Most Cited ICML "cross-embodiment learning" Papers
5,975 papers found • Page 20 of 30
Conference
Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation
Guorui Quan, Zhiqiang Xu, Guiliang Liu
Multiply-Robust Causal Change Attribution
Víctor Quintas-Martínez, Mohammad Bahadori, Eduardo Santiago et al.
Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks
Rahul Ramesh, Ekdeep Singh Lubana, Mikail Khona et al.
Dissecting Multimodality in VideoQA Transformer Models by Impairing Modality Fusion
Ishaan Rawal, Alexander Matyasko, Shantanu Jaiswal et al.
Rejuvenating image-GPT as Strong Visual Representation Learners
Sucheng Ren, Zeyu Wang, Hongru Zhu et al.
CarbonNovo: Joint Design of Protein Structure and Sequence Using a Unified Energy-based Model
Milong Ren, Tian Zhu, Haicang Zhang
Plug-and-Play image restoration with Stochastic deNOising REgularization
Marien Renaud, Jean Prost, Arthur Leclaire et al.
Universal Gradient Methods for Stochastic Convex Optimization
Anton Rodomanov, Ali Kavis, Yongtao Wu et al.
Position: Key Claims in LLM Research Have a Long Tail of Footnotes
Anna Rogers, Sasha Luccioni
Position: Amazing Things Come From Having Many Good Models
Cynthia Rudin, Chudi Zhong, Lesia Semenova et al.
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
Sudeep Salgia, Sattar Vakili, Qing Zhao
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
Sebastian Sanokowski, Sepp Hochreiter, Sebastian Lehner
A sampling theory perspective on activations for implicit neural representations
Hemanth Saratchandran, Sameera Ramasinghe, Violetta Shevchenko et al.
Incentivized Learning in Principal-Agent Bandit Games
Antoine Scheid, Daniil Tiapkin, Etienne Boursier et al.
Online Learning with Bounded Recall
Jon Schneider, Kiran Vodrahalli
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
Nabeel Seedat, Nicolas Huynh, Boris van Breugel et al.
Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models
Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar et al.
Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models
Amrith Setlur, Saurabh Garg, Virginia Smith et al.
The Balanced-Pairwise-Affinities Feature Transform
Daniel Shalam, Simon Korman
Improved Generalization of Weight Space Networks via Augmentations
Aviv Shamsian, Aviv Navon, David Zhang et al.
On Multi-Armed Bandit with Impatient Arms
Yuming Shao, Zhixuan Fang
Learning Decision Policies with Instrumental Variables through Double Machine Learning
Bill Daqian Shao, Ashkan Soleymani, Francesco Quinzan et al.
How Far Can Fairness Constraints Help Recover From Biased Data?
Mohit Sharma, Amit Jayant Deshpande
Position: Do pretrained Transformers Learn In-Context by Gradient Descent?
Lingfeng Shen, Aayush Mishra, Daniel Khashabi
Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning
Jin Hwa Lee, Stefano Mannelli, Andrew Saxe
LCA-on-the-Line: Benchmarking Out of Distribution Generalization with Class Taxonomies
Jia Shi, Gautam Rajendrakumar Gare, Jinjin Tian et al.
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
Jiang-Xin Shi, Tong Wei, Zhi Zhou et al.
Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation
Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee et al.
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation
Jacob Si, Wendy Yusi Cheng, Michael Cooper et al.
Deletion-Anticipative Data Selection with a Limited Budget
Rachael Hwee Ling Sim, Jue Fan, Xiao Tian et al.
Latent variable model for high-dimensional point process with structured missingness
Maksim Sinelnikov, Manuel Haussmann, Harri Lähdesmäki
Domain Generalisation via Imprecise Learning
Anurag Singh, Siu Lun Chau, Shahine Bouabid et al.
