Most Cited ICLR "multi-view ensembling" Papers
6,124 papers found • Page 28 of 31
Conference
Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification
Santiago Cortes-Gomez, Carlos Patiño, Yewon Byun et al.
Uncovering Overfitting in Large Language Model Editing
Mengqi Zhang, Xiaotian Ye, Qiang Liu et al.
ParetoFlow: Guided Flows in Multi-Objective Optimization
Ye Yuan, Can Chen, Christopher Pal et al.
HyperDAS: Towards Automating Mechanistic Interpretability with Hypernetworks
Jiuding Sun, Jing Huang, Sidharth Baskaran et al.
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Verification
Yunzhen Feng, Elvis Dohmatob, Pu Yang et al.
Learning from weak labelers as constraints
Vishwajeet Agrawal, Rattana Pukdee, Nina Balcan et al.
GReaTer: Gradients Over Reasoning Makes Smaller Language Models Strong Prompt Optimizers
Sarkar Snigdha Sarathi Das, Ryo Kamoi, Bo Pang et al.
Agent-to-Sim: Learning Interactive Behavior Models from Casual Longitudinal Videos
Gengshan Yang, Andrea Bajcsy, Shunsuke Saito et al.
MAPS: Advancing Multi-Modal Reasoning in Expert-Level Physical Science
Erle Zhu, Yadi Liu, Zhe Zhang et al.
Fine-Tuning Token-Based Large Multimodal Models: What Works, What Doesn’t and What's Next
Zhulin Hu, Yan Ma, Jiadi Su et al.
T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
Hugo Thimonier, José Lucas De Melo Costa, Fabrice Popineau et al.
h4rm3l: A Language for Composable Jailbreak Attack Synthesis
Moussa Koulako Bala Doumbouya, Ananjan Nandi, Gabriel Poesia et al.
Balancing Act: Diversity and Consistency in Large Language Model Ensembles
Ahmed Abdulaal, Chen Jin, Nina Montaña-Brown et al.
Scaling Long Context Training Data by Long-Distance Referrals
Yonghao Zhuang, Lanxiang Hu, Longfei Yun et al.
Optimal Flow Transport and its Entropic Regularization: a GPU-friendly Matrix Iterative Algorithm for Flow Balance Satisfaction
Liangliang Shi, Yufeng Li, Kaipeng Zeng et al.
AutoBencher: Towards Declarative Benchmark Construction
XIANG LI, Farzaan Kaiyom, Evan Liu et al.
Intrinsic User-Centric Interpretability through Global Mixture of Experts
Vinitra Swamy, Syrielle Montariol, Julian Blackwell et al.
PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
Qiang Liu, Huiqiao Fu, Kaiqiang Tang et al.
MorphoDiff: Cellular Morphology Painting with Diffusion Models
Zeinab Navidi, Jun Ma, Esteban Miglietta et al.
Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization
Matthew Burns, Qingyuan Hou, Michael Huang
Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study
Shawn Tan, Songlin Yang, Aaron Courville et al.
Multi-Task Dense Predictions via Unleashing the Power of Diffusion
Yuqi Yang, Peng-Tao Jiang, Qibin Hou et al.
Innovative Thinking, Infinite Humor: Humor Research of Large Language Models through Structured Thought Leaps
Han Wang, Yilin Zhao, Dian Li et al.
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Zilong Wang, Hao Zhang, Chun-Liang Li et al.
Class Distribution-induced Attention Map for Open-vocabulary Semantic Segmentations
Dong Un Kang, Hayeon Kim, Se Young Chun
ContraDiff: Planning Towards High Return States via Contrastive Learning
Yixiang Shan, Zhengbang Zhu, Ting Long et al.
Reassessing EMNLP 2024’s Best Paper: Does Divergence-Based Calibration for MIAs Hold Up?
Pratyush Maini, Anshuman Suri
Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images
Aiqing Zhu, Yuting Pan, Qianxiao Li
MAESTRO: Masked Encoding Set Transformer with Self-Distillation
Matthew Lee, Jaesik Kim, Matei Ionita et al.
