH14&noteId=J3K6uYfoM5", "content": "Most of the claims are well-supported. Extensive comparisons (see Table 1) with existing algorithms highlight the advantages of the proposed methods in heavy- ..."}

data/sampled_jsons/Causal_Modeling_of_Climate_Activism_on_Reddit_correlation_engagement_participation_rich_subreddits_0_year_2024.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Using Reddit to Understand Car-Free", "date": "", "ddg_snippet": "by E Iacobucci · 2021 · Cited by 1 — They interpret these results to suggest a causal role between a change in neighborhood and changes in travel behavior. ... Disentangling causation from ...", "subpage_snippet": "", "source": "rucore.libraries.rutgers.edu", "link": "https://rucore.libraries.rutgers.edu/rutgers-lib/66787/PDF/1/play/", "content": "by E Iacobucci · 2021 · Cited by 1 — They interpret these results to suggest a causal role between a change in neighborhood and changes in travel behavior. ... Disentangling causation from ..."}
+{"idx": 1, "title": "Understanding, Modeling and Leveraging Temporal ...", "date": "", "ddg_snippet": "Similarly, affiliation behaviors on Reddit have also been used to identify individuals with mental health conditions. Participation in subreddits such as r ...", "subpage_snippet": "", "source": "deepblue.lib.umich.edu", "link": "https://deepblue.lib.umich.edu/bitstream/handle/2027.42/177722/lbiester_1.pdf?sequence=1&isAllowed=y", "content": "Similarly, affiliation behaviors on Reddit have also been used to identify individuals with mental health conditions. Participation in subreddits such as r ..."}
+{"idx": 2, "title": "Reddit's self-organised bull runs: Social contagion and asset ...", "date": "", "ddg_snippet": "by V Semenova · 2021 · Cited by 27 — This paper develops an empirical and theoretical case for how 'hype' among retail investors can drive large asset fluctuations. 51 pages", "subpage_snippet": "", "source": "oms-inet.files.svdcdn.com", "link": "https://oms-inet.files.svdcdn.com/staging/files/Reddit_draft_v2.pdf", "content": "by V Semenova · 2021 · Cited by 27 — This paper develops an empirical and theoretical case for how 'hype' among retail investors can drive large asset fluctuations. 51 pages"}
+{"idx": 3, "title": "Participant behavior and community response in online ...", "date": "", "ddg_snippet": "by V Morini · 2025 · Cited by 2 — This study analyzed a large-scale, five-year Reddit dataset of 67 MH-related subreddits , comprising over 3.4 million posts and 24 million comments from ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0747563224004126", "content": "by V Morini · 2025 · Cited by 2 — This study analyzed a large-scale, five-year Reddit dataset of 67 MH-related subreddits , comprising over 3.4 million posts and 24 million comments from ..."}
+{"idx": 4, "title": "A Synthetic Dataset for Personal Attribute Inference", "date": "", "ddg_snippet": "by H Yukhymenko · 2024 · Cited by 20 — We take two steps to address this problem: (i) we construct a simulation framework for the popular social media platform Reddit using LLM agents seeded with ... 45 pages", "subpage_snippet": "", "source": "proceedings.neurips.cc", "link": "https://proceedings.neurips.cc/paper_files/paper/2024/file/daa1816b84ca2d5051c87fb4d37dd540-Paper-Datasets_and_Benchmarks_Track.pdf", "content": "by H Yukhymenko · 2024 · Cited by 20 — We take two steps to address this problem: (i) we construct a simulation framework for the popular social media platform Reddit using LLM agents seeded with ... 45 pages"}
+{"idx": 5, "title": "Exploring Suicide Factors in Online Discourse: Sentiment and ...", "date": "", "ddg_snippet": "by E Dan — This study aims to leverage NLP and statistical analysis of Reddit data to investigate the factors contributing to suicidal ideation. Specifically, our analysis ...", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/pdf/10.1145/3716546", "content": "by E Dan — This study aims to leverage NLP and statistical analysis of Reddit data to investigate the factors contributing to suicidal ideation. Specifically, our analysis ..."}
+{"idx": 6, "title": "Prevalence and Psychological Effects of Hateful Speech in ...", "date": "", "ddg_snippet": "by K Saha · 2019 · Cited by 238 — We find that hateful speech is prevalent in college subreddits , and 25% of them show greater hateful speech than non-college subreddits .", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7500692/", "content": "by K Saha · 2019 · Cited by 238 — We find that hateful speech is prevalent in college subreddits , and 25% of them show greater hateful speech than non-college subreddits ."}
+{"idx": 7, "title": "Computer Science", "date": "", "ddg_snippet": "Using base models , we achieved a Spearman correlation of 0.8 with human ratings, which increased to 0.9 when employing fine-tuned models . This methodology ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/list/cs/new", "content": "Using base models , we achieved a Spearman correlation of 0.8 with human ratings, which increased to 0.9 when employing fine-tuned models . This methodology ..."}
+{"idx": 8, "title": "SOCIALLY-INFORMED CONTENT ANALYSIS OF ONLINE ...", "date": "", "ddg_snippet": "13 Sept 2025 — This research focuses on the role of social approval in driving online toxicity, suggesting that the pursuit of social approval, rather than a ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2509.10807v1", "content": "13 Sept 2025 — This research focuses on the role of social approval in driving online toxicity, suggesting that the pursuit of social approval, rather than a ..."}
+{"idx": 9, "title": "NLP4PI 2025 Fourth Workshop on NLP for Positive Impact ...", "date": "", "ddg_snippet": "31 Jul 2025 — These papers cover diverse aspects of NLP for positive impact, including developing NLP technology to help applications like physical and mental ...", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/anthology-files/pdf/nlp4pi/2025.nlp4pi-1.pdf", "content": "31 Jul 2025 — These papers cover diverse aspects of NLP for positive impact, including developing NLP technology to help applications like physical and mental ..."}

data/sampled_jsons/Checks-and-Balances_Framework_Context-Aware_Ethical_AI_Alignment_Section_3.2_four-step_self-supervis.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Checks-and-Balances Framework for Context-Aware Ethical AI ... A Three-Branch Checks-and-Balances Framework for Context-Aware... An Adversarial Behavior Model for Contextual Ethical ... A Three-Branch Checks-and-Balances Frameworkfor Context-Aware ... A Three-Branch Checks-and-Balances Frameworkfor Context-Aware ... infolab.stanford.edu Ethical Guardrails for AI: A Checks-and-Balances Approach", "date": "", "ddg_snippet": "Jan 31, 2025 · 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 ... Oct 12, 2024 · 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. 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 ... Jan 31, 2025 · This paper introduces a three-branch checks-and-balances framework for ethical alignment of Large Language Models (LLMs), inspired by 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 ... 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. @article{chang2025threebranch, title={A Three-Branch Checks-and-Balances Framework for Context-Aware Ethical Alignment of Large Language Models}, author={Chang ... A Three-Branch Checks-and-Balances Framework for Context-Aware Ethical Alignment of Large Language Models 48 | 124", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2502.00136", "content": "Jan 31, 2025 · 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 ... Oct 12, 2024 · 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. 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 ... Jan 31, 2025 · This paper introduces a three-branch checks-and-balances framework for ethical alignment of Large Language Models (LLMs), inspired by 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 ... 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. @article{chang2025threebranch, title={A Three-Branch Checks-and-Balances Framework for Context-Aware Ethical Alignment of Large Language Models}, author={Chang ... A Three-Branch Checks-and-Balances Framework for Context-Aware Ethical Alignment of Large Language Models 48 | 124"}
+{"idx": 1, "title": "A Three-Branch Checks-and-Balances Framework for Context-Aware...", "date": "", "ddg_snippet": "Oct 12, 2024 · 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": "Oct 12, 2024 · 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."}
+{"idx": 2, "title": "An Adversarial Behavior Model for Contextual Ethical ...", "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 ..."}
+{"idx": 3, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware ...", "date": "", "ddg_snippet": "Jan 31, 2025 · This paper introduces a three-branch checks-and-balances framework for ethical alignment of Large Language Models (LLMs), inspired by 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": "researchtrend.ai", "link": "https://researchtrend.ai/papers/2502.00136", "content": "Jan 31, 2025 · This paper introduces a three-branch checks-and-balances framework for ethical alignment of Large Language Models (LLMs), inspired by 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 ..."}
+{"idx": 4, "title": "A Three-Branch Checks-and-Balances Frameworkfor Context-Aware ...", "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."}
+{"idx": 5, "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"}
+{"idx": 6, "title": "Navigating the ethical landscape of AI... | F1000Research", "date": "", "ddg_snippet": "... for ethical AI deployment are encapsulated in frameworks like the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems ( IEEE, 2016 ...", "subpage_snippet": "", "source": "f1000research.com", "link": "https://f1000research.com/articles/14-299", "content": "... for ethical AI deployment are encapsulated in frameworks like the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems ( IEEE, 2016 ..."}
+{"idx": 7, "title": "Multi-level Value Alignment in Agentic AI Systems: Survey and", "date": "", "ddg_snippet": "This has brought significant attention to value alignment for agentic AI systems, which aims to ensure that an agent’s goals, preferences, and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.09656v2", "content": "This has brought significant attention to value alignment for agentic AI systems, which aims to ensure that an agent’s goals, preferences, and ..."}
+{"idx": 8, "title": "(PDF) A Unified Framework for Human AI Collaboration in", "date": "", "ddg_snippet": "... presents a structured framework for Human- AI collaboration in Security Operations Centers (SOCs), integrating AI autonomy, trust calibration, and ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/392204042_A_Unified_Framework_for_Human_AI_Collaboration_in_Security_Operations_Centers_with_Trusted_Autonomy", "content": "... presents a structured framework for Human- AI collaboration in Security Operations Centers (SOCs), integrating AI autonomy, trust calibration, and ..."}
+{"idx": 9, "title": "[Intro to brain-like-AGI safety] 10. The alignment problem -", "date": "", "ddg_snippet": "In Section 10. 2 , I’ll define “inner alignment ” and “outer alignment ” in the context of our brain-like-AGI motivation system.", "subpage_snippet": "", "source": "www.greaterwrong.com", "link": "https://www.greaterwrong.com/posts/wucncPjud27mLWZzQ/intro-to-brain-like-agi-safety-10-the-alignment-problem", "content": "In Section 10. 2 , I’ll define “inner alignment ” and “outer alignment ” in the context of our brain-like-AGI motivation system."}

