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2310.02898
Benjamin Heymann
Benjamin Heymann, Alejandro Jofr\'e
Some bidding games converging to their unique pure equilibrium
null
null
null
null
cs.GT math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a class of Bayesian bidding games for which we prove that the set of pure Nash equilibria is a (non-empty) sublattice and we give a sufficient condition for uniqueness that is often verified in the context of markets with inelastic demand. We propose a dynamic that converges to the extrema of the equilib...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 15:37:03 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 17:13:59 GMT" } ]
2023-10-06T00:00:00
[ [ "Heymann", "Benjamin", "" ], [ "Jofré", "Alejandro", "" ] ]
not_new_dataset
0.99728
2310.02911
Umut Can Cabuk
Massimiliano Silenzi and Umut Can Cabuk
Deciphering the Crypto-shopper: Knowledge and Preferences of Consumers Using Cryptocurrencies for Purchases
Cryptorefills Labs Whitepaper. 13 pages
null
null
null
cs.CY cs.CE cs.ET
http://creativecommons.org/licenses/by-nc-nd/4.0/
The fast-growing cryptocurrency sector presents both challenges and opportunities for businesses and consumers alike. This study investigates the knowledge, expertise, and buying habits of people who shop using cryptocurrencies. Our survey of 516 participants shows that knowledge levels vary from beginners to experts...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 15:48:28 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 06:46:02 GMT" } ]
2023-10-06T00:00:00
[ [ "Silenzi", "Massimiliano", "" ], [ "Cabuk", "Umut Can", "" ] ]
not_new_dataset
0.997273
2310.02954
Jing Xiong
Jiong Xiong, Zixuan Li, Chuanyang Zheng, Zhijiang Guo, Yichun Yin, Enze Xie, Zhicheng Yang, Qingxing Cao, Haiming Wang, Xiongwei Han, Jing Tang, Chengming Li, Xiaodan Liang
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Recent advances in natural language processing, primarily propelled by Large Language Models (LLMs), have showcased their remarkable capabilities grounded in in-context learning. A promising avenue for guiding LLMs in intricate reasoning tasks involves the utilization of intermediate reasoning steps within the Chain-...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 16:44:37 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 16:24:58 GMT" } ]
2023-10-06T00:00:00
[ [ "Xiong", "Jiong", "" ], [ "Li", "Zixuan", "" ], [ "Zheng", "Chuanyang", "" ], [ "Guo", "Zhijiang", "" ], [ "Yin", "Yichun", "" ], [ "Xie", "Enze", "" ], [ "Yang", "Zhicheng", "" ], [ "Cao", "Qin...
not_new_dataset
0.997436
2310.02964
Zihan Liu
Zihan Liu, Ge Wang, Jiaqi Wang, Jiangbin Zheng, Stan Z. Li
Co-modeling the Sequential and Graphical Routes for Peptide Representation Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Peptides are formed by the dehydration condensation of multiple amino acids. The primary structure of a peptide can be represented either as an amino acid sequence or as a molecular graph consisting of atoms and chemical bonds. Previous studies have indicated that deep learning routes specific to sequential and graph...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 16:58:25 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 12:42:25 GMT" } ]
2023-10-06T00:00:00
[ [ "Liu", "Zihan", "" ], [ "Wang", "Ge", "" ], [ "Wang", "Jiaqi", "" ], [ "Zheng", "Jiangbin", "" ], [ "Li", "Stan Z.", "" ] ]
not_new_dataset
0.997392
2310.02969
Guancheng Qiu
Guancheng Qiu, Mathieu Tanneau, Pascal Van Hentenryck
Dual Conic Proxies for AC Optimal Power Flow
null
null
null
null
cs.LG math.OC
http://creativecommons.org/licenses/by-nc-nd/4.0/
In recent years, there has been significant interest in the development of machine learning-based optimization proxies for AC Optimal Power Flow (AC-OPF). Although significant progress has been achieved in predicting high-quality primal solutions, no existing learning-based approach can provide valid dual bounds for ...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 17:06:30 GMT" } ]
2023-10-06T00:00:00
[ [ "Qiu", "Guancheng", "" ], [ "Tanneau", "Mathieu", "" ], [ "Van Hentenryck", "Pascal", "" ] ]
not_new_dataset
0.997348
2310.02995
Pengyuan Lu
Pengyuan Lu and Michele Caprio and Eric Eaton and Insup Lee
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual Learning
Duplicate submission to arxiv
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Like generic multi-task learning, continual learning has the nature of multi-objective optimization, and therefore faces a trade-off between the performance of different tasks. That is, to optimize for the current task distribution, it may need to compromise performance on some previous tasks. This means that there e...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 17:30:50 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 17:58:37 GMT" } ]
2023-10-06T00:00:00
[ [ "Lu", "Pengyuan", "" ], [ "Caprio", "Michele", "" ], [ "Eaton", "Eric", "" ], [ "Lee", "Insup", "" ] ]
not_new_dataset
0.997348
2310.03006
Zhizheng Liu
Zhizheng Liu, Mattia Segu, Fisher Yu
COOLer: Class-Incremental Learning for Appearance-Based Multiple Object Tracking
GCPR 2023 Oral
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Continual learning allows a model to learn multiple tasks sequentially while retaining the old knowledge without the training data of the preceding tasks. This paper extends the scope of continual learning research to class-incremental learning for multiple object tracking (MOT), which is desirable to accommodate the...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 17:49:48 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 05:54:34 GMT" } ]
2023-10-06T00:00:00
[ [ "Liu", "Zhizheng", "" ], [ "Segu", "Mattia", "" ], [ "Yu", "Fisher", "" ] ]
not_new_dataset
0.996938
2310.03031
Stefanie Urchs
Stefanie Urchs and Veronika Thurner and Matthias A{\ss}enmacher and Christian Heumann and Stephanie Thiemichen
How Prevalent is Gender Bias in ChatGPT? -- Exploring German and English ChatGPT Responses
Accepted @ "1st Workshop on Biased Data in Conversational Agents" (co-located with ECML PKDD 2023). This is the author's version of the work. The definite version of record will be published in the proceedings
null
null
null
cs.CL cs.AI cs.CY cs.LG
http://creativecommons.org/licenses/by/4.0/
With the introduction of ChatGPT, OpenAI made large language models (LLM) accessible to users with limited IT expertise. However, users with no background in natural language processing (NLP) might lack a proper understanding of LLMs. Thus the awareness of their inherent limitations, and therefore will take the syste...
[ { "version": "v1", "created": "Thu, 21 Sep 2023 07:54:25 GMT" } ]
2023-10-06T00:00:00
[ [ "Urchs", "Stefanie", "" ], [ "Thurner", "Veronika", "" ], [ "Aßenmacher", "Matthias", "" ], [ "Heumann", "Christian", "" ], [ "Thiemichen", "Stephanie", "" ] ]
not_new_dataset
0.997556
2310.03032
Cong Xu
Cong Xu, Jun Wang, Jianyong Wang, Wei Zhang
Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution
13 pages
null
null
null
cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Embedding plays a critical role in modern recommender systems because they are virtual representations of real-world entities and the foundation for subsequent decision models. In this paper, we propose a novel embedding update mechanism, Structure-aware Embedding Evolution (SEvo for short), to encourage related node...
[ { "version": "v1", "created": "Sun, 24 Sep 2023 04:09:16 GMT" } ]
2023-10-06T00:00:00
[ [ "Xu", "Cong", "" ], [ "Wang", "Jun", "" ], [ "Wang", "Jianyong", "" ], [ "Zhang", "Wei", "" ] ]
not_new_dataset
0.997359
2310.03033
EPTCS
Andreea Postovan, M\u{a}d\u{a}lina Era\c{s}cu
Benchmarking Local Robustness of High-Accuracy Binary Neural Networks for Enhanced Traffic Sign Recognition
In Proceedings FROM 2023, arXiv:2309.12959
EPTCS 389, 2023, pp. 120-130
10.4204/EPTCS.389.10
null
cs.CV cs.AI cs.LG cs.LO
http://creativecommons.org/licenses/by/4.0/
Traffic signs play a critical role in road safety and traffic management for autonomous driving systems. Accurate traffic sign classification is essential but challenging due to real-world complexities like adversarial examples and occlusions. To address these issues, binary neural networks offer promise in construct...
[ { "version": "v1", "created": "Mon, 25 Sep 2023 01:17:14 GMT" } ]
2023-10-06T00:00:00
[ [ "Postovan", "Andreea", "" ], [ "Eraşcu", "Mădălina", "" ] ]
not_new_dataset
0.997358
2310.03036
Wen-Jie Liu
Wenjie Liu, Bosi Wang, Jihao Fan, Yebo Ge, Mohammed Zidan
A quantum system control method based on enhanced reinforcement learning
10 pages, 3 figures
Soft Computing, 2022. 26(14): p. 6567-6575
10.1007/s00500-022-07179-5
null
cs.ET cs.AI quant-ph
http://creativecommons.org/licenses/by/4.0/
Traditional quantum system control methods often face different constraints, and are easy to cause both leakage and stochastic control errors under the condition of limited resources. Reinforcement learning has been proved as an efficient way to complete the quantum system control task. To learn a satisfactory contro...
[ { "version": "v1", "created": "Sat, 30 Sep 2023 03:22:44 GMT" } ]
2023-10-06T00:00:00
[ [ "Liu", "Wenjie", "" ], [ "Wang", "Bosi", "" ], [ "Fan", "Jihao", "" ], [ "Ge", "Yebo", "" ], [ "Zidan", "Mohammed", "" ] ]
not_new_dataset
0.997303
2310.03037
Wen-Jie Liu
Wenjie Liu, Lu Wang
Quantum image edge detection based on eight-direction Sobel operator for NEQR
27 pages, 20 figures
Quantum Information Processing, 2022. 21(5): p. 190
10.1007/s11128-022-03527-4
null
cs.CV cs.ET quant-ph
http://creativecommons.org/licenses/by/4.0/
Quantum Sobel edge detection (QSED) is a kind of algorithm for image edge detection using quantum mechanism, which can solve the real-time problem encountered by classical algorithms. However, the existing QSED algorithms only consider two- or four-direction Sobel operator, which leads to a certain loss of edge detai...
