Most Cited 2024 "cognitive reasoning" Papers
12,324 papers found • Page 62 of 62
Conference
How connectivity structure shapes rich and lazy learning in neural circuits
Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford et al.
ARGS: Alignment as Reward-Guided Search
Maxim Khanov, Jirayu Burapacheep, Yixuan Li
Let Models Speak Ciphers: Multiagent Debate through Embeddings
Chau Pham, Boyi Liu, Yingxiang Yang et al.
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
Wenxi Wang, Yang Hu, Mohit Tiwari et al.
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates
Nicholas Corrado, Josiah Hanna
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation
Tien Manh Luong, Khai Nguyen, Nhat Ho et al.
Text-to-3D with Classifier Score Distillation
Xin Yu, Yuan-Chen Guo, Yangguang Li et al.
Transformers can optimally learn regression mixture models
Reese Pathak, Rajat Sen, Weihao Kong et al.
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
HeeSun Bae, Seungjae Shin, Byeonghu Na et al.
Branch-GAN: Improving Text Generation with (not so) Large Language Models
Fredrik Carlsson, Johan Broberg, Erik Hillbom et al.
SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series
Junyan Cheng, Peter Chin
A unique M-pattern for micro-expression spotting in long videos
Jinxuan Wang, Shiting Xu, Tong Zhang
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning
Yun-Hin Chan, Rui Zhou, Running Zhao et al.
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
Yong Liu, Tengge Hu, Haoran Zhang et al.
A Mutual Information Perspective on Federated Contrastive Learning
Christos Louizos, Matthias Reisser, Denis Korzhenkov
Local Graph Clustering with Noisy Labels
Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang
DistillSpec: Improving Speculative Decoding via Knowledge Distillation
Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat et al.
Faithful Vision-Language Interpretation via Concept Bottleneck Models
Songning Lai, Lijie Hu, Junxiao Wang et al.
Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets
Yihuan Mao, Chengjie Wu, Xi Chen et al.
Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits
Qiwei Di, Tao Jin, Yue Wu et al.
Demystifying Embedding Spaces using Large Language Models
Guy Tennenholtz, Yinlam Chow, ChihWei Hsu et al.
A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines
Manju Garimella, Denizhan Pak, Justin Wood et al.
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training
AOCHUAN CHEN, Yimeng Zhang, Jinghan Jia et al.
Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View.
Raj Ghugare, Matthieu Geist, Glen Berseth et al.
Unveiling the Pitfalls of Knowledge Editing for Large Language Models
Zhoubo Li, Ningyu Zhang, Yunzhi Yao et al.
Learning Thresholds with Latent Values and Censored Feedback
Jiahao Zhang, Tao Lin, Weiqiang Zheng et al.
Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World
Chunshu Wu, Ruibing Song, Chuan Liu et al.
Robustifying and Boosting Training-Free Neural Architecture Search
Zhenfeng He, Yao Shu, Zhongxiang Dai et al.
Guess & Sketch: Language Model Guided Transpilation
Celine Lee, Abdulrahman Mahmoud, Michal Kurek et al.
Zero and Few-shot Semantic Parsing with Ambiguous Inputs
Elias Stengel-Eskin, Kyle Rawlins, Benjamin Van Durme
Large-Vocabulary 3D Diffusion Model with Transformer
Ziang Cao, Fangzhou Hong, Tong Wu et al.
An Investigation of Representation and Allocation Harms in Contrastive Learning
Subha Maity, Mayank Agarwal, Mikhail Yurochkin et al.
Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Yujia Bao, Srinivasan Sivanandan, THEOFANIS KARALETSOS
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
Shikai Fang, Madison Cooley, Da Long et al.
Adversarial Attacks on Fairness of Graph Neural Networks
Binchi Zhang, Yushun Dong, Chen Chen et al.
Task structure and nonlinearity jointly determine learned representational geometry
Matteo Alleman, Jack Lindsey, Stefano Fusi
ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models
Iman Mirzadeh, Keivan Alizadeh-Vahid, Sachin Mehta et al.
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang et al.
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy
Yingyu Lin, Yian Ma, Yu-Xiang Wang et al.
Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models
Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh
Graph Transformers on EHRs: Better Representation Improves Downstream Performance
Raphael Poulain, Rahmatollah Beheshti
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Ning Miao, Yee Whye Teh, Tom Rainforth
Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing
Minyang Hu, Hong Chang, Bingpeng Ma et al.
Improved Regret Bounds for Non-Convex Online-Within-Online Meta Learning
Jiechao GUAN, Hui Xiong
Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
Jonghyun Lee, Hansam Cho, YoungJoon Yoo et al.
Recursive Generalization Transformer for Image Super-Resolution
Zheng Chen, Yulun Zhang, Jinjin Gu et al.
Score Models for Offline Goal-Conditioned Reinforcement Learning
Harshit Sikchi, Rohan Chitnis, Ahmed Touati et al.
Treatment Effects Estimation By Uniform Transformer
Ruoqi Yu, Shulei Wang
Representation Deficiency in Masked Language Modeling
Yu Meng, Jitin Krishnan, Sinong Wang et al.
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
Frederic Koehler, Thuy-Duong Vuong
MaGIC: Multi-modality Guided Image Completion
Hao Wang, Yongsheng Yu, Tiejian Luo et al.
Learning Robust Generalizable Radiance Field with Visibility and Feature Augmented Point Representation
Jiaxu Wang, Ziyi Zhang, Renjing Xu
HoloNets: Spectral Convolutions do extend to Directed Graphs
Christian Koke, Daniel Cremers
Searching for High-Value Molecules Using Reinforcement Learning and Transformers
Raj Ghugare, Santiago Miret, Adriana Hugessen et al.
Interpretable Meta-Learning of Physical Systems
Matthieu Blanke, marc lelarge
An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models
Haochen Luo, Jindong Gu, Fengyuan Liu et al.
Fast Value Tracking for Deep Reinforcement Learning
Frank Shih, Faming Liang
Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction
Liu Xiaoyi, Duxin Chen, Wenjia Wei et al.
FedInverse: Evaluating Privacy Leakage in Federated Learning
DI WU, Jun Bai, Yiliao Song et al.
CircuitNet 2.0: An Advanced Dataset for Promoting Machine Learning Innovations in Realistic Chip Design Environment
Xun Jiang, zhuomin chai, Yuxiang Zhao et al.
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
Tokio Kajitsuka, Issei Sato
Self-Supervised Contrastive Learning for Long-term Forecasting
Junwoo Park, Daehoon Gwak, Jaegul Choo et al.
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning
Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya Ezzeldin et al.
Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization
Yibing Liu, Chris Xing TIAN, Haoliang Li et al.
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou et al.
Rethinking CNN’s Generalization to Backdoor Attack from Frequency Domain
Quanrui Rao, Lin Wang, Wuying Liu
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions
Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas
Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation
Zhilong Zhang, Yihao Sun, Junyin Ye et al.
LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts
Hanan Gani, Shariq Bhat, Muzammal Naseer et al.
VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition
Chenyu Liu, XINLIANG ZHOU, Zhengri Zhu et al.
Neural Rate Control for Learned Video Compression
yiwei zhang, Guo Lu, Yunuo Chen et al.
PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
Xuan Ju, Ailing Zeng, Yuxuan Bian et al.
Harnessing Density Ratios for Online Reinforcement Learning
Philip Amortila, Dylan Foster, Nan Jiang et al.
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method
yuyan ni, Shikun Feng, Wei-Ying Ma et al.
Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling
Jiayang Liu, Yiming Bu, Daniel Tso et al.
Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection
Jiawei Liang, Siyuan Liang, Aishan Liu et al.
Negatively Correlated Ensemble Reinforcement Learning for Online Diverse Game Level Generation
Ziqi Wang, Chengpeng Hu, Jialin Liu et al.
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning
Zhaoyi Zhou, Chuning Zhu, Runlong Zhou et al.
Local Composite Saddle Point Optimization
Site Bai, Brian Bullins
ASID: Active Exploration for System Identification in Robotic Manipulation
Marius Memmel, Andrew Wagenmaker, Chuning Zhu et al.
Simple Hierarchical Planning with Diffusion
Chang Chen, Fei Deng, Kenji Kawaguchi et al.
sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows
Dongjin Kim, Donggoo Jung, Sungyong Baik et al.