data/sampled_jsons/Checks-and-Balances_Framework_for_Context-Aware_Ethical_AI_Alignment_dataset_empirical_studies_choic.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "A Unified Framework for Evaluating the Effectiveness and", "date": "", "ddg_snippet": "... organized as follows: Section 2 provides an overview of earlier studies in this area, establishing the foundational work and context for our research.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2412.03884v2", "content": "... organized as follows: Section 2 provides an overview of earlier studies in this area, establishing the foundational work and context for our research."}
+{"idx": 1, "title": "Understanding Ethical Practices in AI: Insights from a", "date": "", "ddg_snippet": "... systematically examines their knowledge and perceptions of AI ethics and its associated principles, regulatory initiatives, and best practices for ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2508.09219v1", "content": "... systematically examines their knowledge and perceptions of AI ethics and its associated principles, regulatory initiatives, and best practices for ..."}
+{"idx": 2, "title": "Multi-level Value Alignment in Agentic AI Systems: Survey and", "date": "", "ddg_snippet": "This has brought significant attention to value alignment for agentic AI systems, which aims to ensure that an agent’s goals, preferences, and ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2506.09656v2", "content": "This has brought significant attention to value alignment for agentic AI systems, which aims to ensure that an agent’s goals, preferences, and ..."}
+{"idx": 3, "title": "Splits! A Flexible Dataset and Evaluation Framework for", "date": "", "ddg_snippet": "For instance, in the context of “healthy eating,” American students tend to use a vocabulary of balancing food groups and avoiding fat and sugar ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.04640v2", "content": "For instance, in the context of “healthy eating,” American students tend to use a vocabulary of balancing food groups and avoiding fat and sugar ..."}
+{"idx": 4, "title": "64 questions with answers in CONTEXT-AWARENESS | Science topic", "date": "", "ddg_snippet": "... for neutral or generic urban settings, their application in cities with sacred significance—such as Karbala or Najaf—requires a more sensitive and ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/topic/Context-Awareness", "content": "... for neutral or generic urban settings, their application in cities with sacred significance—such as Karbala or Najaf—requires a more sensitive and ..."}
+{"idx": 5, "title": "Responsible AI in NLP: GUS-Net Span-Level Bias Detection", "date": "", "ddg_snippet": "We introduce the GUS-Net Framework , comprising the GUS dataset and a multi-label token-level detector for span-level analysis of social bias.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2410.08388v5", "content": "We introduce the GUS-Net Framework , comprising the GUS dataset and a multi-label token-level detector for span-level analysis of social bias."}
+{"idx": 6, "title": "Perspectives on Managing AI Ethics in the Digital Age", "date": "", "ddg_snippet": "... Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and ...", "subpage_snippet": "", "source": "www.mdpi.com", "link": "https://www.mdpi.com/2078-2489/16/4/318", "content": "... Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and ..."}
+{"idx": 7, "title": "Search AI ethics Primer bibliography", "date": "", "ddg_snippet": "RobertoLofaro.com - Knowledge Portal - human-generated content Change, with and without technology for updates on publications, follow @robertolofaro ...", "subpage_snippet": "", "source": "robertolofaro.com", "link": "https://robertolofaro.com/searchkaggleaiethics.php", "content": "RobertoLofaro.com - Knowledge Portal - human-generated content Change, with and without technology for updates on publications, follow @robertolofaro ..."}
+{"idx": 8, "title": "Search AI ethics Primer bibliography", "date": "", "ddg_snippet": "RobertoLofaro.com - Knowledge Portal - human-generated content Change, with and without technology for updates on publications, follow @robertolofaro ...", "subpage_snippet": "", "source": "robertolofaro.com", "link": "http://robertolofaro.com/searchkaggleaiethics.php", "content": "RobertoLofaro.com - Knowledge Portal - human-generated content Change, with and without technology for updates on publications, follow @robertolofaro ..."}
+{"idx": 9, "title": "From Paperclips to Bombs: The Evolution of AI Risk Discourse on", "date": "", "ddg_snippet": "This study aims to investigate how the AI risk discourse is constructed and how it transforms on the LessWrong forum following these major AI ...", "subpage_snippet": "", "source": "www.greaterwrong.com", "link": "https://www.greaterwrong.com/posts/utx8jjAAumeZAu8oz/from-paperclips-to-bombs-the-evolution-of-ai-risk-discourse", "content": "This study aims to investigate how the AI risk discourse is constructed and how it transforms on the LessWrong forum following these major AI ..."}

data/sampled_jsons/Chen_et_al._2023_preference-based_reinforcement_learning_abstract_year_2023.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "PRIMT: Preference-based Reinforcement Learning with Multimodal Feedback ...", "date": "", "ddg_snippet": "Reinforcement learning (RL) has shown great success in various robotics domains [1-4], yet it remains reliant on carefully designed reward functions. In many practical scenarios, designing an informative reward function is highly challenging, as task objectives are often implicit and multi- faceted [5]. Preference-based RL (PbRL) [6-8] has emerged as a promising alternative to address this ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2509.15607", "content": "Reinforcement learning (RL) has shown great success in various robotics domains [1-4], yet it remains reliant on carefully designed reward functions. In many practical scenarios, designing an informative reward function is highly challenging, as task objectives are often implicit and multi- faceted [5]. Preference-based RL (PbRL) [6-8] has emerged as a promising alternative to address this ..."}
+{"idx": 1, "title": "Advances in Preference-based Reinforcement Learning: A Review", "date": "", "ddg_snippet": "Reinforcement Learning (RL) algorithms suffer from the dependency on accurately engineered reward functions to properly guide the learning agents to do the required tasks. Preference-based reinforcement learning (PbRL) addresses that by utilizing human preferences as feedback from the experts instead of numeric rewards. Due to its promising advantage over traditional RL, PbRL has gained more ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/abstract/document/9945333", "content": "Reinforcement Learning (RL) algorithms suffer from the dependency on accurately engineered reward functions to properly guide the learning agents to do the required tasks. Preference-based reinforcement learning (PbRL) addresses that by utilizing human preferences as feedback from the experts instead of numeric rewards. Due to its promising advantage over traditional RL, PbRL has gained more ..."}
+{"idx": 2, "title": "PDF P R -agnostic Preference-based Reinforcement Learning", "date": "", "ddg_snippet": "ABSTRACT Preference-based Reinforcement Learning (PbRL) is a paradigm in which an RL agent learns to optimize a task using pair-wise preference-based feedback over trajectories, rather than explicit reward signals. While PbRL has demonstrated practical success in fine-tuning language models, existing theoretical work focuses on regret minimization and fails to capture most of the practical ...", "subpage_snippet": "", "source": "proceedings.iclr.cc", "link": "https://proceedings.iclr.cc/paper_files/paper/2024/file/1a10956f2cd9b41c0283a7af34b9c728-Paper-Conference.pdf", "content": "ABSTRACT Preference-based Reinforcement Learning (PbRL) is a paradigm in which an RL agent learns to optimize a task using pair-wise preference-based feedback over trajectories, rather than explicit reward signals. While PbRL has demonstrated practical success in fine-tuning language models, existing theoretical work focuses on regret minimization and fails to capture most of the practical ..."}
+{"idx": 3, "title": "PDF Human-in-the-loop: Provably Efficient Preference-based Reinforcement ...", "date": "", "ddg_snippet": "1. Introduction Reinforcement learning (RL) is concerned with sequential decision-making problems in which the agent interacts with the environment to maximize its cumulative rewards. This framework has achieved tremendous successes in various fields such as Atari games (Mnih et al ., 2013), Go (Silver et al ., 2017), and StarCraft (Vinyals et al ., 2019). While these empirical successes are ...", "subpage_snippet": "", "source": "proceedings.mlr.press", "link": "https://proceedings.mlr.press/v162/chen22ag/chen22ag.pdf", "content": "1. Introduction Reinforcement learning (RL) is concerned with sequential decision-making problems in which the agent interacts with the environment to maximize its cumulative rewards. This framework has achieved tremendous successes in various fields such as Atari games (Mnih et al ., 2013), Go (Silver et al ., 2017), and StarCraft (Vinyals et al ., 2019). While these empirical successes are ..."}
+{"idx": 4, "title": "PDF RIME: Robust Preference-based Reinforcement Learning with ... - GitHub", "date": "", "ddg_snippet": "Abstract Preference-based Reinforcement Learning (PbRL) circumvents the need for reward engi-neering by harnessing human preferences as the reward signal. However, current PbRL methods excessively depend on high-quality feedback from domain experts, which results in a lack of robustness. In this paper, we present RIME,", "subpage_snippet": "", "source": "raw.githubusercontent.com", "link": "https://raw.githubusercontent.com/mlresearch/v235/main/assets/cheng24k/cheng24k.pdf", "content": "Abstract Preference-based Reinforcement Learning (PbRL) circumvents the need for reward engi-neering by harnessing human preferences as the reward signal. However, current PbRL methods excessively depend on high-quality feedback from domain experts, which results in a lack of robustness. In this paper, we present RIME,"}
+{"idx": 5, "title": "Decoding Global Preferences: Temporal and Cooperative Dependency ...", "date": "", "ddg_snippet": "Abstract Designing accurate reward functions for reinforcement learn-ing (RL) has long been challenging. Preference-based RL (PbRL) offers a promising approach by using human pref-erences to train agents, eliminating the need for manual re-ward design. While successful in single-agent tasks, extend-ing PbRL to complex multi-agent scenarios is nontrivial. Ex-isting PbRL methods lack the ...", "subpage_snippet": "", "source": "ojs.aaai.org", "link": "https://ojs.aaai.org/index.php/AAAI/article/download/29666/31137", "content": "Abstract Designing accurate reward functions for reinforcement learn-ing (RL) has long been challenging. Preference-based RL (PbRL) offers a promising approach by using human pref-erences to train agents, eliminating the need for manual re-ward design. While successful in single-agent tasks, extend-ing PbRL to complex multi-agent scenarios is nontrivial. Ex-isting PbRL methods lack the ..."}
+{"idx": 6, "title": "Online Preference-based Reinforcement Learning with Self-augmented ...", "date": "", "ddg_snippet": "Abstract Preference-based reinforcement learning (PbRL) provides a powerful paradigm to avoid meticulous reward engineering by learning rewards based on human preferences . However, real-time human feedback is hard to obtain in online tasks.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/10.5555/3709347.3743845", "content": "Abstract Preference-based reinforcement learning (PbRL) provides a powerful paradigm to avoid meticulous reward engineering by learning rewards based on human preferences . However, real-time human feedback is hard to obtain in online tasks."}
+{"idx": 7, "title": "Efficient Preference-Based Reinforcement Learning Using Learned ...", "date": "", "ddg_snippet": "Preference-based reinforcement learning (PbRL) can enable robots to learn to perform tasks based on an individual's preferences without requiring a hand-crafted re-ward function. However, existing approaches either assume access to a high-fidelity simulator or analytic model or take a model-free approach that requires extensive, possibly unsafe online environment interactions. In this paper ...", "subpage_snippet": "", "source": "ieeexplore.ieee.org", "link": "https://ieeexplore.ieee.org/document/10161081", "content": "Preference-based reinforcement learning (PbRL) can enable robots to learn to perform tasks based on an individual's preferences without requiring a hand-crafted re-ward function. However, existing approaches either assume access to a high-fidelity simulator or analytic model or take a model-free approach that requires extensive, possibly unsafe online environment interactions. In this paper ..."}
+{"idx": 8, "title": "Q -e Offline Preference-based Re Inforcement Learning Via In-dataset ...", "date": "", "ddg_snippet": "ABSTRACT Preference-based reinforcement learning has shown great promise in various ap-plications to avoid reward annotations and align better with human intentions. However, obtaining preference feedback can still be expensive or time-consuming, which forms a strong barrier for preference-based RL. In this paper, we propose a novel approach to improve the query eficiency of ofline preference ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf?id=GOvTGntFNj", "content": "ABSTRACT Preference-based reinforcement learning has shown great promise in various ap-plications to avoid reward annotations and align better with human intentions. However, obtaining preference feedback can still be expensive or time-consuming, which forms a strong barrier for preference-based RL. In this paper, we propose a novel approach to improve the query eficiency of ofline preference ..."}
+{"idx": 9, "title": "Offline Multi-Agent Preference-based Reinforcement Learning with Agent ...", "date": "", "ddg_snippet": "Abstract Multi-agent Preference-Based Reinforcement Learning (MAPbRL) is promising in offline policy learning by leveraging human preferences to replace complex manual reward designing. Current MAPbRL methods use complicated structures to realize better reward modeling with off-the-shelf MARL algorithms and obtain the joint policy based on it.", "subpage_snippet": "", "source": "dl.acm.org", "link": "https://dl.acm.org/doi/epdf/10.5555/3709347.3743639", "content": "Abstract Multi-agent Preference-Based Reinforcement Learning (MAPbRL) is promising in offline policy learning by leveraging human preferences to replace complex manual reward designing. Current MAPbRL methods use complicated structures to realize better reward modeling with off-the-shelf MARL algorithms and obtain the joint policy based on it."}