[ { "version": "v1", "created": "Sun, 1 Oct 2023 05:38:59 GMT" } ]
2023-10-06T00:00:00
[ [ "Liu", "Wenjie", "" ], [ "Wang", "Lu", "" ] ]
not_new_dataset
0.997303
2310.03038
Wen-Jie Liu
Wenjie Liu, Lu Wang, Qingshan Wu
A quantum moving target segmentation algorithm for grayscale video
15 pages, 15 figures
Advanced Quantum Technologies, 2023, In Production
10.1002/qute.202300248
null
cs.CV cs.ET quant-ph
http://creativecommons.org/licenses/by/4.0/
The moving target segmentation (MTS) aims to segment out moving targets in the video, however, the classical algorithm faces the huge challenge of real-time processing in the current video era. Some scholars have successfully demonstrated the quantum advantages in some video processing tasks, but not concerning movin...
[ { "version": "v1", "created": "Sun, 1 Oct 2023 15:38:27 GMT" } ]
2023-10-06T00:00:00
[ [ "Liu", "Wenjie", "" ], [ "Wang", "Lu", "" ], [ "Wu", "Qingshan", "" ] ]
not_new_dataset
0.997253
2310.03043
Jianghong Zhou
Jianghong Zhou, Joyce C. Ho, Chen Lin, Eugene Agichtein
A Deep Reinforcement Learning Approach for Interactive Search with Sentence-level Feedback
9 pages, 7 figures, DRL4IR@CIKM
null
null
null
cs.LG cs.AI cs.HC cs.IR
http://creativecommons.org/licenses/by/4.0/
Interactive search can provide a better experience by incorporating interaction feedback from the users. This can significantly improve search accuracy as it helps avoid irrelevant information and captures the users' search intents. Existing state-of-the-art (SOTA) systems use reinforcement learning (RL) models to in...
[ { "version": "v1", "created": "Tue, 3 Oct 2023 18:45:21 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhou", "Jianghong", "" ], [ "Ho", "Joyce C.", "" ], [ "Lin", "Chen", "" ], [ "Agichtein", "Eugene", "" ] ]
not_new_dataset
0.997375
2310.03044
Krzysztof Borowski Mr
Krzysztof Borowski, Bartosz Bali\'s
scg-cli -- a Tool Supporting Software Comprehension via Extraction and Analysis of Semantic Code Graph
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present scg-cli, a~command line tool facilitating software comprehension. The tool extracts semantic information about code structure and dependencies from the Java and Scala projects, and structures it as a~Semantic Code Graph (SCG), an information model underlying scg-cli. The SCG data, once written into a~porta...
[ { "version": "v1", "created": "Tue, 3 Oct 2023 19:04:51 GMT" } ]
2023-10-06T00:00:00
[ [ "Borowski", "Krzysztof", "" ], [ "Baliś", "Bartosz", "" ] ]
not_new_dataset
0.996638
2310.03046
Jieyu Zhang
Jieyu Zhang, Ranjay Krishna, Ahmed H. Awadallah, Chi Wang
EcoAssistant: Using LLM Assistant More Affordably and Accurately
null
null
null
null
cs.SE cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Today, users ask Large language models (LLMs) as assistants to answer queries that require external knowledge; they ask about the weather in a specific city, about stock prices, and even about where specific locations are within their neighborhood. These queries require the LLM to produce code that invokes external A...
[ { "version": "v1", "created": "Tue, 3 Oct 2023 22:16:13 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhang", "Jieyu", "" ], [ "Krishna", "Ranjay", "" ], [ "Awadallah", "Ahmed H.", "" ], [ "Wang", "Chi", "" ] ]
not_new_dataset
0.997105
2310.03049
Hasindu Kariyawasam
Hasindu Kariyawasam, Ramith Hettiarachchi, Dushan Wadduwage
QuATON: Quantization Aware Training of Optical Neurons
null
null
null
null
cs.LG eess.IV physics.optics
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Optical neural architectures (ONAs) use coding elements with optimized physical parameters to perform intelligent measurements. However, fabricating ONAs while maintaining design performances is challenging. Limitations in fabrication techniques often limit the realizable precision of the trained parameters. Physical...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 02:18:28 GMT" } ]
2023-10-06T00:00:00
[ [ "Kariyawasam", "Hasindu", "" ], [ "Hettiarachchi", "Ramith", "" ], [ "Wadduwage", "Dushan", "" ] ]
not_new_dataset
0.997338
2310.03051
Pei Zhou
Pei Zhou, Aman Madaan, Srividya Pranavi Potharaju, Aditya Gupta, Kevin R. McKee, Ari Holtzman, Jay Pujara, Xiang Ren, Swaroop Mishra, Aida Nematzadeh, Shyam Upadhyay, Manaal Faruqui
How FaR Are Large Language Models From Agents with Theory-of-Mind?
Preprint, 18 pages, 6 figures, 6 tables
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
"Thinking is for Doing." Humans can infer other people's mental states from observations--an ability called Theory-of-Mind (ToM)--and subsequently act pragmatically on those inferences. Existing question answering benchmarks such as ToMi ask models questions to make inferences about beliefs of characters in a story, ...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 06:47:58 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhou", "Pei", "" ], [ "Madaan", "Aman", "" ], [ "Potharaju", "Srividya Pranavi", "" ], [ "Gupta", "Aditya", "" ], [ "McKee", "Kevin R.", "" ], [ "Holtzman", "Ari", "" ], [ "Pujara", "Jay", "" ], [ ...
not_new_dataset
0.997392
2310.03052
Sangjun Park
Sangjun Park and JinYeong Bak
Memoria: Hebbian Memory Architecture for Human-Like Sequential Processing
Under review as a conference paper at ICLR 2024. 20 pages, 9 figures, 5 tables
null
null
null
cs.LG cs.AI cs.NE
http://creativecommons.org/licenses/by-nc-nd/4.0/
Transformers have demonstrated their success in various domains and tasks. However, Transformers struggle with long input sequences due to their limited capacity. While one solution is to increase input length, endlessly stretching the length is unrealistic. Furthermore, humans selectively remember and use only relev...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 09:40:46 GMT" } ]
2023-10-06T00:00:00
[ [ "Park", "Sangjun", "" ], [ "Bak", "JinYeong", "" ] ]
not_new_dataset
0.997277
2310.03055
Ishaan Kale
Ruturaj Reddy, Utkarsh Gupta, Ishaan Kale, Apoorva Shastri, Anand J Kulkarni
Modified LAB Algorithm with Clustering-based Search Space Reduction Method for solving Engineering Design Problems
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A modified LAB algorithm is introduced in this paper. It builds upon the original LAB algorithm (Reddy et al. 2023), which is a socio-inspired algorithm that models competitive and learning behaviours within a group, establishing hierarchical roles. The proposed algorithm incorporates the roulette wheel approach and ...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 12:35:13 GMT" } ]
2023-10-06T00:00:00
[ [ "Reddy", "Ruturaj", "" ], [ "Gupta", "Utkarsh", "" ], [ "Kale", "Ishaan", "" ], [ "Shastri", "Apoorva", "" ], [ "Kulkarni", "Anand J", "" ] ]
not_new_dataset
0.99724
2310.03059
Yiwen Tang
Ivan Tang and Eric Zhang and Ray Gu
Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models
10 pages. The specialized PEFT framework for 3D pre-trained models, which achieves competitive performance to full fine-tuning, and significantly reduces the computational resources. Project page: https://github.com/EvenJoker/Point-PEFT
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
The popularity of pre-trained large models has revolutionized downstream tasks across diverse fields, such as language, vision, and multi-modality. To minimize the adaption cost for downstream tasks, many Parameter-Efficient Fine-Tuning (PEFT) techniques are proposed for language and 2D image pre-trained models. Howe...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 16:49:36 GMT" } ]
2023-10-06T00:00:00
[ [ "Tang", "Ivan", "" ], [ "Zhang", "Eric", "" ], [ "Gu", "Ray", "" ] ]
not_new_dataset
0.996882
2310.03084
Deniz Bayazit
Deniz Bayazit, Negar Foroutan, Zeming Chen, Gail Weiss, Antoine Bosselut
Discovering Knowledge-Critical Subnetworks in Pretrained Language Models
null
null
null
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pretrained language models (LMs) encode implicit representations of knowledge in their parameters. However, localizing these representations and disentangling them from each other remains an open problem. In this work, we investigate whether pretrained language models contain various knowledge-critical subnetworks: p...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:02:01 GMT" } ]
2023-10-06T00:00:00
[ [ "Bayazit", "Deniz", "" ], [ "Foroutan", "Negar", "" ], [ "Chen", "Zeming", "" ], [ "Weiss", "Gail", "" ], [ "Bosselut", "Antoine", "" ] ]
not_new_dataset
0.997429
2310.03085
Yann Traonmilin
Hui Shi (IMB), Yann Traonmilin (IMB), J-F Aujol (IMB)
Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoising
null
null
null
null
cs.LG cs.CV cs.IT eess.IV math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of denoising with the help of prior information taken from a database of clean signals or images. Denoising with variational methods is very efficient if a regularizer well adapted to the nature of the data is available. Thanks to the maximum a posteriori Bayesian framework, such regularizer c...
[ { "version": "v1", "created": "Mon, 2 Oct 2023 11:46:11 GMT" } ]
2023-10-06T00:00:00
[ [ "Shi", "Hui", "", "IMB" ], [ "Traonmilin", "Yann", "", "IMB" ], [ "Aujol", "J-F", "", "IMB" ] ]
not_new_dataset
0.997421
2310.03086
Suresh Kumar
Suresh Kumar, Dhanyashri Guruparan, Pavithren Aaron, Philemon Telajan, Kavinesh Mahadevan, Dinesh Davagandhi, Ong Xin Yue
Deep Learning in Computational Biology: Advancements, Challenges, and Future Outlook
50 pages, 1 figure, 2 tables
null
null
null
cs.LG cs.AI q-bio.QM
http://creativecommons.org/licenses/by-nc-sa/4.0/
Deep learning has become a powerful tool in computational biology, revolutionising the analysis and interpretation of biological data over time. In our article review, we delve into various aspects of deep learning in computational biology. Specifically, we examine its history, advantages, and challenges. Our focus i...