Byzantine Resilient and Fast Federated Few-Shot Learning
Ankit Pratap Singh, Namrata Vaswani
Parallelized Spatiotemporal Slot Binding for Videos
Gautam Singh, Yue Wang, Jiawei Yang et al.
In-Context Reinforcement Learning for Variable Action Spaces
Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov et al.
Probabilistic Modeling of Interpersonal Coordination Processes
Paulo Soares, Adarsh Pyarelal, Meghavarshini Krishnaswamy et al.
SurfPro: Functional Protein Design Based on Continuous Surface
Zhenqiao Song, Tinglin Huang, Lei Li et al.
OSN: Infinite Representations of Dynamic 3D Scenes from Monocular Videos
Ziyang Song, Jinxi Li, Bo Yang
Sparse is Enough in Fine-tuning Pre-trained Large Language Models
Weixi Song, Zuchao Li, Lefei Zhang et al.
Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates
Zhenqiao Song, Yunlong Zhao, Wenxian Shi et al.
Position: A Roadmap to Pluralistic Alignment
Taylor Sorensen, Jared Moore, Jillian Fisher et al.
Learning to Intervene on Concept Bottlenecks
David Steinmann, Wolfgang Stammer, Felix Friedrich et al.
ReGAL: Refactoring Programs to Discover Generalizable Abstractions
Elias Stengel-Eskin, Archiki Prasad, Mohit Bansal
RLVF: Learning from Verbal Feedback without Overgeneralization
Moritz Stephan, Alexander Khazatsky, Eric Mitchell et al.
Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration via Shift Reduction Lemmas
Clément Pierquin, Aurélien Bellet, Marc Tommasi et al.
Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction
Arjun Subramonian, Levent Sagun, Yizhou Sun
ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance
Liwen Sun, Abhineet Agarwal, Aaron Kornblith et al.
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering
Li Sun, Zhenhao Huang, Hao Peng et al.
Graph Neural Networks with a Distribution of Parametrized Graphs
See Hian Lee, Feng Ji, Kelin Xia et al.
BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models
Haotian Sun, Yuchen Zhuang, Wei Wei et al.
Community-Invariant Graph Contrastive Learning
Shiyin Tan, Dongyuan Li, Renhe Jiang et al.
Post-hoc Part-Prototype Networks
Andong Tan, Fengtao ZHOU, Hao Chen
Rethinking Optimization and Architecture for Tiny Language Models
Yehui Tang, Kai Han, Fangcheng Liu et al.
StrokeNUWA—Tokenizing Strokes for Vector Graphic Synthesis
Zecheng Tang, Chenfei Wu, Zekai Zhang et al.
SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification
Yehui Tang, Nianzu Yang, Mabiao Long et al.
MathScale: Scaling Instruction Tuning for Mathematical Reasoning
Zhengyang Tang, Xingxing Zhang, Benyou Wang et al.
QUEST: Query-Aware Sparsity for Efficient Long-Context LLM Inference
Jiaming Tang, Yilong Zhao, Kan Zhu et al.
Copula-Nested Spectral Kernel Network
Jinyue Tian, Hui Xue, Yanfang Xue et al.
FRAPPÉ: A Group Fairness Framework for Post-Processing Everything
Alexandru Tifrea, Preethi Lahoti, Ben Packer et al.
Faster Maximum Inner Product Search in High Dimensions
Mo Tiwari, Ryan Kang, Jaeyong Lee et al.
How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model
Umberto Tomasini, Matthieu Wyart
Position: Do Not Explain Vision Models Without Context
Paulina Tomaszewska, Przemyslaw Biecek
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics
Artur Toshev, Jonas Erbesdobler, Nikolaus Adams et al.
Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments
Allen Tran, Aurelien Bibaut, Nathan Kallus
Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
Nikita Tsoy, Nikola Konstantinov
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring
Taira Tsuchiya, Shinji Ito, Junya Honda
Coactive Learning for Large Language Models using Implicit User Feedback
Aaron D. Tucker, Kianté Brantley, Adam Cahall et al.