data/sampled_jsons/CoPINN_Cognitive_Physics-Informed_Neural_Networks.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CoPINN: Cognitive Physics-Informed Neural Networks", "date": "", "ddg_snippet": "CoPINN: Cognitive Physics-Informed Neural Networks . Download PDF. Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, Yuan Sun. Published: 01 May 2025 ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=4vAa0A98xI&noteId=Z6OLWcPple", "content": "CoPINN: Cognitive Physics-Informed Neural Networks . Download PDF. Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, Yuan Sun. Published: 01 May 2025 ..."}
+{"idx": 1, "title": "CoPINN: Cognitive Physics-Informed Neural Networks", "date": "", "ddg_snippet": "16 Jul 2025 — CoPINN: Cognitive Physics-Informed Neural Networks . Siyuan Duan · Wenyuan Wu · Peng Hu · Zhenwen Ren · Dezhong Peng · Yuan Sun. East ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/poster/46458", "content": "16 Jul 2025 — CoPINN: Cognitive Physics-Informed Neural Networks . Siyuan Duan · Wenyuan Wu · Peng Hu · Zhenwen Ren · Dezhong Peng · Yuan Sun. East ..."}
+{"idx": 2, "title": "Physics-Informed NNs: tips & tricks, literature repo, success ...", "date": "", "ddg_snippet": "CoPINN: Cognitive physics-informed neural networks . ICML, 2025. paper. Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, and Yuan ...", "subpage_snippet": "", "source": "hodgesj.substack.com", "link": "https://hodgesj.substack.com/p/physics-informed-nns-tips-and-tricks", "content": "CoPINN: Cognitive physics-informed neural networks . ICML, 2025. paper. Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, and Yuan ..."}
+{"idx": 3, "title": "CoPINN: Cognitive Physics-Informed Neural Networks", "date": "", "ddg_snippet": "CoPINN: Cognitive Physics-Informed Neural Networks . ICML 202518 Jun 2025. Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, Yuan Sun. Sichuan ...", "subpage_snippet": "", "source": "chatpaper.com", "link": "https://chatpaper.com/ja/chatpaper/paper/165180", "content": "CoPINN: Cognitive Physics-Informed Neural Networks . ICML 202518 Jun 2025. Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, Yuan Sun. Sichuan ..."}
+{"idx": 4, "title": "CoPINN: Cognitive Physics-Informed Neural Networks", "date": "", "ddg_snippet": "CoPINN: Cognitive Physics-Informed Neural Networks | Read Paper on Bytez.", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/icml/46458/code?_c=eyJ2IjoxLCJyZWxhdGVkIjpbImNvZGUiLCJyZWZlcmVuY2VzIiwiY29uZmVyZW5jZSJdfQ==", "content": "CoPINN: Cognitive Physics-Informed Neural Networks | Read Paper on Bytez."}
+{"idx": 5, "title": "Siyuan Duan (段思远)", "date": "", "ddg_snippet": "CoPINN: Cognitive Physics-Informed Neural Networks . S Duan, W Wu, P Hu, Z Ren, D Peng, Y Sun. Forty-second International Conference on Machine Learning., 2025.", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=Zck_72MAAAAJ&hl=en", "content": "CoPINN: Cognitive Physics-Informed Neural Networks . S Duan, W Wu, P Hu, Z Ren, D Peng, Y Sun. Forty-second International Conference on Machine Learning., 2025."}
+{"idx": 6, "title": "siyuancncd/FPINNs", "date": "", "ddg_snippet": "@inproceedings{duancopinn, title={ CoPINN: Cognitive Physics-Informed Neural Networks }, author={Duan, Siyuan and Wu, Wenyuan and Hu, Peng and Ren, Zhenwen ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/siyuancncd/FPINNs", "content": "@inproceedings{duancopinn, title={ CoPINN: Cognitive Physics-Informed Neural Networks }, author={Duan, Siyuan and Wu, Wenyuan and Hu, Peng and Ren, Zhenwen ..."}
+{"idx": 7, "title": "Siyuan Duan", "date": "", "ddg_snippet": "CoPINN: Cognitive Physics-Informed Neural Networks · Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, Yuan Sun. Published: 01 May 2025, Last ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/profile?id=~Siyuan_Duan1", "content": "CoPINN: Cognitive Physics-Informed Neural Networks · Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng, Yuan Sun. Published: 01 May 2025, Last ..."}
+{"idx": 8, "title": "Wenyuan Wu", "date": "", "ddg_snippet": "Co-authors ; CoPINN: Cognitive Physics-Informed Neural Networks . S Duan, W Wu, P Hu, Z Ren, D Peng, Y Sun. Forty-second International Conference on Machine ...", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=sjtjpmoAAAAJ&hl=en", "content": "Co-authors ; CoPINN: Cognitive Physics-Informed Neural Networks . S Duan, W Wu, P Hu, Z Ren, D Peng, Y Sun. Forty-second International Conference on Machine ..."}
+{"idx": 9, "title": "ICML 2025 Papers", "date": "", "ddg_snippet": "CoPINN: Cognitive Physics-Informed Neural Networks · Adversarial Robust Generalization of Graph Neural Networks · Open Your Eyes: Vision Enhances Message ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/virtual/2025/papers.html", "content": "CoPINN: Cognitive Physics-Informed Neural Networks · Adversarial Robust Generalization of Graph Neural Networks · Open Your Eyes: Vision Enhances Message ..."}