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
Yinuo Ren, Haoxuan Chen, Grant Rotskoff et al.
Efficient stagewise pretraining via progressive subnetworks
Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu et al.
ODE-based Smoothing Neural Network for Reinforcement Learning Tasks
Yinuo Wang, Wenxuan Wang, Xujie Song et al.
Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies
Sijin Chen, Omar Hagrass, Jason Klusowski
Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions
Peiyao Lai, Oren Mangoubi
What is Wrong with Perplexity for Long-context Language Modeling?
Lizhe Fang, Yifei Wang, Zhaoyang Liu et al.
Diffusion Models and Gaussian Flow Matching: Two Sides of the Same Coin
Ruiqi Gao, Emiel Hoogeboom, Jonathan Heek et al.
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
Zhaoning Yu, Hongyang Gao
COPER: Correlation-based Permutations for Multi-View Clustering
Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum
Straightness of Rectified Flow: A Theoretical Insight into Wasserstein Convergence
Saptarshi Roy, Vansh Bansal, Purnamrita Sarkar et al.
Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness
Baolong Bi, Shenghua Liu, Yiwei Wang et al.
Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning
Yixian Zhang, Huaze Tang, Huijing Lin et al.
ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
Hannes Stärk, Bowen Jing, Tomas Geffner et al.
Doubly robust identification of treatment effects from multiple environments
Piersilvio De Bartolomeis, Julia Kostin, Javier Abad et al.
Can We Trust Embodied Agents? Exploring Backdoor Attacks against Embodied LLM-Based Decision-Making Systems
Ruochen Jiao, Shaoyuan Xie, Justin Yue et al.
Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors
Sungyoon Lee, Sokbae Lee
Factor Graph-based Interpretable Neural Networks
Yicong Li, Kuanjiu Zhou, Shuo Yu et al.
Do WGANs succeed because they minimize the Wasserstein Distance? Lessons from Discrete Generators
Ariel Elnekave, Yair Weiss
Divergence of Neural Tangent Kernel in Classification Problems
Zixiong Yu, Songtao Tian, Guhan Chen
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models
Zuxin Liu, Jesse Zhang, Kavosh Asadi et al.
ProteinBench: A Holistic Evaluation of Protein Foundation Models
Fei YE, Zaixiang Zheng, Dongyu Xue et al.
Enhancing Prediction Performance through Influence Measure
Shuguang Yu, Wenqian Xu, Xinyi Zhou et al.
Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment
Chenhang Cui, An Zhang, Yiyang Zhou et al.
MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models
Peng Xia, Siwei Han, Shi Qiu et al.
PPT: Patch Order Do Matters In Time Series Pretext Task
Jaeho Kim, Kwangryeol Park, Sukmin Yun et al.
Learning LLM-as-a-Judge for Preference Alignment
Ziyi Ye, Xiangsheng Li, Qiuchi Li et al.
Reliable and Diverse Evaluation of LLM Medical Knowledge Mastery
Yuxuan Zhou, Xien Liu, Chen Ning et al.
Vision CNNs trained to estimate spatial latents learned similar ventral-stream-aligned representations
Yudi Xie, Weichen Huang, Esther Alter et al.
Gaussian Mixture Counterfactual Generator
Jong-Hoon Ahn, Akshay Vashist
Retri3D: 3D Neural Graphics Representation Retrieval
Yushi Guan, Daniel Kwan, Jean Dandurand et al.
Learning Graph Quantized Tokenizers
Limei Wang, Kaveh Hassani, Si Zhang et al.
PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration
Yuxuan Sun, Yunlong Zhang, Yixuan Si et al.
Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems
Guibin Zhang, Yanwei Yue, Zhixun Li et al.
From Decoupling to Adaptive Transformation: a Wider Optimization Space for PTQ
Zhaojing Wen, Qiulin Zhang, Yuan Zhang et al.
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
Guangkun Nie, Gongzheng Tang, Shenda Hong
Scaling Large Language Model-based Multi-Agent Collaboration
Chen Qian, Zihao Xie, YiFei Wang et al.