Matroid Semi-Bandits in Sublinear Time
Ruo-Chun Tzeng, Naoto Ohsaka, Kaito Ariu
Feedback Efficient Online Fine-Tuning of Diffusion Models
Masatoshi Uehara, Yulai Zhao, Kevin Black et al.
Federated Self-Explaining GNNs with Anti-shortcut Augmentations
Linan Yue, Qi Liu, Weibo Gao et al.
How to Leverage Diverse Demonstrations in Offline Imitation Learning
Sheng Yue, Jiani Liu, Xingyuan Hua et al.
Proactive DP: A Multiple Target Optimization Framework for DP-SGD
Marten van Dijk, Nhuong Nguyen, Toan N. Nguyen et al.
When Representations Align: Universality in Representation Learning Dynamics
Loek van Rossem, Andrew Saxe
Generalized Smooth Variational Inequalities: Methods with Adaptive Stepsizes
Daniil Vankov, Angelia Nedich, Lalitha Sankar
Discovering Mixtures of Structural Causal Models from Time Series Data
Sumanth Varambally, Yian Ma, Rose Yu
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
Vy Vo, Trung Le, Tung-Long Vuong et al.
Unsupervised Evaluation of Code LLMs with Round-Trip Correctness
Miltiadis Allamanis, Sheena Panthaplackel, Pengcheng Yin
Trustless Audits without Revealing Data or Models
Suppakit Waiwitlikhit, Ion Stoica, Yi Sun et al.
SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets
Shenghua Wan, Ziyuan Chen, Le Gan et al.
VinT-6D: A Large-Scale Object-in-hand Dataset from Vision, Touch and Proprioception
Zhaoliang Wan, Yonggen Ling, Senlin Yi et al.
S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning
Guancheng Wan, Yijun Tian, Wenke Huang et al.
Non-stationary Online Convex Optimization with Arbitrary Delays
Yuanyu Wan, Chang Yao, Mingli Song et al.
Revisiting the Power of Prompt for Visual Tuning
Yuzhu Wang, Lechao Cheng, Chaowei Fang et al.
An Efficient Maximal Ancestral Graph Listing Algorithm
Tian-Zuo Wang, Wen-Bo Du, Zhi-Hua Zhou
Monotone, Bi-Lipschitz, and Polyak-Łojasiewicz Networks
Ruigang Wang, Krishnamurthy Dvijotham, Ian Manchester
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation
Yuyang Wang, Ahmed Elhag, Navdeep Jaitly et al.
Optimal Kernel Quantile Learning with Random Features
Caixing Wang, Xingdong Feng
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
Han Wang, Sihong He, Zhili Zhang et al.
Mollification Effects of Policy Gradient Methods
Tao Wang, Sylvia Herbert, Sicun Gao
Rapid Learning without Catastrophic Forgetting in the Morris Water Maze
Raymond L Wang, Jaedong Hwang, Akhilan Boopathy et al.
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical
Wei Wang, Takashi Ishida, Yu-Jie Zhang et al.
In-context Learning on Function Classes Unveiled for Transformers
Zhijie Wang, Bo Jiang, Shuai Li
StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization
Shida Wang, Qianxiao Li
Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting
Da Wang, Lin Li, Wei Wei et al.
Visual Transformer with Differentiable Channel Selection: An Information Bottleneck Inspired Approach
Yancheng Wang, Ping Li, Yingzhen Yang
Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models
Zhengbo Wang, Jian Liang, Ran He et al.
Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning
Xiyu Wang, Baijiong Lin, Daochang Liu et al.
EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
Shengjie Wang, Shaohuai Liu, Weirui Ye et al.
A Dual-module Framework for Counterfactual Estimation over Time
Xin Wang, Shengfei Lyu, Lishan Yang et al.