[ { "version": "v1", "created": "Mon, 2 Oct 2023 07:53:05 GMT" } ]
2023-10-06T00:00:00
[ [ "Kumar", "Suresh", "" ], [ "Guruparan", "Dhanyashri", "" ], [ "Aaron", "Pavithren", "" ], [ "Telajan", "Philemon", "" ], [ "Mahadevan", "Kavinesh", "" ], [ "Davagandhi", "Dinesh", "" ], [ "Yue", "Ong Xin", ...
not_new_dataset
0.997487
2310.03088
Solon Falas
Solon Falas, Markos Asprou, Charalambos Konstantinou, Maria K. Michael
Physics-Informed Neural Networks for Accelerating Power System State Estimation
null
null
null
null
cs.LG cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
State estimation is the cornerstone of the power system control center since it provides the operating condition of the system in consecutive time intervals. This work investigates the application of physics-informed neural networks (PINNs) for accelerating power systems state estimation in monitoring the operation o...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:14:48 GMT" } ]
2023-10-06T00:00:00
[ [ "Falas", "Solon", "" ], [ "Asprou", "Markos", "" ], [ "Konstantinou", "Charalambos", "" ], [ "Michael", "Maria K.", "" ] ]
not_new_dataset
0.997359
2310.03091
Daile Osorio-Roig
Daile Osorio-Roig, Lazaro J. Gonzalez-Soler, Christian Rathgeb, Christoph Busch
Privacy-preserving Multi-biometric Indexing based on Frequent Binary Patterns
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
The development of large-scale identification systems that ensure the privacy protection of enrolled subjects represents a major challenge. Biometric deployments that provide interoperability and usability by including efficient multi-biometric solutions are a recent requirement. In the context of privacy protection,...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:18:24 GMT" } ]
2023-10-06T00:00:00
[ [ "Osorio-Roig", "Daile", "" ], [ "Gonzalez-Soler", "Lazaro J.", "" ], [ "Rathgeb", "Christian", "" ], [ "Busch", "Christoph", "" ] ]
not_new_dataset
0.997417
2310.03094
Murong Yue
Murong Yue, Jie Zhao, Min Zhang, Liang Du, Ziyu Yao
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
null
null
null
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) such as GPT-4 have exhibited remarkable performance in a variety of tasks, but this strong performance often comes with the high expense of using paid API services. In this paper, we are motivated to study building an LLM cascade to save the cost of using LLMs, particularly for performing...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:21:17 GMT" } ]
2023-10-06T00:00:00
[ [ "Yue", "Murong", "" ], [ "Zhao", "Jie", "" ], [ "Zhang", "Min", "" ], [ "Du", "Liang", "" ], [ "Yao", "Ziyu", "" ] ]
not_new_dataset
0.99747
2310.03095
Hossein B. Jond
Hossein B. Jond
Opinion Dynamics Optimization Through Noncooperative Differential Games
This paper was presented at 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)
null
null
null
cs.SI
http://creativecommons.org/licenses/by/4.0/
In this paper, I study optimizing the opinion formation of a social network of a population of individuals on a graph whose opinion evolves according to the Hegselmann-Krause model for opinion dynamics. I propose an optimization problem based on a differential game for a population of individuals who are not stubborn...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:25:47 GMT" } ]
2023-10-06T00:00:00
[ [ "Jond", "Hossein B.", "" ] ]
not_new_dataset
0.997226
2310.03098
Zichen Zhu
Zichen Zhu, Xiao Hu, Manos Athanassoulis
NOCAP: Near-Optimal Correlation-Aware Partitioning Joins
null
null
null
null
cs.DB
http://creativecommons.org/licenses/by/4.0/
Storage-based joins are still commonly used today because the memory budget does not always scale with the data size. One of the many join algorithms developed that has been widely deployed and proven to be efficient is the Hybrid Hash Join (HHJ), which is designed to exploit any available memory to maximize the data...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:28:10 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhu", "Zichen", "" ], [ "Hu", "Xiao", "" ], [ "Athanassoulis", "Manos", "" ] ]
not_new_dataset
0.997297
2310.03103
Guoyizhe Wei
Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa
Dual Prompt Tuning for Domain-Aware Federated Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain shift across clients. In this work, we consid...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:47:34 GMT" } ]
2023-10-06T00:00:00
[ [ "Wei", "Guoyizhe", "" ], [ "Wang", "Feng", "" ], [ "Shah", "Anshul", "" ], [ "Chellappa", "Rama", "" ] ]
not_new_dataset
0.997402
2310.03104
Monica Ribero
William Kong, Andr\'es Mu\~noz Medina and M\'onica Ribero
DP-SGD for non-decomposable objective functions
null
null
null
null
cs.LG cs.CR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Unsupervised pre-training is a common step in developing computer vision models and large language models. In this setting, the absence of labels requires the use of similarity-based loss functions, such as contrastive loss, that favor minimizing the distance between similar inputs and maximizing the distance between...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:48:16 GMT" } ]
2023-10-06T00:00:00
[ [ "Kong", "William", "" ], [ "Medina", "Andrés Muñoz", "" ], [ "Ribero", "Mónica", "" ] ]
not_new_dataset
0.997397
2310.03105
Hanrui Zhang
Yuan Deng, Mohammad Mahdian, Jieming Mao, Vahab Mirrokni, Hanrui Zhang, Song Zuo
Efficiency of the Generalized Second-Price Auction for Value Maximizers
null
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the price of anarchy of the generalized second-price auction where bidders are value maximizers (i.e., autobidders). We show that in general the price of anarchy can be as bad as $0$. For comparison, the price of anarchy of running VCG is $1/2$ in the autobidding world. We further show a fined-grained price ...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:49:54 GMT" } ]
2023-10-06T00:00:00
[ [ "Deng", "Yuan", "" ], [ "Mahdian", "Mohammad", "" ], [ "Mao", "Jieming", "" ], [ "Mirrokni", "Vahab", "" ], [ "Zhang", "Hanrui", "" ], [ "Zuo", "Song", "" ] ]
not_new_dataset
0.997413
2310.03108
Hamid Mohammadi
Hamid Mohammadi, Ehsan Nazerfard, Tahereh Firoozi
Reinforcement Learning-based Mixture of Vision Transformers for Video Violence Recognition
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Video violence recognition based on deep learning concerns accurate yet scalable human violence recognition. Currently, most state-of-the-art video violence recognition studies use CNN-based models to represent and categorize videos. However, recent studies suggest that pre-trained transformers are more accurate than...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 18:58:47 GMT" } ]
2023-10-06T00:00:00
[ [ "Mohammadi", "Hamid", "" ], [ "Nazerfard", "Ehsan", "" ], [ "Firoozi", "Tahereh", "" ] ]
not_new_dataset
0.997361
2310.03111
Rabia Gondur
Rabia Gondur, Usama Bin Sikandar, Evan Schaffer, Mikio Christian Aoi, Stephen L Keeley
Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data
null
null
null
null
cs.LG q-bio.NC
http://creativecommons.org/licenses/by/4.0/
Characterizing the relationship between neural population activity and behavioral data is a central goal of neuroscience. While latent variable models (LVMs) are successful in describing high-dimensional time-series data, they are typically only designed for a single type of data, making it difficult to identify stru...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 19:04:55 GMT" } ]
2023-10-06T00:00:00
[ [ "Gondur", "Rabia", "" ], [ "Sikandar", "Usama Bin", "" ], [ "Schaffer", "Evan", "" ], [ "Aoi", "Mikio Christian", "" ], [ "Keeley", "Stephen L", "" ] ]
not_new_dataset
0.997348
2310.03119
Tharindu Lakshan Yasarathna
Tharindu Lakshan Yasarathna, Lojenaa Navanesan, Simon Barque, Assanka Sayakkara and Nhien-An Le-Khac
Crossed-IoT device portability of Electromagnetic Side Channel Analysis: Challenges and Dataset
for associated dataset file, see https://aseados.ucd.ie/datasets/EMSCA-2023-Latest/
null
null
null
cs.LG cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
IoT (Internet of Things) refers to the network of interconnected physical devices, vehicles, home appliances, and other items embedded with sensors, software, and connectivity, enabling them to collect and exchange data. IoT Forensics is collecting and analyzing digital evidence from IoT devices to investigate cyberc...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 19:13:39 GMT" } ]
2023-10-06T00:00:00
[ [ "Yasarathna", "Tharindu Lakshan", "" ], [ "Navanesan", "Lojenaa", "" ], [ "Barque", "Simon", "" ], [ "Sayakkara", "Assanka", "" ], [ "Le-Khac", "Nhien-An", "" ] ]
not_new_dataset
0.997495
2310.03122
Md Rushdie Ibne Islam
Md Rushdie Ibne Islam
SPH-based framework for modelling fluid-structure interaction problems with finite deformation and fracturing
null
null
null
null
cs.CE
http://creativecommons.org/licenses/by/4.0/
Understanding crack propagation in structures subjected to fluid loads is crucial in various engineering applications, ranging from underwater pipelines to aircraft components. This study investigates the dynamic response of structures, including their damage and fracture behaviour under hydrodynamic load, emphasizin...