data/sampled_jsons/CogAgent_visual_language_model_GUI_agents_Hong.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CogAgent : A Visual Language Model for GUI Agents", "date": "", "ddg_snippet": "Agents based on visual language models (VLMs) have the potential to overcome these limitations.Figure 1. Samples of visual agents generated by CogAgent . More samples are demonstrated in the Appendix.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2024/papers/Hong_CogAgent_A_Visual_Language_Model_for_GUI_Agents_CVPR_2024_paper.pdf", "content": "Agents based on visual language models (VLMs) have the potential to overcome these limitations.Figure 1. Samples of visual agents generated by CogAgent . More samples are demonstrated in the Appendix."}
+{"idx": 1, "title": "[2312.08914] CogAgent : A Visual Language Model for GUI Agents", "date": "", "ddg_snippet": "View a PDF of the paper titled CogAgent : A Visual Language Model for GUI Agents , by Wenyi Hong and 13 other authors.In this paper, we introduce CogAgent , an 18-billion-parameter visual language model (VLM) specializing in GUI understanding and navigation.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2312.08914", "content": "View a PDF of the paper titled CogAgent : A Visual Language Model for GUI Agents , by Wenyi Hong and 13 other authors.In this paper, we introduce CogAgent , an 18-billion-parameter visual language model (VLM) specializing in GUI understanding and navigation."}
+{"idx": 2, "title": "CogAgent : A Visual Language Model for GUI Agents | OpenReview", "date": "", "ddg_snippet": "As a general-ist visual language model , CogAgent achieves the state of the art on five text-rich and four general VQA benchmarks, including VQAv2, OK- VQA, Text- Vqa, St- Vqa, ChartQA, infoVQA, DocVQA, MM-Vet, and POPE.", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/forum?id=HKg8G2vzW7&referrer=[the+profile+of+Wenyi+Hong](/profile?id=~Wenyi_Hong1)", "content": "As a general-ist visual language model , CogAgent achieves the state of the art on five text-rich and four general VQA benchmarks, including VQAv2, OK- VQA, Text- Vqa, St- Vqa, ChartQA, infoVQA, DocVQA, MM-Vet, and POPE."}
+{"idx": 3, "title": "CogAgent : A Visual Language Model for GUI Agents | Request PDF", "date": "", "ddg_snippet": "Training Vision- Language Models (VLMs) for Graphical User Interfaces ( GUI ) agents via Reinforcement Learning (RL) faces critical challenges: environment-based RL requires costly interactions, while...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/384235870_CogAgent_A_Visual_Language_Model_for_GUI_Agents", "content": "Training Vision- Language Models (VLMs) for Graphical User Interfaces ( GUI ) agents via Reinforcement Learning (RL) faces critical challenges: environment-based RL requires costly interactions, while..."}
+{"idx": 4, "title": "README.md · THUDM/ cogagent -vqa-hf at main", "date": "", "ddg_snippet": "cogagent -chat: This model has strong capabilities in GUI Agent , visual multi-turn dialogue, visual grounding, etc.title={ CogAgent : A Visual Language Model for GUI Agents }", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/THUDM/cogagent-vqa-hf/blob/main/README.md", "content": "cogagent -chat: This model has strong capabilities in GUI Agent , visual multi-turn dialogue, visual grounding, etc.title={ CogAgent : A Visual Language Model for GUI Agents }"}
+{"idx": 5, "title": "A Visual Language Model for GUI Agents", "date": "", "ddg_snippet": "CogAgent is an open-source visual language model improved based on CogVLM. CogAgent -18B has 11 billion visual parameters and 7 billion language parameters.@misc{ hong 2023 cogagent , title={ CogAgent : A Visual Language Model for GUI Agents }", "subpage_snippet": "", "source": "replicate.com", "link": "https://replicate.com/cjwbw/cogagent-chat/readme", "content": "CogAgent is an open-source visual language model improved based on CogVLM. CogAgent -18B has 11 billion visual parameters and 7 billion language parameters.@misc{ hong 2023 cogagent , title={ CogAgent : A Visual Language Model for GUI Agents }"}
+{"idx": 6, "title": "Paper tables with annotated results for CogAgent : A Visual Language ...", "date": "", "ddg_snippet": "CogAgent : A Visual Language Model for GUI Agents . People are spending an enormous amount of time on digital devices through graphical user interfaces ( GUIs ), e.g., computer or smartphone screens.", "subpage_snippet": "", "source": "paperswithcode.com", "link": "https://paperswithcode.com/paper/cogagent-a-visual-language-model-for-gui/review/?hl=114609", "content": "CogAgent : A Visual Language Model for GUI Agents . People are spending an enormous amount of time on digital devices through graphical user interfaces ( GUIs ), e.g., computer or smartphone screens."}
+{"idx": 7, "title": "Wenyi Hong - Google Scholar", "date": "", "ddg_snippet": "CogAgent : A Visual Language Model for GUI Agents .2024. Visualagentbench: Towards large multimodal models as visual foundation agents .", "subpage_snippet": "", "source": "scholar.google.com", "link": "https://scholar.google.com/citations?user=JSEzrlwAAAAJ&hl=en", "content": "CogAgent : A Visual Language Model for GUI Agents .2024. Visualagentbench: Towards large multimodal models as visual foundation agents ."}
+{"idx": 8, "title": "CogAgent : Visual Language Model for GUIs", "date": "", "ddg_snippet": "CogAgent is an 18-billion-parameter visual language model that automates GUI tasks with high-resolution input and efficient dual-resolution modules.", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/papers/2312.08914", "content": "CogAgent is an 18-billion-parameter visual language model that automates GUI tasks with high-resolution input and efficient dual-resolution modules."}
+{"idx": 9, "title": "CogAgent : A Visual Language Model for GUI Agents | AI Research...", "date": "", "ddg_snippet": "Overview CogAgent is a new visual language model designed for GUI interactionUses novel cross-module architecture for better visual - language alignment", "subpage_snippet": "", "source": "www.aimodels.fyi", "link": "https://www.aimodels.fyi/papers/arxiv/cogagent-visual-language-model-gui-agents", "content": "Overview CogAgent is a new visual language model designed for GUI interactionUses novel cross-module architecture for better visual - language alignment"}

data/sampled_jsons/Concept_Bottleneck_Models_Without_Predefined_Concepts_unsupervised_concept_discovery_foundation_mode.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "If Concept Bottlenecks are the Question, are Foundation Models", "date": "", "ddg_snippet": "Concept Bottleneck Models (CBMs) [ 41 ] combine two neural modules: a concept extractor f : 𝒳 → ℝ k : 𝑓 → 𝒳 superscript ℝ 𝑘 ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.19774v2", "content": "Concept Bottleneck Models (CBMs) [ 41 ] combine two neural modules: a concept extractor f : 𝒳 → ℝ k : 𝑓 → 𝒳 superscript ℝ 𝑘 ..."}
+{"idx": 1, "title": "Discover-then-Name: Task-Agnostic Concept Bottlenecks via", "date": "", "ddg_snippet": "Concept Bottleneck Models (CBMs) [ 31 , 60 , 37 ] are a class of inherently interpretable models that express their prediction as a linear combination ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2407.14499v2", "content": "Concept Bottleneck Models (CBMs) [ 31 , 60 , 37 ] are a class of inherently interpretable models that express their prediction as a linear combination ..."}
+{"idx": 2, "title": "Concept Bottleneck Language Models For protein design", "date": "", "ddg_snippet": "... model architecture by adding a concept bottleneck layer to explicitly incorporate human-understandable concepts into the language model —termed a ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2411.06090v2", "content": "... model architecture by adding a concept bottleneck layer to explicitly incorporate human-understandable concepts into the language model —termed a ..."}
+{"idx": 3, "title": "Neural Concept Verifier: Scaling Prover-Verifier Games via", "date": "", "ddg_snippet": "... concept annotations, subsequent research has relaxed this requirement by leveraging pretrained vision-language models like CLIP for concept extraction ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.07532v1", "content": "... concept annotations, subsequent research has relaxed this requirement by leveraging pretrained vision-language models like CLIP for concept extraction ..."}
+{"idx": 4, "title": "ML Models: Understanding the Fundamentals", "date": "", "ddg_snippet": "Here, you are not providing predefined classes for the model to sort data by, so the model will group the unlabeled data inputs into various clusters ...", "subpage_snippet": "", "source": "gretel.ai", "link": "https://gretel.ai/blog/machine-learning-models", "content": "Here, you are not providing predefined classes for the model to sort data by, so the model will group the unlabeled data inputs into various clusters ..."}
+{"idx": 5, "title": "12 Large Language Model Foundations – Machine Learning", "date": "", "ddg_snippet": "... questions about whether these models exhibit genuine intelligence, examining evidence beyond simple retrieval, the role of information bottlenecks in ...", "subpage_snippet": "", "source": "mlbook.jyotirmoy.net", "link": "https://mlbook.jyotirmoy.net/book_content/065-large-model-foundations.html", "content": "... questions about whether these models exhibit genuine intelligence, examining evidence beyond simple retrieval, the role of information bottlenecks in ..."}
+{"idx": 6, "title": "Hanchen Wang's research works | Stanford University and", "date": "", "ddg_snippet": "... foundation , Biomni features a generalist agentic architecture that integrates large language model (LLM) reasoning with retrieval-augmented planning ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/scientific-contributions/Hanchen-Wang-2181172215", "content": "... foundation , Biomni features a generalist agentic architecture that integrates large language model (LLM) reasoning with retrieval-augmented planning ..."}
+{"idx": 7, "title": "BlueGlass: A Framework for Composite AI Safety", "date": "", "ddg_snippet": "This component wraps a target model , providing a standardized mechanism to define access points within the model ’s architecture where features can ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2507.10106v1", "content": "This component wraps a target model , providing a standardized mechanism to define access points within the model ’s architecture where features can ..."}
+{"idx": 8, "title": "All | MongoDB Blog", "date": "", "ddg_snippet": "With MongoDB Atlas , companies are leveraging vector search, seamless document modeling , and large language model (LLM) integrations to make smarter ...", "subpage_snippet": "", "source": "www.mongodb.com", "link": "https://www.mongodb.com/company/blog/all/632", "content": "With MongoDB Atlas , companies are leveraging vector search, seamless document modeling , and large language model (LLM) integrations to make smarter ..."}
+{"idx": 9, "title": "All | MongoDB Blog", "date": "", "ddg_snippet": "With MongoDB Atlas , companies are leveraging vector search, seamless document modeling , and large language model (LLM) integrations to make smarter ...", "subpage_snippet": "", "source": "www.mongodb.com", "link": "https://www.mongodb.com/company/blog/all/722", "content": "With MongoDB Atlas , companies are leveraging vector search, seamless document modeling , and large language model (LLM) integrations to make smarter ..."}