Transforming and Combining Rewards for Aligning Large Language Models
Zihao Wang, Chirag Nagpal, Jonathan Berant et al.
Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data
Yafei Wang, Bo Pan, Mei Li et al.
A Fine-grained Analysis of Fitted Q-evaluation: Beyond Parametric Models
Jiayi Wang, Zhengling Qi, Raymond K. W. Wong
Efficient Online Set-valued Classification with Bandit Feedback
Zhou Wang, Xingye Qiao
Proteus: Exploring Protein Structure Generation for Enhanced Designability and Efficiency
chentong wang, Yannan Qu, Zhangzhi Peng et al.
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks
Haixiao Wang, Zhichao Wang
Transformers Provably Learn Sparse Token Selection While Fully-Connected Nets Cannot
Zixuan Wang, Stanley Wei, Daniel Hsu et al.
Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks
Lihao Wang, Zhaofei Yu
Boximator: Generating Rich and Controllable Motions for Video Synthesis
Jiawei Wang, Yuchen Zhang, Jiaxin Zou et al.
Exact Soft Analytical Side-Channel Attacks using Tractable Circuits
Thomas Wedenig, Rishub Nagpal, Gaëtan Cassiers et al.
Magicoder: Empowering Code Generation with OSS-Instruct
Yuxiang Wei, Zhe Wang, Jiawei Liu et al.
Extending Test-Time Augmentation with Metamorphic Relations for Combinatorial Problems
Siwei Wei, Xudong Zhang, Zhiyang Zhou et al.
Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
Xiaoyu Wen, Chenjia Bai, Kang Xu et al.
Diffusion-based Missing-view Generation With the Application on Incomplete Multi-view Clustering
Jie Wen, Shijie Deng, Waikeung Wong et al.
Stability-Informed Initialization of Neural Ordinary Differential Equations
Theodor Westny, Arman Mohammadi, Daniel Jung et al.
Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains
Steven Wilkins-Reeves, Xu Chen, Qi Ma et al.
Unified Training of Universal Time Series Forecasting Transformers
Gerald Woo, Chenghao Liu, Akshat Kumar et al.
Adaptive Accompaniment with ReaLchords
Yusong Wu, Tim Cooijmans, Kyle Kastner et al.
Ditto: Quantization-aware Secure Inference of Transformers upon MPC
Haoqi Wu, Wenjing Fang, Yancheng Zheng et al.
NExT-GPT: Any-to-Any Multimodal LLM
Shengqiong Wu, Hao Fei, Leigang Qu et al.
Understanding Stochastic Natural Gradient Variational Inference
Kaiwen Wu, Jacob Gardner
A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models
Yihan Wu, Zhengmian Hu, Junfeng Guo et al.
PointMC: Multi-instance Point Cloud Registration based on Maximal Cliques
Yue Wu, Xidao hu, Yongzhe Yuan et al.
Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models
Mingrui Wu, Jiayi Ji, Oucheng Huang et al.
Learning Causal Relations from Subsampled Time Series with Two Time-Slices
Anpeng Wu, Haoxuan Li, Kun Kuang et al.
A Theory of Fault-Tolerant Learning
Changlong Wu, Yifan Wang, Ananth Grama
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization
Yichen WU, Hong Wang, Peilin Zhao et al.
Detecting Any instruction-to-answer interaction relationship:Universal Instruction-to-Answer Navigator for Med-VQA
Zhongze Wu, Hongyan Xu, Yitian Long et al.
Mitigating Label Noise on Graphs via Topological Sample Selection
Yuhao Wu, Jiangchao Yao, Xiaobo Xia et al.
Boosting Reinforcement Learning with Strongly Delayed Feedback Through Auxiliary Short Delays
Qingyuan Wu, Simon Zhan, Yixuan Wang et al.
Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
Xiaobo Xia, Jiale Liu, Shaokun Zhang et al.