[ { "version": "v1", "created": "Fri, 22 Sep 2023 08:47:37 GMT" } ]
2023-10-06T00:00:00
[ [ "Islam", "Md Rushdie Ibne", "" ] ]
not_new_dataset
0.997145
2310.03123
Zihao Lin
Zihao Lin, Yan Sun, Yifan Shi, Xueqian Wang, Lifu Huang, Li Shen, Dacheng Tao
Efficient Federated Prompt Tuning for Black-box Large Pre-trained Models
20 pages, 6 figures, preprint
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the blowout development of pre-trained models (PTMs), the efficient tuning of these models for diverse downstream applications has emerged as a pivotal research concern. Although recent investigations into prompt tuning have provided promising avenues, three salient challenges persist: (1) memory constraint: the...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 19:30:49 GMT" } ]
2023-10-06T00:00:00
[ [ "Lin", "Zihao", "" ], [ "Sun", "Yan", "" ], [ "Shi", "Yifan", "" ], [ "Wang", "Xueqian", "" ], [ "Huang", "Lifu", "" ], [ "Shen", "Li", "" ], [ "Tao", "Dacheng", "" ] ]
not_new_dataset
0.997442
2310.03125
Yihan Wu
Yihan Wu, Brandon Y. Feng, Heng Huang
Shielding the Unseen: Privacy Protection through Poisoning NeRF with Spatial Deformation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In this paper, we introduce an innovative method of safeguarding user privacy against the generative capabilities of Neural Radiance Fields (NeRF) models. Our novel poisoning attack method induces changes to observed views that are imperceptible to the human eye, yet potent enough to disrupt NeRF's ability to accurat...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 19:35:56 GMT" } ]
2023-10-06T00:00:00
[ [ "Wu", "Yihan", "" ], [ "Feng", "Brandon Y.", "" ], [ "Huang", "Heng", "" ] ]
not_new_dataset
0.9974
2310.03128
Yue Huang
Yue Huang and Jiawen Shi and Yuan Li and Chenrui Fan and Siyuan Wu and Qihui Zhang and Yixin Liu and Pan Zhou and Yao Wan and Neil Zhenqiang Gong and Lichao Sun
MetaTool Benchmark: Deciding Whether to Use Tools and Which to Use
null
null
null
null
cs.SE cs.CL
http://creativecommons.org/licenses/by/4.0/
Large language models (LLMs) have garnered significant attention due to their impressive natural language processing (NLP) capabilities. Recently, many studies have focused on the tool utilization ability of LLMs. They primarily investigated how LLMs effectively collaborate with given specific tools. However, in scen...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 19:39:26 GMT" } ]
2023-10-06T00:00:00
[ [ "Huang", "Yue", "" ], [ "Shi", "Jiawen", "" ], [ "Li", "Yuan", "" ], [ "Fan", "Chenrui", "" ], [ "Wu", "Siyuan", "" ], [ "Zhang", "Qihui", "" ], [ "Liu", "Yixin", "" ], [ "Zhou", "Pan", "" ...
new_dataset
0.997708
2310.03131
Vignesh Viswanathan
Gagan Biradar, Yacine Izza, Elita Lobo, Vignesh Viswanathan, Yair Zick
Axiomatic Aggregations of Abductive Explanations
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The recent criticisms of the robustness of post hoc model approximation explanation methods (like LIME and SHAP) have led to the rise of model-precise abductive explanations. For each data point, abductive explanations provide a minimal subset of features that are sufficient to generate the outcome. While theoretical...
[ { "version": "v1", "created": "Fri, 29 Sep 2023 04:06:10 GMT" } ]
2023-10-06T00:00:00
[ [ "Biradar", "Gagan", "" ], [ "Izza", "Yacine", "" ], [ "Lobo", "Elita", "" ], [ "Viswanathan", "Vignesh", "" ], [ "Zick", "Yair", "" ] ]
not_new_dataset
0.997462
2310.03132
Yebin Wang
Adrian Stein, Yebin Wang, Yusuke Sakamoto, Bingnan Wang, and Huazhen Fang
Application-Oriented Co-Design of Motors and Motions for a 6DOF Robot Manipulator
null
null
null
null
cs.RO cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work investigates an application-driven co-design problem where the motion and motors of a six degrees of freedom robotic manipulator are optimized simultaneously, and the application is characterized by a set of tasks. Unlike the state-of-the-art which selects motors from a product catalogue and performs co-des...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 19:44:45 GMT" } ]
2023-10-06T00:00:00
[ [ "Stein", "Adrian", "" ], [ "Wang", "Yebin", "" ], [ "Sakamoto", "Yusuke", "" ], [ "Wang", "Bingnan", "" ], [ "Fang", "Huazhen", "" ] ]
not_new_dataset
0.997268
2310.03137
Edward Guo
Eddie Guo, Christopher Perlette, Mojtaba Sharifi, Lukas Grasse, Matthew Tata, Vivian K. Mushahwar, Mahdi Tavakoli
Speech-Based Human-Exoskeleton Interaction for Lower Limb Motion Planning
13 pages, 8 figures, 2 tables
null
null
null
cs.RO cs.HC
http://creativecommons.org/licenses/by/4.0/
This study presents a speech-based motion planning strategy (SBMP) developed for lower limb exoskeletons to facilitate safe and compliant human-robot interaction. A speech processing system, finite state machine, and central pattern generator are the building blocks of the proposed strategy for online planning of the...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 19:57:52 GMT" } ]
2023-10-06T00:00:00
[ [ "Guo", "Eddie", "" ], [ "Perlette", "Christopher", "" ], [ "Sharifi", "Mojtaba", "" ], [ "Grasse", "Lukas", "" ], [ "Tata", "Matthew", "" ], [ "Mushahwar", "Vivian K.", "" ], [ "Tavakoli", "Mahdi", "" ] ]
not_new_dataset
0.997257
2310.03140
Bryan Bo Cao
Bryan Bo Cao, Abrar Alali, Hansi Liu, Nicholas Meegan, Marco Gruteser, Kristin Dana, Ashwin Ashok, Shubham Jain
ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements
22 pages, 12 figures, 9 tables. MobiCom 2023 ISACom
null
10.1145/3615984.3616503
null
cs.CV cs.MM
http://creativecommons.org/licenses/by-nc-sa/4.0/
Tracking subjects in videos is one of the most widely used functions in camera-based IoT applications such as security surveillance, smart city traffic safety enhancement, vehicle to pedestrian communication and so on. In the computer vision domain, tracking is usually achieved by first detecting subjects with boundi...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:05:40 GMT" } ]
2023-10-06T00:00:00
[ [ "Cao", "Bryan Bo", "" ], [ "Alali", "Abrar", "" ], [ "Liu", "Hansi", "" ], [ "Meegan", "Nicholas", "" ], [ "Gruteser", "Marco", "" ], [ "Dana", "Kristin", "" ], [ "Ashok", "Ashwin", "" ], [ "Jain", ...
not_new_dataset
0.99726
2310.03142
Yong Deng
Yong Deng and Min Dong
Design and Optimization of Heterogeneous Coded Distributed Computing with Nonuniform File Popularity
15 pages, 7 figures, 3 tables
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies MapReduce-based heterogeneous coded distributed computing (CDC) where, besides different computing capabilities at workers, input files to be accessed by computing jobs have nonuniform popularity. We propose a file placement strategy that can handle an arbitrary number of input files. Furthermore, ...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:06:26 GMT" } ]
2023-10-06T00:00:00
[ [ "Deng", "Yong", "" ], [ "Dong", "Min", "" ] ]
not_new_dataset
0.997392
2310.03146
Son Nguyen
Adam Wang, Son Nguyen, Albert Montillo
Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional deep learning (DL) suffers from two core problems. Firstly, it assumes training samples are independent and identically distributed. However, numerous real-world datasets group samples by shared measurements (e.g., study participants or cells), violating this assumption. In these scenarios, DL can show co...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:18:45 GMT" } ]
2023-10-06T00:00:00
[ [ "Wang", "Adam", "" ], [ "Nguyen", "Son", "" ], [ "Montillo", "Albert", "" ] ]
not_new_dataset
0.997431
2310.03147
Jovan Jeromela
Jovan Jeromela
Context-Based Tweet Engagement Prediction
Submitted as a Diploma Thesis at TU Wien on 2023-05-25. Advisor: Peter Knees. 198 pages
null
10.34726/hss.2023.79627
null
cs.IR cs.LG cs.SI
http://creativecommons.org/licenses/by/4.0/
Twitter is currently one of the biggest social media platforms. Its users may share, read, and engage with short posts called tweets. For the ACM Recommender Systems Conference 2020, Twitter published a dataset around 70 GB in size for the annual RecSys Challenge. In 2020, the RecSys Challenge invited participating t...
[ { "version": "v1", "created": "Thu, 28 Sep 2023 08:36:57 GMT" } ]
2023-10-06T00:00:00
[ [ "Jeromela", "Jovan", "" ] ]
new_dataset
0.996766
2310.03148
Phanideep Gampa
Phanideep Gampa, Farnoosh Javadi, Belhassen Bayar, Ainur Yessenalina
Multi-Task Learning For Reduced Popularity Bias In Multi-Territory Video Recommendations
Recsys CARS 2023 Workshop paper
null
null
null
cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Various data imbalances that naturally arise in a multi-territory personalized recommender system can lead to a significant item bias for globally prevalent items. A locally popular item can be overshadowed by a globally prevalent item. Moreover, users' viewership patterns/statistics can drastically change from one g...