Improving Generalization of Alignment with Human Preferences through Group Invariant Learning
Rui Zheng, Wei Shen, Yuan Hua et al.
Dynamic Sparse Training with Structured Sparsity
Mike Lasby, Anna Golubeva, Utku Evci et al.
DENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING
Shitong Duan, Xiaoyuan Yi, Peng Zhang et al.
Robustifying State-space Models for Long Sequences via Approximate Diagonalization
Annan Yu, Arnur Nigmetov, Dmitriy Morozov et al.
Generative Adversarial Equilibrium Solvers
Denizalp Goktas, David Parkes, Ian Gemp et al.
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models
Shuai Zhao, Xiaohan Wang, Linchao Zhu et al.
FedImpro: Measuring and Improving Client Update in Federated Learning
Zhenheng Tang, Yonggang Zhang, Shaohuai Shi et al.
Improving LoRA in Privacy-preserving Federated Learning
Youbang Sun, Zitao Li, Yaliang Li et al.
Efficient Inverse Multiagent Learning
Denizalp Goktas, Amy Greenwald, Sadie Zhao et al.
Neural Neighborhood Search for Multi-agent Path Finding
Zhongxia Yan, Cathy Wu
Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models
Shuai Fu, Shuai Fu, Xiequn Wang et al.
FasterViT: Fast Vision Transformers with Hierarchical Attention
Ali Hatamizadeh, Greg Heinrich, Hongxu Yin et al.
C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee et al.
DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
Jingxiang Sun, Bo Zhang, Ruizhi Shao et al.
Plugin estimators for selective classification with out-of-distribution detection
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum et al.
P$^2$OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering
Chuyu Zhang, Hui Ren, Xuming He
Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning
Feiyang YE, YUEMING LYU, Xuehao Wang et al.
Intriguing Properties of Data Attribution on Diffusion Models
Xiaosen Zheng, Tianyu Pang, Chao Du et al.
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
Xuefeng Du, Zhen Fang, Ilias Diakonikolas et al.
GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks
Renat Sergazinov, Elizabeth Chun, Valeriya Rogovchenko et al.
Look, Remember and Reason: Grounded Reasoning in Videos with Language Models
Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza et al.
Pushing Boundaries: Mixup's Influence on Neural Collapse
Quinn Fisher, Haoming Meng, Vardan Papyan
LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer
Guangyi Chen, Yuke Li, Xiao Liu et al.
Implicit regularization of deep residual networks towards neural ODEs
Pierre Marion, Yu-Han Wu, Michael Sander et al.
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
Ruiquan Huang, Yingbin Liang, Jing Yang
Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models
Shikun Sun, Longhui Wei, Zhicai Wang et al.
Compressing Latent Space via Least Volume
Qiuyi Chen, Mark Fuge
CoLiDE: Concomitant Linear DAG Estimation
Seyed Saman Saboksayr, Gonzalo Mateos, Mariano Tepper
Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory
Yiting Chen, Zhanpeng Zhou, Junchi Yan
A Unified Framework for Bayesian Optimization under Contextual Uncertainty
Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano et al.
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG
Jonas Seng, Matej Zečević, Devendra Singh Dhami et al.
Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization
Joe Benton, Valentin De Bortoli, Arnaud Doucet et al.
Active Retrosynthetic Planning Aware of Route Quality
Luotian Yuan, Yemin Yu, Ying Wei et al.
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
Bowen Song, Soo Min Kwon, Zecheng Zhang et al.
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
Yinan Zheng, Jianxiong Li, Dongjie Yu et al.
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy
Pingzhi Li, Zhenyu Zhang, Prateek Yadav et al.
Non-Exchangeable Conformal Risk Control
António Farinhas, Chrysoula Zerva, Dennis Ulmer et al.
Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM
Eliya Nachmani, Alon Levkovitch, Roy Hirsch et al.
USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields
Moyang Li, Peng Wang, Lingzhe Zhao et al.
Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations
yisheng xiao, Juntao Li, Zechen Sun et al.
Synergistic Patch Pruning for Vision Transformer: Unifying Intra- & Inter-Layer Patch Importance
Yuyao Zhang, Lan Wei, Nikolaos Freris
Early Stopping Against Label Noise Without Validation Data
Suqin Yuan, Lei Feng, Tongliang Liu