LESS: Selecting Influential Data for Targeted Instruction Tuning
Mengzhou Xia, Sadhika Malladi, Suchin Gururangan et al.
Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources
Xia, Jonathan Wilson, Benjamin Goldstein et al.
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
Yifan Xia, Xianliang Yang, Zichuan Liu et al.
Delving into the Convergence of Generalized Smooth Minimax Optimization
Wenhan Xian, Ziyi Chen, Heng Huang
Improved Operator Learning by Orthogonal Attention
Zipeng Xiao, Zhongkai Hao, Bokai Lin et al.
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning
Mingqing Xiao, Yixin Zhu, Di He et al.
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs
Teng Xiao, Huaisheng Zhu, Zhiwei Zhang et al.
Intersecting-Boundary-Sensitive Fingerprinting for Tampering Detection of DNN Models
Xiaofan Bai, Chaoxiang He, Xiaojing Ma et al.
Automating the Selection of Proxy Variables of Unmeasured Confounders
Feng Xie, Zhengming Chen, Shanshan Luo et al.
Implicit Bias of AdamW: $\ell_\infty$-Norm Constrained Optimization
Shuo Xie, Zhiyuan Li
Federated Neuro-Symbolic Learning
Pengwei Xing, Songtao Lu, Han Yu
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
Lanxiang Xing, Haixu Wu, yuezhou ma et al.
Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback
GUOJUN XIONG, Jian Li
Stochastic Bandits with ReLU Neural Networks
Kan Xu, Hamsa Bastani, Surbhi Goel et al.
Intersectional Unfairness Discovery
Gezheng Xu, Qi CHEN, Charles X. Ling et al.
Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning
Ning Xu, Yihao Hu, Congyu Qiao et al.
Enhancing Vision Transformer: Amplifying Non-Linearity in Feedforward Network Module
Yixing Xu, Chao Li, Dong Li et al.
Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning
TengYe Xu, Zihao Li, Qinyuan Ren
Soft Prompt Recovers Compressed LLMs, Transferably
Zhaozhuo Xu, Zirui Liu, Beidi Chen et al.
Adaptive Group Personalization for Federated Mutual Transfer Learning
Haoqing Xu, Dian Shen, Meng Wang et al.
Pricing with Contextual Elasticity and Heteroscedastic Valuation
Jianyu Xu, Yu-Xiang Wang
SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter
Haobo Xu, Yuchen Yan, Dingsu Wang et al.
Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble
Chenhui Xu, Fuxun Yu, Zirui Xu et al.
Exponential Spectral Pursuit: An Effective Initialization Method for Sparse Phase Retrieval
Mengchu Xu, Zhang Yuxuan, Jian Wang
Iterative Regularized Policy Optimization with Imperfect Demonstrations
Xudong Gong, Feng Dawei, Kele Xu et al.
Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings
Yihao Xue, Ali Payani, Yu Yang et al.
Offline Multi-Objective Optimization
Ke Xue, Rong-Xi Tan, Xiaobin Huang et al.
Balancing Similarity and Complementarity for Federated Learning
Kunda Yan, Sen Cui, Abudukelimu Wuerkaixi et al.
Probabilistic Time Series Modeling with Decomposable Denoising Diffusion Model
Tijin Yan, Hengheng Gong, Yongping He et al.
Exploring the LLM Journey from Cognition to Expression with Linear Representations
Yuzi Yan, Jialian Li, YipinZhang et al.
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction
Keqiang Yan, Alexandra Saxton, Xiaofeng Qian et al.
Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching
Kai Yan, Alex Schwing, Yu-Xiong Wang
Handling Heterogeneous Curvatures in Bandit LQR Control
Yu-Hu Yan, Jing Wang, Peng Zhao
SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation
Danni Yang, Jiayi Ji, Yiwei Ma et al.
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation
Haibo Yang, Peiwen Qiu, Prashant Khanduri et al.