[ { "version": "v1", "created": "Mon, 25 Sep 2023 00:11:33 GMT" } ]
2023-10-06T00:00:00
[ [ "Gampa", "Phanideep", "" ], [ "Javadi", "Farnoosh", "" ], [ "Bayar", "Belhassen", "" ], [ "Yessenalina", "Ainur", "" ] ]
not_new_dataset
0.997316
2310.03149
Davis Brown
Nicholas Konz, Charles Godfrey, Madelyn Shapiro, Jonathan Tu, Henry Kvinge, Davis Brown
Attributing Learned Concepts in Neural Networks to Training Data
null
null
null
null
cs.LG cs.AI cs.CV
http://creativecommons.org/licenses/by/4.0/
By now there is substantial evidence that deep learning models learn certain human-interpretable features as part of their internal representations of data. As having the right (or wrong) concepts is critical to trustworthy machine learning systems, it is natural to ask which inputs from the model's original training...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:26:59 GMT" } ]
2023-10-06T00:00:00
[ [ "Konz", "Nicholas", "" ], [ "Godfrey", "Charles", "" ], [ "Shapiro", "Madelyn", "" ], [ "Tu", "Jonathan", "" ], [ "Kvinge", "Henry", "" ], [ "Brown", "Davis", "" ] ]
not_new_dataset
0.997322
2310.03150
Herbert Woisetschl\"ager
Herbert Woisetschl\"ager, Alexander Isenko, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly
6 pages, 3 figures
null
null
null
cs.LG cs.DC cs.PF
http://creativecommons.org/licenses/by-nc-nd/4.0/
Large Language Models (LLM) and foundation models are popular as they offer new opportunities for individuals and businesses to improve natural language processing, interact with data, and retrieve information faster. However, training or fine-tuning LLMs requires a vast amount of data, which can be challenging to ac...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:27:20 GMT" } ]
2023-10-06T00:00:00
[ [ "Woisetschläger", "Herbert", "" ], [ "Isenko", "Alexander", "" ], [ "Wang", "Shiqiang", "" ], [ "Mayer", "Ruben", "" ], [ "Jacobsen", "Hans-Arno", "" ] ]
not_new_dataset
0.997422
2310.03152
Zihao Wang
Zihao Wang, Yongqiang Chen, Yang Duan, Weijiang Li, Bo Han, James Cheng, Hanghang Tong
Towards out-of-distribution generalizable predictions of chemical kinetics properties
Work in progress. 11 pages, 1 figure, and 5 tables
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine Learning (ML) techniques have found applications in estimating chemical kinetics properties. With the accumulated drug molecules identified through "AI4drug discovery", the next imperative lies in AI-driven design for high-throughput chemical synthesis processes, with the estimation of properties of unseen re...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:36:41 GMT" } ]
2023-10-06T00:00:00
[ [ "Wang", "Zihao", "" ], [ "Chen", "Yongqiang", "" ], [ "Duan", "Yang", "" ], [ "Li", "Weijiang", "" ], [ "Han", "Bo", "" ], [ "Cheng", "James", "" ], [ "Tong", "Hanghang", "" ] ]
not_new_dataset
0.997345
2310.03156
Ziyao Wang
Ziyao Wang, Jianyu Wang, Ang Li
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent
null
null
null
null
cs.LG cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The theoretical landscape of federated learning (FL) undergoes rapid evolution, but its practical application encounters a series of intricate challenges, and hyperparameter optimization is one of these critical challenges. Amongst the diverse adjustments in hyperparameters, the adaptation of the learning rate emerge...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:51:52 GMT" } ]
2023-10-06T00:00:00
[ [ "Wang", "Ziyao", "" ], [ "Wang", "Jianyu", "" ], [ "Li", "Ang", "" ] ]
not_new_dataset
0.996782
2310.03158
Jiri Navratil
Jiri Navratil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves
Published at Workshop on Distribution-Free Uncertainty Quantification, International Conference on Machine Learning (ICML), July 2022. arXiv admin note: substantial text overlap with arXiv:2106.00858
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Accurate quantification of model uncertainty has long been recognized as a fundamental requirement for trusted AI. In regression tasks, uncertainty is typically quantified using prediction intervals calibrated to an ad-hoc operating point, making evaluation and comparison across different studies relatively difficult...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:54:08 GMT" } ]
2023-10-06T00:00:00
[ [ "Navratil", "Jiri", "" ], [ "Elder", "Benjamin", "" ], [ "Arnold", "Matthew", "" ], [ "Ghosh", "Soumya", "" ], [ "Sattigeri", "Prasanna", "" ] ]
not_new_dataset
0.997466
2310.03159
Dimitri Bertsekas
Dimitri Bertsekas
New Auction Algorithms for the Assignment Problem and Extensions
null
null
null
null
cs.GT
http://creativecommons.org/licenses/by/4.0/
We consider the classical linear assignment problem, and we introduce new auction algorithms for its optimal and suboptimal solution. The algorithms are founded on duality theory, and are related to ideas of competitive bidding by persons for objects and the attendant market equilibrium, which underlie real-life auct...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 20:54:41 GMT" } ]
2023-10-06T00:00:00
[ [ "Bertsekas", "Dimitri", "" ] ]
not_new_dataset
0.997415
2310.03161
Victor George
Victor Vadakechirayath George
Neural architecture impact on identifying temporally extended Reinforcement Learning tasks
Master's thesis at Albert-Ludwigs-University, Freiburg Faculty of Engineering, Department of Computer Science Chair for Machine Learning. Advisor: Raghu Rajan, Examiners: Prof. Dr. Frank Hutter, Prof. Dr. Thomas Brox
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Inspired by recent developments in attention models for image classification and natural language processing, we present various Attention based architectures in reinforcement learning (RL) domain, capable of performing well on OpenAI Gym Atari-2600 game suite. In spite of the recent success of Deep Reinforcement lea...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:09:19 GMT" } ]
2023-10-06T00:00:00
[ [ "George", "Victor Vadakechirayath", "" ] ]
not_new_dataset
0.9972
2310.03162
Hui Zhong
Hui Zhong, Chenpei Huang, Xinyue Zhang, Miao Pan
Metaverse CAN: Embracing Continuous, Active, and Non-intrusive Biometric Authentication
6 pages, 3 figures
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Metaverse is a virtual world, an immersive experience, a new human-computer interaction, built upon various advanced technologies. How to protect Metaverse personal information and virtual properties is also facing new challenges, such as new attacks and new expectations of user experiences. While traditional met...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:09:33 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhong", "Hui", "" ], [ "Huang", "Chenpei", "" ], [ "Zhang", "Xinyue", "" ], [ "Pan", "Miao", "" ] ]
not_new_dataset
0.997382
2310.03163
Junbo Li
Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang
FedNAR: Federated Optimization with Normalized Annealing Regularization
Thirty-seventh Conference on Neural Information Processing Systems
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Weight decay is a standard technique to improve generalization performance in modern deep neural network optimization, and is also widely adopted in federated learning (FL) to prevent overfitting in local clients. In this paper, we first explore the choices of weight decay and identify that weight decay value appreci...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:11:40 GMT" } ]
2023-10-06T00:00:00
[ [ "Li", "Junbo", "" ], [ "Li", "Ang", "" ], [ "Tian", "Chong", "" ], [ "Ho", "Qirong", "" ], [ "Xing", "Eric P.", "" ], [ "Wang", "Hongyi", "" ] ]
not_new_dataset
0.98839
2310.03165
Yitzchak Shmalo
Leonid Berlyand, Etienne Sandier, Yitzchak Shmalo, Lei Zhang
Enhancing Accuracy in Deep Learning Using Random Matrix Theory
null
null
null
null
cs.LG math.OC
http://creativecommons.org/licenses/by/4.0/
In this study, we explore the applications of random matrix theory (RMT) in the training of deep neural networks (DNNs), focusing on layer pruning to simplify DNN architecture and loss landscape. RMT, recently used to address overfitting in deep learning, enables the examination of DNN's weight layer spectra. We use ...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:17:31 GMT" } ]
2023-10-06T00:00:00
[ [ "Berlyand", "Leonid", "" ], [ "Sandier", "Etienne", "" ], [ "Shmalo", "Yitzchak", "" ], [ "Zhang", "Lei", "" ] ]
not_new_dataset
0.997497
2310.03166
Biagio Montaruli
Biagio Montaruli, Luca Demetrio, Maura Pintor, Luca Compagna, Davide Balzarotti, Battista Biggio
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security (AISec '23), November 30, 2023, Copenhagen, Denmark
null
10.1145/3605764.3623920
null
cs.CR cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
Machine-learning phishing webpage detectors (ML-PWD) have been shown to suffer from adversarial manipulations of the HTML code of the input webpage. Nevertheless, the attacks recently proposed have demonstrated limited effectiveness due to their lack of optimizing the usage of the adopted manipulations, and they focu...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:20:44 GMT" } ]
2023-10-06T00:00:00
[ [ "Montaruli", "Biagio", "" ], [ "Demetrio", "Luca", "" ], [ "Pintor", "Maura", "" ], [ "Compagna", "Luca", "" ], [ "Balzarotti", "Davide", "" ], [ "Biggio", "Battista", "" ] ]
not_new_dataset
0.997361
2310.03171
Shagun Jhaver
Alyvia Walters and Tawfiq Ammari and Kiran Garimella and Shagun Jhaver
Online Knowledge Production in Polarized Political Memes: The Case of Critical Race Theory
null
null
null
null
cs.HC
http://creativecommons.org/licenses/by-nc-sa/4.0/
Visual culture has long been deployed by actors across the political spectrum as tools of political mobilization, and have recently incorporated new communication tools, such as memes, GIFs, and emojis. In this study, we analyze the top-circulated Facebook memes relating to critical race theory (CRT) from May 2021 - ...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:33:56 GMT" } ]
2023-10-06T00:00:00
[ [ "Walters", "Alyvia", "" ], [ "Ammari", "Tawfiq", "" ], [ "Garimella", "Kiran", "" ], [ "Jhaver", "Shagun", "" ] ]
not_new_dataset
0.997302
2310.03172
Darren Chiu
Darren Chiu, Radhika Nagpal, Bahar Haghighat
Optimization and Evaluation of Multi Robot Surface Inspection Through Particle Swarm Optimization
6 pages, 8 figures
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
Robot swarms can be tasked with a variety of automated sensing and inspection applications in aerial, aquatic, and surface environments. In this paper, we study a simplified two-outcome surface inspection task. We task a group of robots to inspect and collectively classify a 2D surface section based on a binary patte...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:35:00 GMT" } ]
2023-10-06T00:00:00
[ [ "Chiu", "Darren", "" ], [ "Nagpal", "Radhika", "" ], [ "Haghighat", "Bahar", "" ] ]
not_new_dataset
0.997323
2310.03173
Zishun Yu
Zishun Yu, Yunzhe Tao, Liyu Chen, Tao Sun, Hongxia Yang
$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Program synthesis aims to create accurate, executable code from natural language descriptions. This field has leveraged the power of reinforcement learning (RL) in conjunction with large language models (LLMs), significantly enhancing code generation capabilities. This integration focuses on directly optimizing funct...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:40:36 GMT" } ]
2023-10-06T00:00:00
[ [ "Yu", "Zishun", "" ], [ "Tao", "Yunzhe", "" ], [ "Chen", "Liyu", "" ], [ "Sun", "Tao", "" ], [ "Yang", "Hongxia", "" ] ]
not_new_dataset
0.997308
2310.03174
Mosab Rezaei
Mosab Rezaei, Hamed Alhoori, Mona Rahimi
Test Case Recommendations with Distributed Representation of Code Syntactic Features
8 pages, 4 figures, 14th Workshop on Automating Test Case Design, Selection and Evaluation (A-TEST 2023) co-located with 38th IEEE/ACM International Conference on ASE 2023 conference
null
null
null
cs.LG cs.SE
http://creativecommons.org/licenses/by/4.0/
Frequent modifications of unit test cases are inevitable due to software's continuous underlying changes in source code, design, and requirements. Since manually maintaining software test suites is tedious, timely, and costly, automating the process of generation and maintenance of test units will significantly impac...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:42:01 GMT" } ]
2023-10-06T00:00:00
[ [ "Rezaei", "Mosab", "" ], [ "Alhoori", "Hamed", "" ], [ "Rahimi", "Mona", "" ] ]
not_new_dataset
0.997471
2310.03175
Md Sadik Awal
Md Sadik Awal, Md Tauhidur Rahman
Impedance Leakage Vulnerability and its Utilization in Reverse-engineering Embedded Software
null
null
null
null
cs.CR cs.IR eess.SP
http://creativecommons.org/licenses/by-sa/4.0/
Discovering new vulnerabilities and implementing security and privacy measures are important to protect systems and data against physical attacks. One such vulnerability is impedance, an inherent property of a device that can be exploited to leak information through an unintended side channel, thereby posing signific...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:43:16 GMT" } ]
2023-10-06T00:00:00
[ [ "Awal", "Md Sadik", "" ], [ "Rahman", "Md Tauhidur", "" ] ]
not_new_dataset
0.997374
2310.03178
Liangqi Yuan
Liangqi Yuan and Ziran Wang and Christopher G. Brinton
Digital Ethics in Federated Learning
null
null
null
null
cs.LG cs.CY cs.DC cs.GT
http://creativecommons.org/licenses/by/4.0/
The Internet of Things (IoT) consistently generates vast amounts of data, sparking increasing concern over the protection of data privacy and the limitation of data misuse. Federated learning (FL) facilitates collaborative capabilities among multiple parties by sharing machine learning (ML) model parameters instead o...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:48:35 GMT" } ]
2023-10-06T00:00:00
[ [ "Yuan", "Liangqi", "" ], [ "Wang", "Ziran", "" ], [ "Brinton", "Christopher G.", "" ] ]
not_new_dataset
0.997486
2310.03179
Min Dai
Min Dai, Jaemin Lee and Aaron D. Ames
Multi-Domain Walking with Reduced-Order Models of Locomotion
submitted to ACC 2024
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
Drawing inspiration from human multi-domain walking, this work presents a novel reduced-order model based framework for realizing multi-domain robotic walking. At the core of our approach is the viewpoint that human walking can be represented by a hybrid dynamical system, with continuous phases that are fully-actuate...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:48:35 GMT" } ]
2023-10-06T00:00:00
[ [ "Dai", "Min", "" ], [ "Lee", "Jaemin", "" ], [ "Ames", "Aaron D.", "" ] ]
not_new_dataset
0.997238
2310.03182
An Yan
An Yan, Yu Wang, Yiwu Zhong, Zexue He, Petros Karypis, Zihan Wang, Chengyu Dong, Amilcare Gentili, Chun-Nan Hsu, Jingbo Shang, Julian McAuley
Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models
18 pages, 12 figures
null
null
null
cs.CV cs.CL cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Medical image classification is a critical problem for healthcare, with the potential to alleviate the workload of doctors and facilitate diagnoses of patients. However, two challenges arise when deploying deep learning models to real-world healthcare applications. First, neural models tend to learn spurious correlat...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 21:57:09 GMT" } ]
2023-10-06T00:00:00
[ [ "Yan", "An", "" ], [ "Wang", "Yu", "" ], [ "Zhong", "Yiwu", "" ], [ "He", "Zexue", "" ], [ "Karypis", "Petros", "" ], [ "Wang", "Zihan", "" ], [ "Dong", "Chengyu", "" ], [ "Gentili", "Amilcare",...