Less is More: Masking Elements in Image Condition Features Avoids Content Leakages in Style Transfer Diffusion Models
Lin Zhu, Xinbing Wang, Chenghu Zhou et al.
When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs'' for Human-AI Interaction
Zhenchang Xing, Yang Liu, Zhuo Cheng et al.
Quantifying Generalization Complexity for Large Language Models
Zhenting Qi, Hongyin Luo, Xuliang Huang et al.
Do vision models perceive objects like toddlers ?
Arthur Aubret, Jochen Triesch
YOLO-RD: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary
Hao-Tang Tsui, Chien-Yao Wang, Hong-Yuan Liao
Hierarchical Uncertainty Estimation for Learning-based Registration in Neuroimaging
Xiaoling Hu, Karthik Gopinath, Peirong Liu et al.
Multi-Reward as Condition for Instruction-based Image Editing
Xin Gu, Ming Li, Libo Zhang et al.
A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems
Shulan Zhu, Chenglong Bao, Defeng Sun et al.
A Benchmark for Semantic Sensitive Information in LLMs Outputs
Qingjie Zhang, Han Qiu, Di Wang et al.
Lipschitz Bandits in Optimal Space
Xiaoyi Zhu, Zengfeng Huang
TEASER: Token Enhanced Spatial Modeling for Expressions Reconstruction
Yunfei Liu, Lei Zhu, Lijian Lin et al.
Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
Shuang Liu, Yihan Wang, Yifan Zhu et al.
GROOT-2: Weakly Supervised Multimodal Instruction Following Agents
Shaofei Cai, Bowei Zhang, Zihao Wang et al.
Computing Circuits Optimization via Model-Based Circuit Genetic Evolution
Zhihai Wang, Jie Wang, Xilin Xia et al.
Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning
Sheng Li, Qitao Tan, Yue Dai et al.
Geometry of Lightning Self-Attention: Identifiability and Dimension
Nathan Henry, Giovanni Luca Marchetti, Kathlén Kohn
Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics
Josiah Kratz, Jacob Adamczyk
Deep Networks Learn Features From Local Discontinuities in the Label Function
Prithaj Banerjee, Harish G Ramaswamy, Mahesh Yadav et al.
Vevo: Controllable Zero-Shot Voice Imitation with Self-Supervised Disentanglement
Xueyao Zhang, Xiaohui Zhang, Kainan Peng et al.
Safe Collaborative Filtering
Riku Togashi, Tatsushi Oka, Naoto Ohsaka et al.
Towards more rigorous evaluations of language models
Desi R Ivanova, Ilija Ilievski, Momchil Konstantinov
OmniBind: Large-scale Omni Multimodal Representation via Binding Spaces
zehan wang, Ziang Zhang, Minjie Hong et al.
RobustKV: Defending Large Language Models against Jailbreak Attacks via KV Eviction
Tanqiu Jiang, Zian Wang, Jiacheng Liang et al.
Exploiting Hidden Symmetry to Improve Objective Perturbation for DP Linear Learners with a Nonsmooth L1-Norm
Du Chen, Geoffrey A. Chua
Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off
Futa Waseda, Ching-Chun Chang, Isao Echizen
Sort-free Gaussian Splatting via Weighted Sum Rendering
Qiqi Hou, Randall Rauwendaal, Zifeng Li et al.
BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
Aly Lidayan, Michael Dennis, Stuart Russell
Weak to Strong Generalization for Large Language Models with Multi-capabilities
Yucheng Zhou, Jianbing Shen, Yu Cheng
Is Your Model Really A Good Math Reasoner? Evaluating Mathematical Reasoning with Checklist
Zihao Zhou, Shudong Liu, Maizhen Ning et al.
Gyrogroup Batch Normalization
Ziheng Chen, Yue Song, Xiaojun Wu et al.
ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning
Zihan Ye, Shreyank Gowda, Shiming Chen et al.
GrabS: Generative Embodied Agent for 3D Object Segmentation without Scene Supervision
Zihui Zhang, Yafei YANG, Hongtao Wen et al.