UniAudio: Towards Universal Audio Generation with Large Language Models
Dongchao Yang, Jinchuan Tian, Xu Tan et al.
Neuro-Symbolic Temporal Point Processes
Yang Yang, Chao Yang, Boyang Li et al.
Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?
Fan Yao, Chuanhao Li, Denis Nekipelov et al.
Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers
Zhiyu Yao, Jian Wang, Haixu Wu et al.
Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption
Chenlu Ye, Jiafan He, Quanquan Gu et al.
StableMask: Refining Causal Masking in Decoder-only Transformer
Qingyu Yin, Xuzheng He, Xiang Zhuang et al.
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights $\textit{Irreversibly}$ and $\textit{Monotonically}$ Impairs ``Difficult" Downstream Tasks in LLMs
Lu Yin, Ajay Jaiswal, Shiwei Liu et al.
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
Haoran You, Yichao Fu, Zheng Wang et al.
SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN
kang you, Zekai Xu, Chen Nie et al.
Privacy-Preserving Instructions for Aligning Large Language Models
Da Yu, Peter Kairouz, Sewoong Oh et al.
Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders
XUE YU, Muchen Li, Yan Leng et al.
Generalization Bound and New Algorithm for Clean-Label Backdoor Attack
Lijia Yu, Shuang Liu, Yibo Miao et al.
Learning Causal Dynamics Models in Object-Oriented Environments
Zhongwei Yu, Jingqing Ruan, Dengpeng Xing
ViP: A Differentially Private Foundation Model for Computer Vision
Yaodong Yu, Maziar Sanjabi, Yi Ma et al.
Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders
Yi Yu, Yufei Wang, Song Xia et al.
MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities
Weihao Yu, Zhengyuan Yang, Linjie Li et al.
SHINE: Shielding Backdoors in Deep Reinforcement Learning
Zhuowen Yuan, Wenbo Guo, Jinyuan Jia et al.
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
Zelin Zang, Hao Luo, Kai Wang et al.
In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
sili huang, Jifeng Hu, Hechang Chen et al.
tnGPS: Discovering Unknown Tensor Network Structure Search Algorithms via Large Language Models (LLMs)
Junhua Zeng, Chao Li, Zhun Sun et al.
Token-level Direct Preference Optimization
Yongcheng Zeng, Guoqing Liu, Weiyu Ma et al.
Efficient Stochastic Approximation of Minimax Excess Risk Optimization
Lijun Zhang, Haomin Bai, Wei-Wei Tu et al.
Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation
Tonghe Zhang, Yu Chen, Longbo Huang
Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining
Qi Zhang, Tianqi Du, Haotian Huang et al.
CaM: Cache Merging for Memory-efficient LLMs Inference
Yuxin Zhang, Yuxuan Du, Gen Luo et al.
MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness
Yahong Zhang, Chenchen Fan, Donghui Chen et al.
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
Shuai Zhang, Heshan Fernando, Miao Liu et al.
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning
Kaiwen Wang, Owen Oertell, Alekh Agarwal et al.
Parameter-Efficient Fine-Tuning with Controls
Chi Zhang, Jingpu Cheng, Yanyu Xu et al.
Understanding Unimodal Bias in Multimodal Deep Linear Networks
Yedi Zhang, Peter Latham, Andrew Saxe
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
Yihua Zhang, Pingzhi Li, Junyuan Hong et al.
S3O: A Dual-Phase Approach for Reconstructing Dynamic Shape and Skeleton of Articulated Objects from Single Monocular Video
Hao Zhang, Fang Li, Samyak Rawlekar et al.
Understanding and Diagnosing Deep Reinforcement Learning
Ezgi Korkmaz
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
Wanpeng Zhang, Yilin Li, Boyu Yang et al.
Multi-Factor Adaptive Vision Selection for Egocentric Video Question Answering
Haoyu Zhang, Meng Liu, Zixin Liu et al.