data/sampled_jsons/Creating_noise_from_data_is_easy;_creating_data_from_noise_is_generative_modeling_Song_2021_abstract_year_2021.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Score-Based Generative Modeling through Stochastic ...", "date": "", "ddg_snippet": "by Y Song · 2020 · Cited by 8724 — Abstract : Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2011.13456", "content": "by Y Song · 2020 · Cited by 8724 — Abstract : Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation ..."}
+{"idx": 1, "title": "SCORE-BASED GENERATIVE MODELING THROUGH ...", "date": "", "ddg_snippet": "by Y Song · Cited by 8724 — ABSTRACT . Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that ...", "subpage_snippet": "", "source": "openreview.net", "link": "https://openreview.net/pdf/ef0eadbe07115b0853e964f17aa09d811cd490f1.pdf?ref=news-tutorials-ai-research", "content": "by Y Song · Cited by 8724 — ABSTRACT . Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that ..."}
+{"idx": 2, "title": "Yang Song", "date": "", "ddg_snippet": "Abstract PDF Blog Code Poster Media. Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential ...", "subpage_snippet": "", "source": "yang-song.net", "link": "https://yang-song.net/", "content": "Abstract PDF Blog Code Poster Media. Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential ..."}
+{"idx": 3, "title": "Score-based generative models: Score matching", "date": "", "ddg_snippet": "... abstract of ( Song et al., 2020):. \" Creating noise from data is easy; creating data from noise is generative modeling .\" I must say that it is hard to come up ...", "subpage_snippet": "", "source": "jmtomczak.github.io", "link": "https://jmtomczak.github.io/blog/16/16_score_matching.html", "content": "... abstract of ( Song et al., 2020):. \" Creating noise from data is easy; creating data from noise is generative modeling .\" I must say that it is hard to come up ..."}
+{"idx": 4, "title": "Score-Based Generative Modeling with SDEs", "date": "", "ddg_snippet": "Abstract : Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that ...", "subpage_snippet": "", "source": "www.emergentmind.com", "link": "https://www.emergentmind.com/papers/2011.13456", "content": "Abstract : Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that ..."}
+{"idx": 5, "title": "AIM-Harvard/ICLR-Accepted-Papers · Datasets at ...", "date": "", "ddg_snippet": "Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that smoothly ...", "subpage_snippet": "", "source": "huggingface.co", "link": "https://huggingface.co/datasets/AIM-Harvard/ICLR-Accepted-Papers", "content": "Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that smoothly ..."}
+{"idx": 6, "title": "ICLR 2021 Orals", "date": "", "ddg_snippet": "Abstract . Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that ...", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2021/events/oral", "content": "Abstract . Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that ..."}
+{"idx": 7, "title": "Track: Outstanding Paper Session 1", "date": "", "ddg_snippet": "5 May 2021 — Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that ...", "subpage_snippet": "", "source": "iclr.cc", "link": "https://iclr.cc/virtual/2021/session/4366", "content": "5 May 2021 — Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that ..."}
+{"idx": 8, "title": "publications", "date": "", "ddg_snippet": "Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that smoothly transforms ...", "subpage_snippet": "", "source": "yang-song.net", "link": "https://yang-song.net/publications/", "content": "Creating noise from data is easy; creating data from noise is generative modeling . We present a stochastic differential equation (SDE) that smoothly transforms ..."}
+{"idx": 9, "title": "Ben Poole", "date": "", "ddg_snippet": "ICLR 2021 ( 2021 ) (to appear). Preview Preview abstract Creating noise from data is easy; creating data from noise is generative modeling . We present a ...", "subpage_snippet": "", "source": "research.google", "link": "https://research.google/people/benpoole/", "content": "ICLR 2021 ( 2021 ) (to appear). Preview Preview abstract Creating noise from data is easy; creating data from noise is generative modeling . We present a ..."}

data/sampled_jsons/Cronbach_Meehl_1955_Construct_validity_in_psychological_tests_abstract.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "Kentucky Derby - Wikipedia", "date": "", "ddg_snippet": "Kentucky Derby ... The Kentucky Derby (/ ˈdɜːrbi /) is an American Grade I stakes race run at Churchill Downs in Louisville, Kentucky . The race is run by three-year-old Thoroughbreds at a distance of 11⁄4 miles (10 furlongs; 2,012 metres). Colts and geldings carry 126 pounds (57 kilograms) and fillies 121 pounds (55 kilograms). [3]", "subpage_snippet": "", "source": "en.wikipedia.org", "link": "https://en.wikipedia.org/wiki/Kentucky_Derby", "content": "Kentucky Derby ... The Kentucky Derby (/ ˈdɜːrbi /) is an American Grade I stakes race run at Churchill Downs in Louisville, Kentucky . The race is run by three-year-old Thoroughbreds at a distance of 11⁄4 miles (10 furlongs; 2,012 metres). Colts and geldings carry 126 pounds (57 kilograms) and fillies 121 pounds (55 kilograms). [3]"}
+{"idx": 1, "title": "Classics in the History of Psychology -- Cronbach & Meehl ( 1955 )", "date": "", "ddg_snippet": "Construct validity in psychological tests . Lee J. Cronbach and Paul E. Meehl ( 1955 )[1]. First published in Psychological Bulletin, 52, 281-302. Validation of psychological tests has not yet been adequately conceptualized, as the APA Committee on Psychological ...", "subpage_snippet": "", "source": "psychclassics.yorku.ca", "link": "https://psychclassics.yorku.ca/Cronbach/construct.htm", "content": "Construct validity in psychological tests . Lee J. Cronbach and Paul E. Meehl ( 1955 )[1]. First published in Psychological Bulletin, 52, 281-302. Validation of psychological tests has not yet been adequately conceptualized, as the APA Committee on Psychological ..."}
+{"idx": 2, "title": "Construct validity in psychological tests", "date": "", "ddg_snippet": "L J Cronbach , p e Meehl .No abstract available. MeSH terms. Humans. Psychological Tests *.", "subpage_snippet": "", "source": "pubmed.ncbi.nlm.nih.gov", "link": "https://pubmed.ncbi.nlm.nih.gov/13245896/", "content": "L J Cronbach , p e Meehl .No abstract available. MeSH terms. Humans. Psychological Tests *."}
+{"idx": 3, "title": "Psychological", "date": "", "ddg_snippet": "JULY, 1955 . Psychological Bulletin. Construct validity in psychological tests . LEE J. CRONBACH University of Illinois. AND. PAUL E. MEEHLi University of Minnesota.", "subpage_snippet": "", "source": "www.sfu.ca", "link": "https://www.sfu.ca/~palys/Cronbach&Meehl-1955-ConstructValidityInPsychologicalTests.pdf", "content": "JULY, 1955 . Psychological Bulletin. Construct validity in psychological tests . LEE J. CRONBACH University of Illinois. AND. PAUL E. MEEHLi University of Minnesota."}
+{"idx": 4, "title": "Introduction to the special section on construct validity of...", "date": "", "ddg_snippet": "of construct validity ( Cronbach & Meehl , 1955 ), and described a. methodology for estimating convergent and discriminant validity . Construct validity is one of the most central concepts in psychology .", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/7378545_Introduction_to_the_special_section_on_construct_validity_of_psychological_tests_50_Years_after_Cronbach_and_Meehl_1955", "content": "of construct validity ( Cronbach & Meehl , 1955 ), and described a. methodology for estimating convergent and discriminant validity . Construct validity is one of the most central concepts in psychology ."}
+{"idx": 5, "title": "Cronbach , L. J., & Meehl , P. E. ( 1955 ). Construct validity in ...", "date": "", "ddg_snippet": "Construct validity in psychological tests . Psychological bulletin, 52(4), 281.Correspondence to: Heidemae R. Tabor, University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines. Email: heidemae.tabor@ustp.edu.ph. Abstract .", "subpage_snippet": "", "source": "www.sciepub.com", "link": "https://www.sciepub.com/reference/449543", "content": "Construct validity in psychological tests . Psychological bulletin, 52(4), 281.Correspondence to: Heidemae R. Tabor, University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines. Email: heidemae.tabor@ustp.edu.ph. Abstract ."}
+{"idx": 6, "title": "Evaluating Construct Validity within Preclinical In Vivo Animal Research", "date": "", "ddg_snippet": "Construct validity was first introduced in research by Meehl and Cronbach in 1955 ( Cronbach & Meehl , 1955 ). They defined construct validity in terms of psychological test evaluation.", "subpage_snippet": "", "source": "ruor.uottawa.ca", "link": "https://ruor.uottawa.ca/server/api/core/bitstreams/b0bda751-ed46-4e37-abf1-9a17ba5910a4/content", "content": "Construct validity was first introduced in research by Meehl and Cronbach in 1955 ( Cronbach & Meehl , 1955 ). They defined construct validity in terms of psychological test evaluation."}
+{"idx": 7, "title": "CronbachPaper", "date": "", "ddg_snippet": "My current thoughts on coefficient alpha and successor procedures. Educational and Psychological Measurement, 64, 391–418. Cronbach , L. J., & Meehl , P. E. ( 1955 ). Construct validity in psychological tests .", "subpage_snippet": "", "source": "cda.psych.uiuc.edu", "link": "http://cda.psych.uiuc.edu/psychometrika_johnson/CronbachPaper+(1).pdf", "content": "My current thoughts on coefficient alpha and successor procedures. Educational and Psychological Measurement, 64, 391–418. Cronbach , L. J., & Meehl , P. E. ( 1955 ). Construct validity in psychological tests ."}
+{"idx": 8, "title": "Measuring Personality Constructs : The Advantages and...", "date": "", "ddg_snippet": "According to Cronbach and Meehl ( 1955 ), psychological and personality constructs are “postulated” or inferred characteristics or traits of a person. Construct validity in psychological tests . Psychological Bulletin, 52, 281-301.", "subpage_snippet": "", "source": "www.nottingham.ac.uk", "link": "https://www.nottingham.ac.uk/sociology/documents/enquire/volume-1-issue-1-dodorico-mcdonald.pdf", "content": "According to Cronbach and Meehl ( 1955 ), psychological and personality constructs are “postulated” or inferred characteristics or traits of a person. Construct validity in psychological tests . Psychological Bulletin, 52, 281-301."}
+{"idx": 9, "title": "On Validity", "date": "", "ddg_snippet": "Cronbach and Meehl ( 1955 ) maintained that the construct needed to be part of a nomological network: “the interlocking system of laws which constitute a theory” (p. 290).University of Illinois Press. Cronbach , L. J., & Meehl , P. E. ( 1955 ). Construct validity in psychological tests .", "subpage_snippet": "", "source": "journals.library.columbia.edu", "link": "https://journals.library.columbia.edu/index.php/SALT/article/download/11804/5991/30419", "content": "Cronbach and Meehl ( 1955 ) maintained that the construct needed to be part of a nomological network: “the interlocking system of laws which constitute a theory” (p. 290).University of Illinois Press. Cronbach , L. J., & Meehl , P. E. ( 1955 ). Construct validity in psychological tests ."}