not_new_dataset
0.997471
2310.03184
Zachary Levonian
Zachary Levonian, Chenglu Li, Wangda Zhu, Anoushka Gade, Owen Henkel, Millie-Ellen Postle, Wanli Xing
Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference
6 pages
null
null
null
cs.CL cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For middle-school math students, interactive question-answering (QA) with tutors is an effective way to learn. The flexibility and emergent capabilities of generative large language models (LLMs) has led to a surge of interest in automating portions of the tutoring process - including interactive QA to support concep...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 22:09:28 GMT" } ]
2023-10-06T00:00:00
[ [ "Levonian", "Zachary", "" ], [ "Li", "Chenglu", "" ], [ "Zhu", "Wangda", "" ], [ "Gade", "Anoushka", "" ], [ "Henkel", "Owen", "" ], [ "Postle", "Millie-Ellen", "" ], [ "Xing", "Wanli", "" ] ]
not_new_dataset
0.997327
2310.03185
Xiaohan Fu
Xiaohan Fu, Zihan Wang, Shuheng Li, Rajesh K. Gupta, Niloofar Mireshghallah, Taylor Berg-Kirkpatrick, Earlence Fernandes
Misusing Tools in Large Language Models With Visual Adversarial Examples
null
null
null
null
cs.CR cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Large Language Models (LLMs) are being enhanced with the ability to use tools and to process multiple modalities. These new capabilities bring new benefits and also new security risks. In this work, we show that an attacker can use visual adversarial examples to cause attacker-desired tool usage. For example, the att...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 22:10:01 GMT" } ]
2023-10-06T00:00:00
[ [ "Fu", "Xiaohan", "" ], [ "Wang", "Zihan", "" ], [ "Li", "Shuheng", "" ], [ "Gupta", "Rajesh K.", "" ], [ "Mireshghallah", "Niloofar", "" ], [ "Berg-Kirkpatrick", "Taylor", "" ], [ "Fernandes", "Earlence", "...
not_new_dataset
0.997438
2310.03188
Zhe Zhao
Zhe Zhao, Qingyun Liu, Huan Gui, Bang An, Lichan Hong, Ed H. Chi
Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication
19 pages, 3 figures
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Many recent breakthroughs in machine learning have been enabled by the pre-trained foundation models. By scaling up model parameters, training data, and computation resources, foundation models have significantly advanced the state-of-the-art in many applications. However, it is still an open question of how to use t...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 22:22:21 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhao", "Zhe", "" ], [ "Liu", "Qingyun", "" ], [ "Gui", "Huan", "" ], [ "An", "Bang", "" ], [ "Hong", "Lichan", "" ], [ "Chi", "Ed H.", "" ] ]
not_new_dataset
0.997222
2310.03191
Jeremy Dao
Jeremy Dao, Helei Duan, Alan Fern
Sim-to-Real Learning for Humanoid Box Loco-Manipulation
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work we propose a learning-based approach to box loco-manipulation for a humanoid robot. This is a particularly challenging problem due to the need for whole-body coordination in order to lift boxes of varying weight, position, and orientation while maintaining balance. To address this challenge, we present a...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 22:32:35 GMT" } ]
2023-10-06T00:00:00
[ [ "Dao", "Jeremy", "" ], [ "Duan", "Helei", "" ], [ "Fern", "Alan", "" ] ]
not_new_dataset
0.997246
2310.03192
Rania Abdelghani
Rania Abdelghani, H\'el\`ene Sauz\'eon and Pierre-Yves Oudeyer
Generative AI in the Classroom: Can Students Remain Active Learners?
null
null
null
null
cs.CY
http://creativecommons.org/licenses/by-nc-nd/4.0/
Generative Artificial Intelligence (GAI) has high potential to help address a diversity of educational challenges. In principle, GAI could facilitate the implementation of interactive and empowering pedagogical activities to complement the standard teaching strategies and favor students active engagement, understandi...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 22:33:46 GMT" } ]
2023-10-06T00:00:00
[ [ "Abdelghani", "Rania", "" ], [ "Sauzéon", "Hélène", "" ], [ "Oudeyer", "Pierre-Yves", "" ] ]
not_new_dataset
0.997504
2310.03193
Hancheng Cao
Hancheng Cao, Jesse Dodge, Kyle Lo, Daniel A. McFarland, Lucy Lu Wang
The Rise of Open Science: Tracking the Evolution and Perceived Value of Data and Methods Link-Sharing Practices
null
null
null
null
cs.DL cs.CL cs.CY physics.hist-ph physics.soc-ph
http://creativecommons.org/licenses/by/4.0/
In recent years, funding agencies and journals increasingly advocate for open science practices (e.g. data and method sharing) to improve the transparency, access, and reproducibility of science. However, quantifying these practices at scale has proven difficult. In this work, we leverage a large-scale dataset of 1.1...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 22:34:56 GMT" } ]
2023-10-06T00:00:00
[ [ "Cao", "Hancheng", "" ], [ "Dodge", "Jesse", "" ], [ "Lo", "Kyle", "" ], [ "McFarland", "Daniel A.", "" ], [ "Wang", "Lucy Lu", "" ] ]
not_new_dataset
0.996623
2310.03195
Todd Charter
Maziyar Khadivi, Todd Charter, Marjan Yaghoubi, Masoud Jalayer, Maryam Ahang, Ardeshir Shojaeinasab, Homayoun Najjaran
Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions
null
null
null
null
cs.LG cs.AI cs.NE
http://creativecommons.org/licenses/by-nc-sa/4.0/
Machine scheduling aims to optimize job assignments to machines while adhering to manufacturing rules and job specifications. This optimization leads to reduced operational costs, improved customer demand fulfillment, and enhanced production efficiency. However, machine scheduling remains a challenging combinatorial ...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 22:45:09 GMT" } ]
2023-10-06T00:00:00
[ [ "Khadivi", "Maziyar", "" ], [ "Charter", "Todd", "" ], [ "Yaghoubi", "Marjan", "" ], [ "Jalayer", "Masoud", "" ], [ "Ahang", "Maryam", "" ], [ "Shojaeinasab", "Ardeshir", "" ], [ "Najjaran", "Homayoun", "" ...