Laplace Sample Information: Data Informativeness Through a Bayesian Lens
Johannes Kaiser, Kristian Schwethelm, Daniel Rueckert et al.
QP-SNN: Quantized and Pruned Spiking Neural Networks
Wenjie Wei, Malu Zhang, Zijian Zhou et al.
MMEgo: Towards Building Egocentric Multimodal LLMs for Video QA
Hanrong Ye, Haotian Zhang, Erik Daxberger et al.
TidalDecode: Fast and Accurate LLM Decoding with Position Persistent Sparse Attention
Lijie Yang, Zhihao Zhang, Zhuofu Chen et al.
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Zhengfeng Lai, Vasileios Saveris, Chen Chen et al.
Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence
Weize Chen, Ziming You, Ran Li et al.
SAM 2: Segment Anything in Images and Videos
Nikhila Ravi, Valentin Gabeur, Yuan-Ting Hu et al.
Adam-mini: Use Fewer Learning Rates To Gain More
Yushun Zhang, Congliang Chen, Ziniu Li et al.
SegLLM: Multi-round Reasoning Segmentation with Large Language Models
Xudong Wang, Shaolun Zhang, Shufan Li et al.
Adaptive Rank Allocation: Speeding Up Modern Transformers with RaNA Adapters
Roberto Garcia, Jerry Liu, Daniel Sorvisto et al.
AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly
Hongyu Guo, Yoshua Bengio, Shengchao Liu
Automatic Curriculum Expert Iteration for Reliable LLM Reasoning
Zirui Zhao, Hanze Dong, Amrita Saha et al.
ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
Ziru Chen, Shijie Chen, Yuting Ning et al.
Poisson-Dirac Neural Networks for Modeling Coupled Dynamical Systems across Domains
Razmik Khosrovian, Takaharu Yaguchi, Hiroaki Yoshimura et al.
Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA
Sangmin Bae, Adam Fisch, Hrayr Harutyunyan et al.
Teaching LLMs How to Learn with Contextual Fine-Tuning
Younwoo Choi, Muhammad Adil Asif, Ziwen Han et al.
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction
Junjie Xu, Artem Moskalev, Tommaso Mansi et al.
Mixture of In-Context Prompters for Tabular PFNs
Derek Xu, Olcay Cirit, Reza Asadi et al.
Open-Vocabulary Customization from CLIP via Data-Free Knowledge Distillation
Yongxian Wei, Zixuan Hu, Li Shen et al.
Towards counterfactual fairness through auxiliary variables
Bowei Tian, Ziyao Wang, Shwai He et al.
Towards Continuous Reuse of Graph Models via Holistic Memory Diversification
Ziyue Qiao, Junren Xiao, Qingqiang Sun et al.
Analytically Tractable Hidden-States Inference in Bayesian Neural Networks
Luong-Ha Nguyen, James-A. Goulet
Cauchy-Schwarz Regularizers
Sueda Taner, Ziyi Wang, Christoph Studer
Breaking the $\log(1/\Delta_2)$ Barrier: Better Batched Best Arm Identification with Adaptive Grids
Tianyuan Jin, Qin Zhang, Dongruo Zhou
The Complexity of Two-Team Polymatrix Games with Independent Adversaries
Alexandros Hollender, Gilbert Maystre, Sai Ganesh Nagarajan
INS: Interaction-aware Synthesis to Enhance Offline Multi-agent Reinforcement Learning
Yuqian Fu, Yuanheng Zhu, Jian Zhao et al.
Classic but Everlasting: Traditional Gradient-Based Algorithms Converge Fast Even in Time-Varying Multi-Player Games
Yanzheng Chen, Jun Yu
Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction
Ziyang Wu, Tianjiao Ding, Yifu Lu et al.
FlexCAD: Unified and Versatile Controllable CAD Generation with Fine-tuned Large Language Models
Zhanwei Zhang, Shizhao Sun, Wenxiao Wang et al.
Improving Complex Reasoning with Dynamic Prompt Corruption: A Soft Prompt Optimization Approach
Sinan Fan, Liang Xie, Chen Shen et al.