data/sampled_jsons/CrossKD_classification_CIFAR100_Wang_et_al.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which delivers the intermediate features of the student's ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2306.11369", "content": "Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which delivers the intermediate features of the student's ..."}
+{"idx": 1, "title": "CIFAR-100-Image-Classification - GitHub", "date": "", "ddg_snippet": "This project explores diverse approaches to image classification on the CIFAR-100 dataset. Starting from traditional CNNs combined with KNN classifiers, it progresses to ResNet50 with FCNN and culm...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/ishreya09/CIFAR-100-Image-Classification", "content": "This project explores diverse approaches to image classification on the CIFAR-100 dataset. Starting from traditional CNNs combined with KNN classifiers, it progresses to ResNet50 with FCNN and culm..."}
+{"idx": 2, "title": "Classification accuracy on CIFAR100 benchmark. - ResearchGate", "date": "", "ddg_snippet": "Download scientific diagram | Classification accuracy on CIFAR100 benchmark. from publication: Look One and More: Distilling Hybrid Order Relational Knowledge for Cross-Resolution Image ...", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/figure/Classification-accuracy-on-CIFAR100-benchmark_tbl1_383910666", "content": "Download scientific diagram | Classification accuracy on CIFAR100 benchmark. from publication: Look One and More: Distilling Hybrid Order Relational Knowledge for Cross-Resolution Image ..."}
+{"idx": 3, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Abstract Knowledge Distillation (KD) has been validated as an effective model compression technique for learning com-pact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which de-livers the intermediate features of the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2306.11369", "content": "Abstract Knowledge Distillation (KD) has been validated as an effective model compression technique for learning com-pact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which de-livers the intermediate features of the ..."}
+{"idx": 4, "title": "PDF CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Recently, Zheng et al . [73] proposed a localization distillation (LD) method that improves prediction mimicking by transferring localization knowledge, which pushes the prediction mim-icking to a new level.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2024/papers/Wang_CrossKD_Cross-Head_Knowledge_Distillation_for_Object_Detection_CVPR_2024_paper.pdf", "content": "Recently, Zheng et al . [73] proposed a localization distillation (LD) method that improves prediction mimicking by transferring localization knowledge, which pushes the prediction mim-icking to a new level."}
+{"idx": 5, "title": "Distilling and transferring knowledge via cGAN-generated samples for ...", "date": "", "ddg_snippet": "Knowledge distillation (KD) has been actively studied for image classification tasks in deep learning, aiming to improve the performance of a student …", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/abs/pii/S0957417422020784", "content": "Knowledge distillation (KD) has been actively studied for image classification tasks in deep learning, aiming to improve the performance of a student …"}
+{"idx": 6, "title": "CVPR 2024 Open Access Repository", "date": "", "ddg_snippet": "CrossKD : Cross-Head Knowledge Distillation for Object Detection Jiabao Wang , Yuming Chen, Zhaohui Zheng, Xiang Li, Ming-Ming Cheng, Qibin Hou; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 16520-16530 Abstract", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2024/html/Wang_CrossKD_Cross-Head_Knowledge_Distillation_for_Object_Detection_CVPR_2024_paper.html", "content": "CrossKD : Cross-Head Knowledge Distillation for Object Detection Jiabao Wang , Yuming Chen, Zhaohui Zheng, Xiang Li, Ming-Ming Cheng, Qibin Hou; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 16520-16530 Abstract"}
+{"idx": 7, "title": "Multistage feature fusion knowledge distillation", "date": "", "ddg_snippet": "The CIFAR-100 classification dataset 35 consists of 100 categories with images of size 32 \\ (\\times\\) 32. The dataset includes 50,000 training images and 10,000 validation images.", "subpage_snippet": "", "source": "www.nature.com", "link": "https://www.nature.com/articles/s41598-024-64041-4", "content": "The CIFAR-100 classification dataset 35 consists of 100 categories with images of size 32 \\ (\\times\\) 32. The dataset includes 50,000 training images and 10,000 validation images."}
+{"idx": 8, "title": "Enhancing Adversarial Robustness of Deep Neural Networks Through ...", "date": "", "ddg_snippet": "The experiments are conducted on the CIFAR-100 dataset, a widely used benchmark for image classification tasks, consisting of 60,000 images across 100 classes, with 50,000 training samples and 10,000 test samples.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2412.19747v1", "content": "The experiments are conducted on the CIFAR-100 dataset, a widely used benchmark for image classification tasks, consisting of 60,000 images across 100 classes, with 50,000 training samples and 10,000 test samples."}
+{"idx": 9, "title": "CIFAR-100 on Benchmarks.AI", "date": "", "ddg_snippet": "Explore CIFAR-100 dataset benchmarks, pre-trained models and fine-tuning techniques to improve deep learning performance on vision tasks.", "subpage_snippet": "", "source": "benchmarks.ai", "link": "https://benchmarks.ai/cifar-100", "content": "Explore CIFAR-100 dataset benchmarks, pre-trained models and fine-tuning techniques to improve deep learning performance on vision tasks."}

data/sampled_jsons/Crosskd_Cross-head_knowledge_distillation_for_object_detection_Wang_2024_CIFAR100_classification.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which delivers the intermediate features of the student's ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2306.11369", "content": "Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which delivers the intermediate features of the student's ..."}
+{"idx": 1, "title": "PDF CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which de-livers the intermediate features of the student's detection head to the teacher's detection head . The resulting cross - head predictions are then forced to mimic the teacher's pre-dictions.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2024/papers/Wang_CrossKD_Cross-Head_Knowledge_Distillation_for_Object_Detection_CVPR_2024_paper.pdf", "content": "In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which de-livers the intermediate features of the student's detection head to the teacher's detection head . The resulting cross - head predictions are then forced to mimic the teacher's pre-dictions."}
+{"idx": 2, "title": "Awesome Knowledge Distillation for Object Detection - GitHub", "date": "", "ddg_snippet": "A curated list of awesome distillation techniques designed for object detectors. Parameters compression and accuracy boosting are core problems for object detection towards practical application, where knowledge distillation (KD) is one of the most popular solutions. KD aims at training the compact model (student) by transferring knowledge from a high-capacity model (teacher). Papers and codes ...", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/LutingWang/awesome-knowledge-distillation-for-object-detection", "content": "A curated list of awesome distillation techniques designed for object detectors. Parameters compression and accuracy boosting are core problems for object detection towards practical application, where knowledge distillation (KD) is one of the most popular solutions. KD aims at training the compact model (student) by transferring knowledge from a high-capacity model (teacher). Papers and codes ..."}
+{"idx": 3, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Abstract:Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which delivers the intermediate features of the ...", "subpage_snippet": "", "source": "bohrium.dp.tech", "link": "https://bohrium.dp.tech/paper/arxiv/2306.11369", "content": "Abstract:Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which delivers the intermediate features of the ..."}
+{"idx": 4, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Wang , Jiabao, et al. \" CrossKD : Cross - head knowledge distillation for object detection .\" Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024 .", "subpage_snippet": "", "source": "velog.io", "link": "https://velog.io/@hseop/CrossKD-Cross-Head-Knowledge-Distillation-for-Object-Detection", "content": "Wang , Jiabao, et al. \" CrossKD : Cross - head knowledge distillation for object detection .\" Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024 ."}
+{"idx": 5, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Abstract Knowledge Distillation (KD) has been validated as an effective model compression technique for learning com-pact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which de-livers the intermediate features of the ...", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2306.11369", "content": "Abstract Knowledge Distillation (KD) has been validated as an effective model compression technique for learning com-pact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which de-livers the intermediate features of the ..."}
+{"idx": 6, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "In this paper we present a general and effective prediction mimicking distillation scheme called CrossKD which delivers the intermediate features of the student's detection head to the teacher's detection head . The resulting cross - head predictions are then forced to mimic the teacher's predictions.", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2024/html/Wang_CrossKD_Cross-Head_Knowledge_Distillation_for_Object_Detection_CVPR_2024_paper.html", "content": "In this paper we present a general and effective prediction mimicking distillation scheme called CrossKD which delivers the intermediate features of the student's detection head to the teacher's detection head . The resulting cross - head predictions are then forced to mimic the teacher's predictions."}
+{"idx": 7, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper we present a general and effective prediction mimicking distillation scheme called CrossKD which delivers the intermediate features of the student's ...", "subpage_snippet": "", "source": "www.deepnlp.org", "link": "https://www.deepnlp.org/content/articles/crosskd:-cross-head-knowledge-distillation-for-object-detection", "content": "Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper we present a general and effective prediction mimicking distillation scheme called CrossKD which delivers the intermediate features of the student's ..."}
+{"idx": 8, "title": "CrossKD/README.md at master · jbwang1997/CrossKD · GitHub", "date": "", "ddg_snippet": "CrossKD : Cross - Head Knowledge Distillation for Dense Object Detection - CrossKD /README.md at master · jbwang1997/ CrossKD", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/jbwang1997/CrossKD/blob/master/README.md", "content": "CrossKD : Cross - Head Knowledge Distillation for Dense Object Detection - CrossKD /README.md at master · jbwang1997/ CrossKD"}
+{"idx": 9, "title": "CrossKD: Cross-Head Knowledge Distillation for Object Detection", "date": "", "ddg_snippet": "Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which delivers the intermediate features of the student's ...", "subpage_snippet": "", "source": "bytez.com", "link": "https://bytez.com/docs/cvpr/31390/paper", "content": "Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper, we present a general and effective prediction mimicking distillation scheme, called CrossKD , which delivers the intermediate features of the student's ..."}