not_new_dataset
0.99749
2310.03200
Jongwook Woo Prof
Hsiu-Ping Lin, Suman Chauhan, Yougender Chauhan, Nagender Chauhan, Jongwook Woo
Amazon Books Rating prediction & Recommendation Model
5 pages, 4 figures, 8 tables
null
null
null
cs.IR cs.DC
http://creativecommons.org/licenses/by/4.0/
This paper uses the dataset of Amazon to predict the books ratings listed on Amazon website. As part of this project, we predicted the ratings of the books, and also built a recommendation cluster. This recommendation cluster provides the recommended books based on the column's values from dataset, for instance, cate...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 22:59:13 GMT" } ]
2023-10-06T00:00:00
[ [ "Lin", "Hsiu-Ping", "" ], [ "Chauhan", "Suman", "" ], [ "Chauhan", "Yougender", "" ], [ "Chauhan", "Nagender", "" ], [ "Woo", "Jongwook", "" ] ]
not_new_dataset
0.997197
2310.03202
Qifan Zhang
Qifan Zhang, Xuesong Bai, Xiang Li, Haixin Duan, Qi Li and Zhou Li
ResolverFuzz: Automated Discovery of DNS Resolver Vulnerabilities with Query-Response Fuzzing
Extended version. Accepted by USENIX Security 2024
null
null
null
cs.CR cs.NI cs.SE
http://creativecommons.org/licenses/by-nc-nd/4.0/
Domain Name System (DNS) is a critical component of the Internet. DNS resolvers, which act as the cache between DNS clients and DNS nameservers, are the central piece of the DNS infrastructure, essential to the scalability of DNS. However, finding the resolver vulnerabilities is non-trivial, and this problem is not w...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 23:17:32 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhang", "Qifan", "" ], [ "Bai", "Xuesong", "" ], [ "Li", "Xiang", "" ], [ "Duan", "Haixin", "" ], [ "Li", "Qi", "" ], [ "Li", "Zhou", "" ] ]
not_new_dataset
0.997339
2310.03205
Kim Youwang
Kim Youwang and Lee Hyun and Kim Sung-Bin and Suekyeong Nam and Janghoon Ju and Tae-Hyun Oh
A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization
9 pages, 7 figures, and 3 tables for the main paper. 8 pages, 6 figures and 3 tables for the appendix
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose NeuFace, a 3D face mesh pseudo annotation method on videos via neural re-parameterized optimization. Despite the huge progress in 3D face reconstruction methods, generating reliable 3D face labels for in-the-wild dynamic videos remains challenging. Using NeuFace optimization, we annotate the per-view/-fram...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 23:24:22 GMT" } ]
2023-10-06T00:00:00
[ [ "Youwang", "Kim", "" ], [ "Hyun", "Lee", "" ], [ "Sung-Bin", "Kim", "" ], [ "Nam", "Suekyeong", "" ], [ "Ju", "Janghoon", "" ], [ "Oh", "Tae-Hyun", "" ] ]
new_dataset
0.99799
2310.03210
Erfan Al-Hossami
Erfan Al-Hossami, Razvan Bunescu, Justin Smith, Ryan Teehan
Can Language Models Employ the Socratic Method? Experiments with Code Debugging
8 pages, 2 tables. To be published in Proceedings of the 2024 Technical Symposium on Computer Science Education (SIGCSE'24)
null
null
null
cs.CL cs.CY
http://creativecommons.org/licenses/by/4.0/
When employing the Socratic method of teaching, instructors guide students toward solving a problem on their own rather than providing the solution directly. While this strategy can substantially improve learning outcomes, it is usually time-consuming and cognitively demanding. Automated Socratic conversational agent...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 23:32:33 GMT" } ]
2023-10-06T00:00:00
[ [ "Al-Hossami", "Erfan", "" ], [ "Bunescu", "Razvan", "" ], [ "Smith", "Justin", "" ], [ "Teehan", "Ryan", "" ] ]
new_dataset
0.981184
2310.03211
Utsav Garg
Utsav Garg, Erhan Bas
On the Performance of Multimodal Language Models
null
null
null
null
cs.CL cs.AI cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
Instruction-tuned large language models (LLMs) have demonstrated promising zero-shot generalization capabilities across various downstream tasks. Recent research has introduced multimodal capabilities to LLMs by integrating independently pretrained vision encoders through model grafting. These multimodal variants und...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 23:33:36 GMT" } ]
2023-10-06T00:00:00
[ [ "Garg", "Utsav", "" ], [ "Bas", "Erhan", "" ] ]
not_new_dataset
0.997463
2310.03212
Samaneh Javadinia
Samaneh Javadinia, Amirali Baniasadi
PDR-CapsNet: an Energy-Efficient Parallel Approach to Dynamic Routing in Capsule Networks
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Convolutional Neural Networks (CNNs) have produced state-of-the-art results for image classification tasks. However, they are limited in their ability to handle rotational and viewpoint variations due to information loss in max-pooling layers. Capsule Networks (CapsNets) employ a computationally-expensive iterative p...
[ { "version": "v1", "created": "Wed, 4 Oct 2023 23:38:09 GMT" } ]
2023-10-06T00:00:00
[ [ "Javadinia", "Samaneh", "" ], [ "Baniasadi", "Amirali", "" ] ]
not_new_dataset
0.99732
2310.03214
Tu Vu
Tu Vu, Mohit Iyyer, Xuezhi Wang, Noah Constant, Jerry Wei, Jason Wei, Chris Tar, Yun-Hsuan Sung, Denny Zhou, Quoc Le, Thang Luong
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation
Preprint, 22 pages, 7 figures, 5 tables
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most large language models (LLMs) are trained once and never updated; thus, they lack the ability to dynamically adapt to our ever-changing world. In this work, we perform a detailed study of the factuality of LLM-generated text in the context of answering questions that test current world knowledge. Specifically, we...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:04:12 GMT" } ]
2023-10-06T00:00:00
[ [ "Vu", "Tu", "" ], [ "Iyyer", "Mohit", "" ], [ "Wang", "Xuezhi", "" ], [ "Constant", "Noah", "" ], [ "Wei", "Jerry", "" ], [ "Wei", "Jason", "" ], [ "Tar", "Chris", "" ], [ "Sung", "Yun-Hsuan", ...
new_dataset
0.735618
2310.03217
Robert Moss
Jean-Guillaume Durand, Arthur Dubois, Robert J. Moss
Formal and Practical Elements for the Certification of Machine Learning Systems
Best of Conference at the 2023 Digital Avionics Systems Conference (DASC)
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Over the past decade, machine learning has demonstrated impressive results, often surpassing human capabilities in sensing tasks relevant to autonomous flight. Unlike traditional aerospace software, the parameters of machine learning models are not hand-coded nor derived from physics but learned from data. They are a...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:20:59 GMT" } ]
2023-10-06T00:00:00
[ [ "Durand", "Jean-Guillaume", "" ], [ "Dubois", "Arthur", "" ], [ "Moss", "Robert J.", "" ] ]
not_new_dataset
0.997407
2310.03218
Peiyu Yu
Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
Learning Energy-Based Prior Model with Diffusion-Amortized MCMC
NeurIPS 2023
null
null
null
cs.LG cs.AI stat.ML
http://creativecommons.org/licenses/by-sa/4.0/
Latent space Energy-Based Models (EBMs), also known as energy-based priors, have drawn growing interests in the field of generative modeling due to its flexibility in the formulation and strong modeling power of the latent space. However, the common practice of learning latent space EBMs with non-convergent short-run...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:23:34 GMT" } ]
2023-10-06T00:00:00
[ [ "Yu", "Peiyu", "" ], [ "Zhu", "Yaxuan", "" ], [ "Xie", "Sirui", "" ], [ "Ma", "Xiaojian", "" ], [ "Gao", "Ruiqi", "" ], [ "Zhu", "Song-Chun", "" ], [ "Wu", "Ying Nian", "" ] ]
not_new_dataset
0.997477
2310.03221
Yijia Xiao
Yijia Xiao, Dylan Steinecke, Alexander Russell Pelletier, Yushi Bai, Peipei Ping, Wei Wang
Know2BIO: A Comprehensive Dual-View Benchmark for Evolving Biomedical Knowledge Graphs
26 pages, 2 figures, 14 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge graphs (KGs) have emerged as a powerful framework for representing and integrating complex biomedical information. However, assembling KGs from diverse sources remains a significant challenge in several aspects, including entity alignment, scalability, and the need for continuous updates to keep pace with s...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:34:56 GMT" } ]
2023-10-06T00:00:00
[ [ "Xiao", "Yijia", "" ], [ "Steinecke", "Dylan", "" ], [ "Pelletier", "Alexander Russell", "" ], [ "Bai", "Yushi", "" ], [ "Ping", "Peipei", "" ], [ "Wang", "Wei", "" ] ]
new_dataset
0.997773
2310.03222
Alan Frieze
Alan Frieze, Wesley Pegden
The bright side of simple heuristics for the TSP
null
null
null
null
cs.DM cs.CG math.CO
http://creativecommons.org/licenses/by/4.0/
The greedy and nearest-neighbor TSP heuristics can both have $\log n$ approximation factors from optimal in worst case, even just for $n$ points in Euclidean space. In this note, we show that this approximation factor is only realized when the optimal tour is unusually short. In particular, for points from any fixed ...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:44:18 GMT" } ]
2023-10-06T00:00:00
[ [ "Frieze", "Alan", "" ], [ "Pegden", "Wesley", "" ] ]
not_new_dataset
0.997054
2310.03223
Tongzhou Shen
Tony Shen, Mohit Pandey and Martin Ester
TacoGFN: Target Conditioned GFlowNet for Structure-Based Drug Design
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
We seek to automate the generation of drug-like compounds conditioned to specific protein pocket targets. Most current methods approximate the protein-molecule distribution of a finite dataset and, therefore struggle to generate molecules with significant binding improvement over the training dataset. We instead fram...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:45:04 GMT" } ]
2023-10-06T00:00:00
[ [ "Shen", "Tony", "" ], [ "Pandey", "Mohit", "" ], [ "Ester", "Martin", "" ] ]
not_new_dataset
0.997149
2310.03224
Arian Eamaz
Arian Eamaz, Farhang Yeganegi, and Mojtaba Soltanalian
Matrix Completion from One-Bit Dither Samples
null
null
null
null
cs.IT eess.SP math.IT
http://creativecommons.org/licenses/by/4.0/
We explore the impact of coarse quantization on matrix completion in the extreme scenario of dithered one-bit sensing, where the matrix entries are compared with time-varying threshold levels. In particular, instead of observing a subset of high-resolution entries of a low-rank matrix, we have access to a small numbe...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:46:25 GMT" } ]
2023-10-06T00:00:00
[ [ "Eamaz", "Arian", "" ], [ "Yeganegi", "Farhang", "" ], [ "Soltanalian", "Mojtaba", "" ] ]
not_new_dataset
0.997441
2310.03225
Akifumi Wachi
Akifumi Wachi, Wataru Hashimoto, Xun Shen, Kazumune Hashimoto
Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms
Accepted to NeurIPS 2023
null
null
null
