Most Cited ICLR "motion dataset" Papers

CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning

Shaofeng Zhang, Qiang Zhou, Sitong Wu et al.

Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping

Yining Li, Peizhong Ju, Ness Shroff

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.

A Large-scale Training Paradigm for Graph Generative Models

Yu Wang, Ryan Rossi, Namyong Park et al.

New Algorithms for the Learning-Augmented k-means Problem

Junyu Huang, Qilong Feng, Ziyun Huang et al.

Benign Overfitting in Out-of-Distribution Generalization of Linear Models

Shange Tang, Jiayun Wu, Jianqing Fan et al.

Generative Adversarial Ranking Nets

Yinghua Yao, Yuangang Pan, Jing Li et al.

Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra

Roman Worschech, Bernd Rosenow

Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation

Shengyuan Zhang, Ling Yang, Zejian Li et al.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression

Michael Crawshaw, Blake Woodworth, Mingrui Liu

ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge

Eslam Abdelrahman, Liangbing Zhao, Tao Hu et al.

EvA: Erasing Spurious Correlations with Activations

Qiyuan He, Kai Xu, Angela Yao

Graph Neural Networks Gone Hogwild

Olga Solodova, Nick Richardson, Deniz Oktay et al.

Beyond single neurons: population response geometry in digital twins of mouse visual cortex

Dario Liscai, Emanuele Luconi, Alessandro Marin Vargas et al.

Revisiting text-to-image evaluation with Gecko: on metrics, prompts, and human rating

Olivia Wiles, Chuhan Zhang, Isabela Albuquerque et al.

Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation

Sua Lee, Kyubum Shin, Jung Ho Park

Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics

Josiah Kratz, Jacob Adamczyk

Distribution-Specific Agnostic Conditional Classification With Halfspaces

Jizhou Huang, Brendan Juba

Decoupled Finetuning for Domain Generalizable Semantic Segmentation

Jaehyun Pahk, Donghyeon Kwon, Seong Joon Oh et al.

Multi-agent cooperation through learning-aware policy gradients

Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald et al.

How Gradient descent balances features: A dynamical analysis for two-layer neural networks

Zhenyu Zhu, Fanghui Liu, Volkan Cevher

Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making

Aliyah Hsu, Yeshwanth Cherapanamjeri, Briton Park et al.

Efficient Causal Decision Making with One-sided Feedback

Jianing Chu, Shu Yang, Wenbin Lu et al.

Generalization and Distributed Learning of GFlowNets

Tiago Silva, Amauri Souza, Omar Rivasplata et al.

Event-Driven Online Vertical Federated Learning

Ganyu Wang, Boyu Wang, Bin Gu et al.

Real-time design of architectural structures with differentiable mechanics and neural networks

Rafael Pastrana, Eder Medina, Isabel M. de Oliveira et al.

PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph

Dazhou Yu, Genpei Zhang, Liang Zhao

Scalable Decentralized Learning with Teleportation

Yuki Takezawa, Sebastian Stich

Learning Gain Map for Inverse Tone Mapping

yinuo liao, Yuanshen Guan, Ruikang Xu et al.

Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport

Siqi Zeng, Sixian Du, Makoto Yamada et al.

Exploring channel distinguishability in local neighborhoods of the model space in quantum neural networks

Sabrina Herbst, Sandeep Cranganore, Vincenzo De Maio et al.

Interactive Adjustment for Human Trajectory Prediction with Individual Feedback

Jianhua Sun, Yuxuan Li, Liang Chai et al.

Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment

Aadirupa Saha, Pierre Gaillard

DyCAST: Learning Dynamic Causal Structure from Time Series

Yue Cheng, Bochen Lyu, Weiwei Xing et al.

Shared-AE: Automatic Identification of Shared Subspaces in High-dimensional Neural and Behavioral Activity

Daiyao Yi, Hao Dong, Michael Higley et al.

Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex

Tanishq Kumar, Blake Bordelon, Cengiz Pehlevan et al.

Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception

Ziqi Pang, Xin Xu, Yu-Xiong Wang

Towards Learning High-Precision Least Squares Algorithms with Sequence Models

Jerry Liu, Jessica Grogan, Owen Dugan et al.