data/sampled_jsons/DART_radiology_report_generation_Figure_2_focal_consolidation_github_discussion_year_2024.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "mk-runner/Awesome-Radiology-Report-Generation - GitHub", "date": "", "ddg_snippet": "We collect existing papers on radiology report generation that have been published in prominent conferences and journals. If you find this helpful, please consider citing the following reference.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/mk-runner/Awesome-Radiology-Report-Generation", "content": "We collect existing papers on radiology report generation that have been published in prominent conferences and journals. If you find this helpful, please consider citing the following reference."}
+{"idx": 1, "title": "DART: Disease-aware Image-Text Alignment and Self-correcting Re ...", "date": "", "ddg_snippet": "In this study, we propose a Disease-aware image-text Alignment and self-correcting Re-alignment for Trustworthy radiology report generation ( DART ), a novel framework that ensures retrieved reports contain similar disease-relevant findings and introduces a self-correction mechanism to refine generated reports .", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/html/2504.11786v1", "content": "In this study, we propose a Disease-aware image-text Alignment and self-correcting Re-alignment for Trustworthy radiology report generation ( DART ), a novel framework that ensures retrieved reports contain similar disease-relevant findings and introduces a self-correction mechanism to refine generated reports ."}
+{"idx": 2, "title": "Radiology report generation with a learned knowledge base and multi ...", "date": "", "ddg_snippet": "It also indicates that the radiology report generation benefits from the multi-modal alignment mechanism and the learned knowledge base, avoiding laborious manual construction of the knowledge graph or template database. Furthermore, the proposed methods boost the quality of generated reports in both natural language and clinical correctness.", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S1361841523000592", "content": "It also indicates that the radiology report generation benefits from the multi-modal alignment mechanism and the learned knowledge base, avoiding laborious manual construction of the knowledge graph or template database. Furthermore, the proposed methods boost the quality of generated reports in both natural language and clinical correctness."}
+{"idx": 3, "title": "Awesome Radiology Report Generation - GitHub", "date": "", "ddg_snippet": "A curated list of radiology report generation (medical report generation ) and related areas. :-) - zhjohnchan/awesome- radiology - report - generation", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/zhjohnchan/awesome-radiology-report-generation", "content": "A curated list of radiology report generation (medical report generation ) and related areas. :-) - zhjohnchan/awesome- radiology - report - generation"}
+{"idx": 4, "title": "DART | PDF | Artificial Intelligence | Intelligence (AI) & Semantics", "date": "", "ddg_snippet": "The document presents the DART framework, which focuses on automatic radiology report generation by ensuring disease-aware image-text alignment and incorporating a self-correction mechanism. This two-stage approach first generates initial reports through image-to-text retrieval with a disease-matching constraint and then refines these reports by re-aligning them with input X-ray images. The ...", "subpage_snippet": "", "source": "www.scribd.com", "link": "https://www.scribd.com/document/876841025/DART", "content": "The document presents the DART framework, which focuses on automatic radiology report generation by ensuring disease-aware image-text alignment and incorporating a self-correction mechanism. This two-stage approach first generates initial reports through image-to-text retrieval with a disease-matching constraint and then refines these reports by re-aligning them with input X-ray images. The ..."}
+{"idx": 5, "title": "Medical radiology report generation: A systematic review of current ...", "date": "", "ddg_snippet": "Medical radiology reports play a crucial role in diagnosing various diseases, yet generating them manually is time-consuming and burdens clinical workflows. Medical radiology report generation aims to automate this process using deep learning to assist radiologists and reduce patient wait times. This study presents the most comprehensive systematic review to date on deep learning-based MRRG ...", "subpage_snippet": "", "source": "www.sciencedirect.com", "link": "https://www.sciencedirect.com/science/article/pii/S0933365725001551", "content": "Medical radiology reports play a crucial role in diagnosing various diseases, yet generating them manually is time-consuming and burdens clinical workflows. Medical radiology report generation aims to automate this process using deep learning to assist radiologists and reduce patient wait times. This study presents the most comprehensive systematic review to date on deep learning-based MRRG ..."}
+{"idx": 6, "title": "PDF Progressive Transformer-Based Generation of Radiology Reports", "date": "", "ddg_snippet": "As shown in Figure 1, we divide the prob-lem of radiology report generation into two steps. In the first step, the model generates global con-cepts from the image and then reforms them into finer and coherent text using a transformer archi-tecture.", "subpage_snippet": "", "source": "aclanthology.org", "link": "https://aclanthology.org/2021.findings-emnlp.241.pdf", "content": "As shown in Figure 1, we divide the prob-lem of radiology report generation into two steps. In the first step, the model generates global con-cepts from the image and then reforms them into finer and coherent text using a transformer archi-tecture."}
+{"idx": 7, "title": "PDF DART: Disease-aware Image-Text Alignment and Self-correcting Re ...", "date": "", "ddg_snippet": "In this study, we propose a Disease-aware image-text Alignment and self-correcting Re-alignment for Trustworthy radiology report generation ( DART ) framework. In the first stage, we generate ini-tial reports based on image-to-text retrieval with disease-matching, embedding both images and texts in a shared em-bedding space through contrastive ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/papers/Park_DART_Disease-aware_Image-Text_Alignment_and_Self-correcting_Re-alignment_for_Trustworthy_Radiology_CVPR_2025_paper.pdf", "content": "In this study, we propose a Disease-aware image-text Alignment and self-correcting Re-alignment for Trustworthy radiology report generation ( DART ) framework. In the first stage, we generate ini-tial reports based on image-to-text retrieval with disease-matching, embedding both images and texts in a shared em-bedding space through contrastive ..."}
+{"idx": 8, "title": "GitHub - banbooliang/REVTAF-RRG", "date": "", "ddg_snippet": "Learnable Retrieval Enhanced Visual-Text Alignment and Fusion for Radiology Report Generation If you find this project useful, please give us a star🌟. Framework Automated radiology report generation is essential for improving diagnostic efficiency and reducing the workload of medical professionals.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/banbooliang/REVTAF-RRG", "content": "Learnable Retrieval Enhanced Visual-Text Alignment and Fusion for Radiology Report Generation If you find this project useful, please give us a star🌟. Framework Automated radiology report generation is essential for improving diagnostic efficiency and reducing the workload of medical professionals."}
+{"idx": 9, "title": "CVPR 2025 Open Access Repository", "date": "", "ddg_snippet": "In this study, we propose a Disease-aware image-text Alignment and self-correcting Re-alignment for Trustworthy radiology report generation ( DART ) framework. In the first stage, we generate initial reports based on image-to-text retrieval with disease-matching, embedding both images and texts in a shared embedding space through contrastive ...", "subpage_snippet": "", "source": "openaccess.thecvf.com", "link": "https://openaccess.thecvf.com/content/CVPR2025/html/Park_DART_Disease-aware_Image-Text_Alignment_and_Self-correcting_Re-alignment_for_Trustworthy_Radiology_CVPR_2025_paper.html", "content": "In this study, we propose a Disease-aware image-text Alignment and self-correcting Re-alignment for Trustworthy radiology report generation ( DART ) framework. In the first stage, we generate initial reports based on image-to-text retrieval with disease-matching, embedding both images and texts in a shared embedding space through contrastive ..."}

data/sampled_jsons/DCBM_area_filter_minimum_area_maximum_area_segmentation_year_2024.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "An open-source pipeline for the analysis of filopodia - PMC", "date": "", "ddg_snippet": "by V Urbančič · 2017 · Cited by 61 — Robust filopodia segmentation, tracking, and measurement across cell types. We developed Filopodyan for the growth cones in Xenopus laevis RGC ...", "subpage_snippet": "", "source": "pmc.ncbi.nlm.nih.gov", "link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC5626553/", "content": "by V Urbančič · 2017 · Cited by 61 — Robust filopodia segmentation, tracking, and measurement across cell types. We developed Filopodyan for the growth cones in Xenopus laevis RGC ..."}
+{"idx": 1, "title": "Filopodyan: an open-source pipeline for the analysis of filopodia", "date": "", "ddg_snippet": "channel and the following segmentation and filtering parameters: Thresholding: 35. Renyi entropy, σ LoG = 2.6, ED = 4, number of base back frames = 20 (other.", "subpage_snippet": "", "source": "www.biorxiv.org", "link": "https://www.biorxiv.org/content/10.1101/138610v2.full.pdf", "content": "channel and the following segmentation and filtering parameters: Thresholding: 35. Renyi entropy, σ LoG = 2.6, ED = 4, number of base back frames = 20 (other."}
+{"idx": 2, "title": "Econometrics and Statistics (EcoSta 2025)", "date": "", "ddg_snippet": "21 Aug 2025 — The Computational and Financial Econometrics (CFEnetwork) comprises a number of specialized teams in various research areas of theoretical and ...", "subpage_snippet": "", "source": "www.cmstatistics.org", "link": "https://www.cmstatistics.org/EcoSta2025/docs/BoA.pdf?20250728012733", "content": "21 Aug 2025 — The Computational and Financial Econometrics (CFEnetwork) comprises a number of specialized teams in various research areas of theoretical and ..."}
+{"idx": 3, "title": "Downloads 2025", "date": "", "ddg_snippet": "Learning Minimum-Size BDDs: Towards Efficient Exact Algorithms · Learning Mixtures of Experts with EM: A Mirror Descent Perspective · Learning Monotonic ...", "subpage_snippet": "", "source": "icml.cc", "link": "https://icml.cc/Downloads/2025", "content": "Learning Minimum-Size BDDs: Towards Efficient Exact Algorithms · Learning Mixtures of Experts with EM: A Mirror Descent Perspective · Learning Monotonic ..."}
+{"idx": 4, "title": "", "date": "", "ddg_snippet": "", "subpage_snippet": "", "source": "", "link": "", "content": ""}
+{"idx": 5, "title": "Filopodyan: An open-source pipeline for the analysis of", "date": "", "ddg_snippet": "Urbančič et al. developed an open-source platform called Filopodyan (filopodia dynamics analysis) in Fiji and R to measure fluorescence in ...", "subpage_snippet": "", "source": "rupress.org", "link": "https://rupress.org/jcb/article/216/10/3405/38925/Filopodyan-An-open-source-pipeline-for-the", "content": "Urbančič et al. developed an open-source platform called Filopodyan (filopodia dynamics analysis) in Fiji and R to measure fluorescence in ..."}
+{"idx": 6, "title": "Machine Learning in Sensors and Imaging", "date": "", "ddg_snippet": "2022 by the authors. Articles in this book are Open Access and distributed under the Creative. Commons Attribution (CC BY) license, which allows users to ...", "subpage_snippet": "", "source": "unglueit-files.s3.amazonaws.com", "link": "https://unglueit-files.s3.amazonaws.com/ebf/af61d61cc2f4412983b7366de44a7cc5.pdf", "content": "2022 by the authors. Articles in this book are Open Access and distributed under the Creative. Commons Attribution (CC BY) license, which allows users to ..."}
+{"idx": 7, "title": "an open-source pipeline for the analysis of filopodia", "date": "", "ddg_snippet": "17 May 2017 — It is possible to segment filopodia at bigger pixel dimensions and consequently a smaller number of pixels per filopodium width, but the ...", "subpage_snippet": "", "source": "www.biorxiv.org", "link": "https://www.biorxiv.org/content/10.1101/138610v1.full-text", "content": "17 May 2017 — It is possible to segment filopodia at bigger pixel dimensions and consequently a smaller number of pixels per filopodium width, but the ..."}
+{"idx": 8, "title": "Hydrophobin Bilayer as Water Impermeable Protein Membrane", "date": "", "ddg_snippet": "by F Nolle · 2023 · Cited by 1 — This study reports on the very low water permeability of pure protein membranes composed of a bilayer of the amphiphilic protein hydrophobin HFBI.", "subpage_snippet": "", "source": "pubs.acs.org", "link": "https://pubs.acs.org/doi/10.1021/acs.langmuir.3c01006", "content": "by F Nolle · 2023 · Cited by 1 — This study reports on the very low water permeability of pure protein membranes composed of a bilayer of the amphiphilic protein hydrophobin HFBI."}
+{"idx": 9, "title": "Linear Regression and Its Inference on Noisy Network-Linked ...", "date": "", "ddg_snippet": "by CM Le · 2022 · Cited by 40 — This paper proposes a regression model with non-parametric network effects. The model does not assume that the relational data or network structure is exactly ...", "subpage_snippet": "", "source": "academic.oup.com", "link": "https://academic.oup.com/jrsssb/article/84/5/1851/7072882", "content": "by CM Le · 2022 · Cited by 40 — This paper proposes a regression model with non-parametric network effects. The model does not assume that the relational data or network structure is exactly ..."}