Continuous Exposure Learning for Low-light Image Enhancement using Neural ODEs
Donggoo Jung, Daehyun Kim, Tae Hyun Kim
High-dimension Prototype is a Better Incremental Object Detection Learner
Yanjie Wang, Liqun Chen, Tianming Zhao et al.
Discriminator-Guided Embodied Planning for LLM Agent
Haofu Qian, Chenjia Bai, Jiatao Zhang et al.
Controllable Unlearning for Image-to-Image Generative Models via $\epsilon$-Constrained Optimization
XiaoHua Feng, Yuyuan Li, Chaochao Chen et al.
Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models
Dvir Samuel, Barak Meiri, Haggai Maron et al.
Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding
Yanming Liu, Xinyue Peng, Jiannan Cao et al.
Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attention
Tongzhou Liao, Barnabás Póczos
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen et al.
Robotouille: An Asynchronous Planning Benchmark for LLM Agents
Gonzalo Gonzalez-Pumariega, Leong Yean, Neha Sunkara et al.
Generation and Comprehension Hand-in-Hand: Vision-guided Expression Diffusion for Boosting Referring Expression Generation and Comprehension
Jingcheng Ke, Jun-Cheng Chen, I-Hong Jhuo et al.
Sketch2Diagram: Generating Vector Diagrams from Hand-Drawn Sketches
Itsumi Saito, Haruto Yoshida, Keisuke Sakaguchi
Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences
Nikos Dimitriadis, Pascal Frossard, François Fleuret
BP-Modified Local Loss for Efficient Training of Deep Neural Networks
REN Lianhai, Qianxiao Li
Endowing Visual Reprogramming with Adversarial Robustness
Shengjie Zhou, Xin Cheng, Haiyang Xu et al.
DOCS: Quantifying Weight Similarity for Deeper Insights into Large Language Models
Zeping Min, Xinshang Wang
Improving Neural Network Accuracy by Concurrently Training with a Twin Network
Benjamin Vandersmissen, Lucas Deckers, Jose Oramas
Automatic Functional Differentiation in JAX
Min Lin
Designing Concise ConvNets with Columnar Stages
Ashish Kumar, Jaesik Park
Local convergence of simultaneous min-max algorithms to differential equilibrium on Riemannian manifold
Sixin Zhang
Policy Optimization under Imperfect Human Interactions with Agent-Gated Shared Autonomy
Zhenghai Xue, Bo An, Shuicheng YAN
On the Optimal Memorization Capacity of Transformers
Tokio Kajitsuka, Issei Sato
Shape as Line Segments: Accurate and Flexible Implicit Surface Representation
Siyu Ren, Junhui Hou
Attention with Markov: A Curious Case of Single-layer Transformers
Ashok Makkuva, Marco Bondaschi, Adway Girish et al.
Do Stochastic, Feel Noiseless: Stable Stochastic Optimization via a Double Momentum Mechanism
Tehila Dahan, Kfir Y Levy
Reexamining the Aleatoric and Epistemic Uncertainty Dichotomy
Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions
Yan Ru Pei
How Feature Learning Can Improve Neural Scaling Laws
Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan
Multi-LLM-Agents Debate - Performance, Efficiency, and Scaling Challenges
Hangfan Zhang, Zhiyao Cui, Qiaosheng Zhang et al.
Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale
Alaa Khaddaj, Logan Engstrom, Aleksander Madry
Exploring The Forgetting in Adversarial Training: A Novel Method for Enhancing Robustness
Xianglu Wang, Hu Ding
Can LLM Simulations Truly Reflect Humanity? A Deep Dive
Qian Wang, Zhenheng Tang, Bingsheng He
Multi-objective antibody design with constrained preference optimization
Milong Ren, ZaiKai He, Haicang Zhang
Robot Fleet Learning via Policy Merging
Lirui Wang, Kaiqing Zhang, Allan Zhou et al.
Topic Modeling as Multi-Objective Contrastive Optimization
Thong Thanh Nguyen, Xiaobao Wu, Xinshuai Dong et al.
PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation
Haopeng Sun, Lumin Xu, Sheng Jin et al.