cs.LG cs.AI cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Safe exploration is essential for the practical use of reinforcement learning (RL) in many real-world scenarios. In this paper, we present a generalized safe exploration (GSE) problem as a unified formulation of common safe exploration problems. We then propose a solution of the GSE problem in the form of a meta-algo...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:47:09 GMT" } ]
2023-10-06T00:00:00
[ [ "Wachi", "Akifumi", "" ], [ "Hashimoto", "Wataru", "" ], [ "Shen", "Xun", "" ], [ "Hashimoto", "Kazumune", "" ] ]
not_new_dataset
0.997418
2310.03228
Su Jiang
Su Jiang, Louis J. Durlofsky
History Matching for Geological Carbon Storage using Data-Space Inversion with Spatio-Temporal Data Parameterization
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
History matching based on monitoring data will enable uncertainty reduction, and thus improved aquifer management, in industrial-scale carbon storage operations. In traditional model-based data assimilation, geomodel parameters are modified to force agreement between flow simulation results and observations. In data-...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:50:06 GMT" } ]
2023-10-06T00:00:00
[ [ "Jiang", "Su", "" ], [ "Durlofsky", "Louis J.", "" ] ]
not_new_dataset
0.99727
2310.03232
Xinyang Ren
Xinyang Ren, Hannah A Burkhardt, Patricia A Are\'an, Thomas D Hull, Trevor Cohen
Deep Representations of First-person Pronouns for Prediction of Depression Symptom Severity
Accepted: AMIA Annual Symposium 2023. To appear as: Ren X, Burkhardt H, Are\'an P, Hull T, Cohen T. Deep Representations of First-person Pronouns for Prediction of Depression Symptom Severity. AMIA Annual Symposium Proceedings 2023. American Medical Informatics Association
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Prior work has shown that analyzing the use of first-person singular pronouns can provide insight into individuals' mental status, especially depression symptom severity. These findings were generated by counting frequencies of first-person singular pronouns in text data. However, counting doesn't capture how these p...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 00:55:46 GMT" } ]
2023-10-06T00:00:00
[ [ "Ren", "Xinyang", "" ], [ "Burkhardt", "Hannah A", "" ], [ "Areán", "Patricia A", "" ], [ "Hull", "Thomas D", "" ], [ "Cohen", "Trevor", "" ] ]
not_new_dataset
0.997314
2310.03237
Hayyu Imanda
Hayyu Imanda and Kasper Rasmussen
Ask for Alice: Online Covert Distress Signal in the Presence of a Strong Adversary
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we propose a protocol that can be used to covertly send a distress signal through a seemingly normal webserver, even if the adversary is monitoring both the network and the user's device. This allows a user to call for help even when they are in the same physical space as their adversaries. We model suc...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 01:07:06 GMT" } ]
2023-10-06T00:00:00
[ [ "Imanda", "Hayyu", "" ], [ "Rasmussen", "Kasper", "" ] ]
not_new_dataset
0.99727
2310.03239
Aravind Sivaramakrishnan
Aravind Sivaramakrishnan, Noah R. Carver, Sumanth Tangirala, Kostas E. Bekris
Roadmaps with Gaps over Controllers: Achieving Efficiency in Planning under Dynamics
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper aims to improve the computational efficiency of motion planning for mobile robots with non-trivial dynamics by taking advantage of learned controllers. It adopts a decoupled strategy, where a system-specific controller is first trained offline in an empty environment to deal with the system's dynamics. For...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 01:21:33 GMT" } ]
2023-10-06T00:00:00
[ [ "Sivaramakrishnan", "Aravind", "" ], [ "Carver", "Noah R.", "" ], [ "Tangirala", "Sumanth", "" ], [ "Bekris", "Kostas E.", "" ] ]
not_new_dataset
0.997332
2310.03240
Awni Altabaa
Awni Altabaa, John Lafferty
Relational Convolutional Networks: A framework for learning representations of hierarchical relations
18 pages, 7 figures, 4 tables
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
A maturing area of research in deep learning is the development of architectures that can learn explicit representations of relational features. In this paper, we focus on the problem of learning representations of hierarchical relations, proposing an architectural framework we call "relational convolutional networks...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 01:22:50 GMT" } ]
2023-10-06T00:00:00
[ [ "Altabaa", "Awni", "" ], [ "Lafferty", "John", "" ] ]
not_new_dataset
0.997449
2310.03246
Aravind Sivaramakrishnan
Ewerton R. Vieira, Aravind Sivaramakrishnan, Sumanth Tangirala, Edgar Granados, Konstantin Mischaikow, Kostas E. Bekris
${\tt MORALS}$: Analysis of High-Dimensional Robot Controllers via Topological Tools in a Latent Space
The first two authors contributed equally to this paper
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Estimating the region of attraction (${\tt RoA}$) for a robotic system's controller is essential for safe application and controller composition. Many existing methods require access to a closed-form expression that limit applicability to data-driven controllers. Methods that operate only over trajectory rollouts ten...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 01:31:45 GMT" } ]
2023-10-06T00:00:00
[ [ "Vieira", "Ewerton R.", "" ], [ "Sivaramakrishnan", "Aravind", "" ], [ "Tangirala", "Sumanth", "" ], [ "Granados", "Edgar", "" ], [ "Mischaikow", "Konstantin", "" ], [ "Bekris", "Kostas E.", "" ] ]
not_new_dataset
0.99743
2310.03248
Siavash Hosseini
Siavash Hosseini
Xcrum: A Synergistic Approach Integrating Extreme Programming with Scrum
null
null
null
null
cs.SE
http://creativecommons.org/licenses/by-nc-sa/4.0/
In today's modern world, software plays a pivotal role. Software development is a highly complex and time-consuming process, demanding multidimensional efforts. Companies continually adapt their requirements to align with the evolving environment, with a specific emphasis on rapid delivery and the acceptance of chang...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 01:39:10 GMT" } ]
2023-10-06T00:00:00
[ [ "Hosseini", "Siavash", "" ] ]
not_new_dataset
0.997476
2310.03249
Mohamed Aghzal
Mohamed Aghzal, Erion Plaku, Ziyu Yao
Can Large Language Models be Good Path Planners? A Benchmark and Investigation on Spatial-temporal Reasoning
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Large language models (LLMs) have achieved remarkable success across a wide spectrum of tasks; however, they still face limitations in scenarios that demand long-term planning and spatial reasoning. To facilitate this line of research, in this work, we propose a new benchmark, termed $\textbf{P}$ath $\textbf{P}$lanni...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 01:42:16 GMT" } ]
2023-10-06T00:00:00
[ [ "Aghzal", "Mohamed", "" ], [ "Plaku", "Erion", "" ], [ "Yao", "Ziyu", "" ] ]
new_dataset
0.949306
2310.03251
Sumit Bam Shrestha
Sumit Bam Shrestha, Jonathan Timcheck, Paxon Frady, Leobardo Campos-Macias, Mike Davies
Efficient Video and Audio processing with Loihi 2
5 pages, 3 figures
null
null
null
cs.NE cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Loihi 2 is an asynchronous, brain-inspired research processor that generalizes several fundamental elements of neuromorphic architecture, such as stateful neuron models communicating with event-driven spikes, in order to address limitations of the first generation Loihi. Here we explore and characterize some of these...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 01:56:03 GMT" } ]
2023-10-06T00:00:00
[ [ "Shrestha", "Sumit Bam", "" ], [ "Timcheck", "Jonathan", "" ], [ "Frady", "Paxon", "" ], [ "Campos-Macias", "Leobardo", "" ], [ "Davies", "Mike", "" ] ]
not_new_dataset
0.997393
2310.03252
Edgar Pacheco Dr
Edgar Pacheco
Exploring age-related patterns in internet access: Insights from a secondary analysis of New Zealand survey data
15 pages, 5 tables
null
null
null
cs.CY
http://creativecommons.org/licenses/by-nc-sa/4.0/
For over two decades Internet access has been a topic of research and debate. Up-to-date evidence about key predictors such as age is important considering not only the complexities of access to the online medium but also the ever-changing nature of the Internet. This paper attempts to provide a stocktake of current ...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 02:03:28 GMT" } ]
2023-10-06T00:00:00
[ [ "Pacheco", "Edgar", "" ] ]
not_new_dataset
0.997425
2310.03253
Kong Deqian
Deqian Kong, Yuhao Huang, Jianwen Xie, Ying Nian Wu
Molecule Design by Latent Prompt Transformer
null
null
null
null
cs.LG q-bio.BM stat.ML
http://creativecommons.org/licenses/by/4.0/
This paper proposes a latent prompt Transformer model for solving challenging optimization problems such as molecule design, where the goal is to find molecules with optimal values of a target chemical or biological property that can be computed by an existing software. Our proposed model consists of three components...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 02:09:51 GMT" } ]
2023-10-06T00:00:00
[ [ "Kong", "Deqian", "" ], [ "Huang", "Yuhao", "" ], [ "Xie", "Jianwen", "" ], [ "Wu", "Ying Nian", "" ] ]
not_new_dataset
0.997018
2310.03254
Unchitta Kan
Unchitta Kan, Jericho McLeod, Eduardo L\'opez
Non-coresident family as a driver of migration change in a crisis: The case of the COVID-19 pandemic
19 pages, 3 figures
null
null
null
cs.SI physics.soc-ph
http://creativecommons.org/licenses/by-sa/4.0/
Changes in U.S. migration trends during the COVID-19 pandemic show that many moved to less populated cities from larger cities, deviating from previous trends. In this study, building on prior work in the literature showing that the abundance of family ties are inversely related to population size, we analyze these m...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 02:11:25 GMT" } ]
2023-10-06T00:00:00
[ [ "Kan", "Unchitta", "" ], [ "McLeod", "Jericho", "" ], [ "López", "Eduardo", "" ] ]
not_new_dataset
0.997415
2310.03256
Abdelhak Bentaleb Dr
Abdelhak Bentaleb, May Lim, Mehmet N. Akcay, Ali C. Begen, Sarra Hammoudi, Roger Zimmermann
Toward One-Second Latency: Evolution of Live Media Streaming
null
null
null
null
cs.NI cs.MM
http://creativecommons.org/licenses/by/4.0/
This survey presents the evolution of live media streaming and the technological developments behind today's IP-based low-latency live streaming systems. Live streaming primarily involves capturing, encoding, packaging and delivering real-time events such as live sports, live news, personal broadcasts and surveillanc...
[ { "version": "v1", "created": "Thu, 5 Oct 2023 02:18:55 GMT" } ]
2023-10-06T00:00:00
[ [ "Bentaleb", "Abdelhak", "" ], [ "Lim", "May", "" ], [ "Akcay", "Mehmet N.", "" ], [ "Begen", "Ali C.", "" ], [ "Hammoudi", "Sarra", "" ], [ "Zimmermann", "Roger", "" ] ]
not_new_dataset
0.997447