data/sampled_jsons/DSDFM_Algorithm_1_line_8_D_Drift_DerODE_DivSDE_human_motion_synthesis_year_2024.jsonl

@@ -0,0 +1,10 @@
+{"idx": 0, "title": "[2505.00998] Deterministic-to-Stochastic Diverse Latent ... Deterministic-to-Stochastic Diverse Latent Feature Mapping ... 论文阅读--DSDFM--用于人体运动合成的确定性到随机多种潜在特征映射 -... arXiv:2505.00998v1 [cs.CV] 2 May 2025 CVPR 2025 Open Access Repository Appendix - CVF Open Access MDM: Human Motion Diffusion Model - GitHub", "date": "", "ddg_snippet": "May 2, 2025 · 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 . To synthesize diverse and accurate human motions , we propose a novel method called DSDFM for human motion synthesis . The proposed method has straight trajectories and is easy to train compared to previous SGMs methods, while guaranteeing the diversity and accuracy of the generated hu-man motions. May 29, 2025 · 首先，提出了Diverse Latent Feature Mapping ( DS D FM )方法，可以在采样过程有效训练和利用；，可以用于有条件和无条件的生成。 提出了一个最优解，剪力高斯分布和 人体 运动 潜在空间的关系，同时在采样过程提供随机多样化的输出生成过程。 thesis. DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the laten space distribution of human motions . The second diverse mo-tion generation stage aims to build connections between the Gaussian distribution and the latent space distribution of hu-man motions , thereby enhancing the diversity and ac The second diverse motion generation stage aims to build connections between the Gaussian distribution and the latent space distribution of human motions , thereby enhancing the diversity and accuracy of the generated human motions . 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. (1) We released the 50 diffusion steps model (instead of 1000 steps) which runs 20X faster with comparable results. (2) Calling CLIP just once and caching the result runs 2X faster for all models.", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/abs/2505.00998", "content": "May 2, 2025 · 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 . To synthesize diverse and accurate human motions , we propose a novel method called DSDFM for human motion synthesis . The proposed method has straight trajectories and is easy to train compared to previous SGMs methods, while guaranteeing the diversity and accuracy of the generated hu-man motions. May 29, 2025 · 首先，提出了Diverse Latent Feature Mapping ( DS D FM )方法，可以在采样过程有效训练和利用；，可以用于有条件和无条件的生成。 提出了一个最优解，剪力高斯分布和 人体 运动 潜在空间的关系，同时在采样过程提供随机多样化的输出生成过程。 thesis. DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the laten space distribution of human motions . The second diverse mo-tion generation stage aims to build connections between the Gaussian distribution and the latent space distribution of hu-man motions , thereby enhancing the diversity and ac The second diverse motion generation stage aims to build connections between the Gaussian distribution and the latent space distribution of human motions , thereby enhancing the diversity and accuracy of the generated human motions . 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. (1) We released the 50 diffusion steps model (instead of 1000 steps) which runs 20X faster with comparable results. (2) Calling CLIP just once and caching the result runs 2X faster for all models."}
+{"idx": 1, "title": "DivDiff: A Conditional Diffusion Model for Diverse Human Motion ...", "date": "", "ddg_snippet": "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.", "subpage_snippet": "", "source": "www.researchgate.net", "link": "https://www.researchgate.net/publication/387413105_DivDiff_A_Conditional_Diffusion_Model_for_Diverse_Human_Motion_Prediction", "content": "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."}
+{"idx": 2, "title": "Deterministic-to-Stochastic Diverse Latent Feature Mapping for Human ...", "date": "", "ddg_snippet": "Abstract: 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.", "subpage_snippet": "", "source": "www.alphaxiv.org", "link": "https://www.alphaxiv.org/abs/2505.00998", "content": "Abstract: 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."}
+{"idx": 3, "title": "Human Fall Flat: Cheats | Console Commands", "date": "", "ddg_snippet": "This guide will tell you how to access the console and all of the known commands in Human Fall Flat.", "subpage_snippet": "", "source": "www.yekbot.com", "link": "https://www.yekbot.com/human-fall-flat-console-commands/", "content": "This guide will tell you how to access the console and all of the known commands in Human Fall Flat."}
+{"idx": 4, "title": "Free YouTube Video Downloader Online (1080p) - YT 1 D", "date": "", "ddg_snippet": "Copy the youtube link of the video and paste it into the input line .", "subpage_snippet": "", "source": "yt1d.com", "link": "https://yt1d.com/en307/", "content": "Copy the youtube link of the video and paste it into the input line ."}
+{"idx": 5, "title": "论文阅读--DSDFM--用于人体运动合成的确定性到随机多种潜在特征映射 -...", "date": "", "ddg_snippet": "May 29, 2025 · 首先，提出了Diverse Latent Feature Mapping ( DS D FM )方法，可以在采样过程有效训练和利用；，可以用于有条件和无条件的生成。 提出了一个最优解，剪力高斯分布和 人体 运动 潜在空间的关系，同时在采样过程提供随机多样化的输出生成过程。", "subpage_snippet": "", "source": "zhuanlan.zhihu.com", "link": "https://zhuanlan.zhihu.com/p/1911144623440625860", "content": "May 29, 2025 · 首先，提出了Diverse Latent Feature Mapping ( DS D FM )方法，可以在采样过程有效训练和利用；，可以用于有条件和无条件的生成。 提出了一个最优解，剪力高斯分布和 人体 运动 潜在空间的关系，同时在采样过程提供随机多样化的输出生成过程。"}
+{"idx": 6, "title": "MDM: Human Motion Diffusion Model - GitHub", "date": "", "ddg_snippet": "(1) We released the 50 diffusion steps model (instead of 1000 steps) which runs 20X faster with comparable results. (2) Calling CLIP just once and caching the result runs 2X faster for all models.", "subpage_snippet": "", "source": "github.com", "link": "https://github.com/GuyTevet/motion-diffusion-model", "content": "(1) We released the 50 diffusion steps model (instead of 1000 steps) which runs 20X faster with comparable results. (2) Calling CLIP just once and caching the result runs 2X faster for all models."}
+{"idx": 7, "title": "DDA Line Drawing Algorithm - Computer Graphics - YouTube", "date": "", "ddg_snippet": "About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How...", "subpage_snippet": "", "source": "www.youtube.com", "link": "https://www.youtube.com/watch?v=W5P8GlaEOSI", "content": "About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How..."}
+{"idx": 8, "title": "Deterministic-to-Stochastic Diverse Latent Feature Mapping ...", "date": "", "ddg_snippet": "To synthesize diverse and accurate human motions , we propose a novel method called DSDFM for human motion synthesis . The proposed method has straight trajectories and is easy to train compared to previous SGMs methods, while guaranteeing the diversity and accuracy of the generated hu-man 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": "To synthesize diverse and accurate human motions , we propose a novel method called DSDFM for human motion synthesis . The proposed method has straight trajectories and is easy to train compared to previous SGMs methods, while guaranteeing the diversity and accuracy of the generated hu-man motions."}
+{"idx": 9, "title": "arXiv:2505.00998v1 [cs.CV] 2 May 2025", "date": "", "ddg_snippet": "thesis. DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the laten space distribution of human motions . The second diverse mo-tion generation stage aims to build connections between the Gaussian distribution and the latent space distribution of hu-man motions , thereby enhancing the diversity and ac", "subpage_snippet": "", "source": "arxiv.org", "link": "https://arxiv.org/pdf/2505.00998", "content": "thesis. DSDFM consists of two stages. The first human motion reconstruction stage aims to learn the laten space distribution of human motions . The second diverse mo-tion generation stage aims to build connections between the Gaussian distribution and the latent space distribution of hu-man motions , thereby enhancing the diversity and ac"}