LOQA: Learning with Opponent Q-Learning Awareness
Milad Aghajohari, Juan Duque, Timotheus Cooijmans et al.
Blending Imitation and Reinforcement Learning for Robust Policy Improvement
Xuefeng Liu, Takuma Yoneda, Rick Stevens et al.
A Simple Romance Between Multi-Exit Vision Transformer and Token Reduction
Dongyang Liu, Meina Kan, Shiguang Shan et al.
Sparsistency for inverse optimal transport
Francisco Andrade, Gabriel Peyré, Clarice Poon
Zipformer: A faster and better encoder for automatic speech recognition
Zengwei Yao, Liyong Guo, Xiaoyu Yang et al.
NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation
Pengfei Zheng, Yonggang Zhang, Zhen Fang et al.
Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks
Xihaier Luo, Wei Xu, Balasubramanya T. Nadiga et al.
GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion
Xueyi Liu, Li Yi
Reward Model Ensembles Help Mitigate Overoptimization
Thomas Coste, Usman Anwar, Robert Kirk et al.
Near-Optimal Solutions of Constrained Learning Problems
Juan Elenter, Luiz Chamon, Alejandro Ribeiro
Identifying the Risks of LM Agents with an LM-Emulated Sandbox
Yangjun Ruan, Honghua Dong, Andrew Wang et al.
Patched Denoising Diffusion Models For High-Resolution Image Synthesis
Zheng Ding, Mengqi Zhang, Jiajun Wu et al.
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Yuwei GUO, Ceyuan Yang, Anyi Rao et al.
AttEXplore: Attribution for Explanation with model parameters eXploration
Zhiyu Zhu, Huaming Chen, Jiayu Zhang et al.
Multisize Dataset Condensation
Yang He, Lingao Xiao, Joey Tianyi Zhou et al.
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates
Siqi Zhang, Sayantan Choudhury, Sebastian Stich et al.
Reasoning with Latent Diffusion in Offline Reinforcement Learning
Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella et al.
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
Dujian Ding, Ankur Mallick, Chi Wang et al.
Sparse Autoencoders Find Highly Interpretable Features in Language Models
Robert Huben, Hoagy Cunningham, Logan Smith et al.
Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation
Hoyong Kim, Kangil Kim
Dual-Encoders for Extreme Multi-label Classification
Nilesh Gupta, Fnu Devvrit, Ankit Singh Rawat et al.
Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers
Runyi Zhao, Sheng Xu, Bo Yue et al.
Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy
Simon Ging, Maria A. Bravo, Thomas Brox
ResFields: Residual Neural Fields for Spatiotemporal Signals
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys et al.
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform
Shengyi Huang, Jiayi Weng, Rujikorn Charakorn et al.
SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs
Jaehyung Kim, Jaehyun Nam, Sangwoo Mo et al.
Feature Collapse
Thomas Laurent, James von Brecht, Xavier Bresson
HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
Sunwoo Kim, Shinhwan Kang, Fanchen Bu et al.
In-context Exploration-Exploitation for Reinforcement Learning
Zhenwen Dai, Federico Tomasi, Sina Ghiassian
Model Merging by Uncertainty-Based Gradient Matching
Nico Daheim, Thomas Möllenhoff, Edoardo M. Ponti et al.
Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data?
Megan Richards, Polina Kirichenko, Diane Bouchacourt et al.
Learning Optimal Contracts: How to Exploit Small Action Spaces
Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi et al.
Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs
Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande et al.
Self-Supervised High Dynamic Range Imaging with Multi-Exposure Images in Dynamic Scenes
Zhilu Zhang, Haoyu Wang, Shuai Liu et al.
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization
Fei Kong, Jinhao Duan, ruipeng ma et al.
Test-Time Training on Nearest Neighbors for Large Language Models
Moritz Hardt, Yu Sun
Critical Learning Periods Emerge Even in Deep Linear Networks
Michael Kleinman, Alessandro Achille, Stefano Soatto
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency
Tianhong Li, Sangnie Bhardwaj, Yonglong Tian et al.