ADAM Optimization with Adaptive Batch Selection

Gyu Yeol Kim, Min-hwan Oh

Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games

Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu et al.

Leveraging Uncertainty Estimates To Improve Classifier Performance

Gundeep Arora, Srujana Merugu, Anoop Saladi et al.

Gaussian Splatting Lucas-Kanade

Liuyue Xie, Joel Julin, Koichiro Niinuma et al.

LEAD: Min-Max Optimization from a Physical Perspective

Guillaume Lajoie, Amartya Mitra, Reyhane Askari Hemmat et al.

High-Dynamic Radar Sequence Prediction for Weather Nowcasting Using Spatiotemporal Coherent Gaussian Representation

Ziye Wang, Yiran Qin, Lin Zeng et al.

Scale-aware Recognition in Satellite Images under Resource Constraints

Shreelekha Revankar, Cheng Perng Phoo, Utkarsh Kumar Mall et al.

Safety Representations for Safer Policy Learning

Kaustubh Mani, Vincent Mai, Charlie Gauthier et al.

Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions

Piotr Indyk, Michael Kapralov, Kshiteej Jitesh Sheth et al.

Scalable Universal T-Cell Receptor Embeddings from Adaptive Immune Repertoires

Paidamoyo Chapfuwa, Ilker Demirel, Lorenzo Pisani et al.

When narrower is better: the narrow width limit of Bayesian parallel branching neural networks

Zechen Zhang, Haim Sompolinsky

R2Det: Exploring Relaxed Rotation Equivariance in 2D Object Detection

Zhiqiang Wu, Yingjie Liu, Hanlin Dong et al.

Boost Self-Supervised Dataset Distillation via Parameterization, Predefined Augmentation, and Approximation

Sheng-Feng Yu, Jia-Jiun Yao, Wei-Chen Chiu

Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives

Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori et al.

Dynamic Assortment Selection and Pricing with Censored Preference Feedback

Jung-hun Kim, Min-hwan Oh

VOILA: Evaluation of MLLMs For Perceptual Understanding and Analogical Reasoning

Nilay Yilmaz, Maitreya Patel, Lawrence Luo et al.

Minimax Optimal Reinforcement Learning with Quasi-Optimism

Harin Lee, Min-hwan Oh

Data Distillation for extrapolative protein design through exact preference optimization

Mostafa Karimi, Sharmi Banerjee, Tommi Jaakkola et al.

Improving Graph Neural Networks by Learning Continuous Edge Directions

Seong Ho Pahng, Sahand Hormoz

Exploring Learning Complexity for Efficient Downstream Dataset Pruning

Wenyu Jiang, Zhenlong Liu, Zejian Xie et al.

Debiasing Federated Learning with Correlated Client Participation

Zhenyu Sun, Ziyang Zhang, Zheng Xu et al.

Feedback Schrödinger Bridge Matching

Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli et al.

SWEb: A Large Web Dataset for the Scandinavian Languages

Tobias Norlund, Tim Isbister, Amaru Cuba Gyllensten et al.

Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables

Yaochen Zhu, Jing Ma, Liang Wu et al.

A representation-learning game for classes of prediction tasks

Neria Uzan, Nir Weinberger

GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation

Dingdong Yang, Yizhi Wang, Konrad Schindler et al.

Mind Control through Causal Inference: Predicting Clean Images from Poisoned Data

Mengxuan Hu, Zihan Guan, Yi Zeng et al.

Self-supervised Monocular Depth Estimation Robust to Reflective Surface Leveraged by Triplet Mining

Wonhyeok Choi, Kyumin Hwang, Wei Peng et al.

Learning Randomized Algorithms with Transformers

Johannes von Oswald, Seijin Kobayashi, Yassir Akram et al.

MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy

Haitian Jiang, Renjie Liu, Zengfeng Huang et al.

Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization

Rei Higuchi, Pierre-Louis Poirion, Akiko Takeda

SleepSMC: Ubiquitous Sleep Staging via Supervised Multimodal Coordination

Shuo Ma, Yingwei Zhang, Yiqiang Chen et al.

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift

Zhen Zhang, Xin Liu, Shaoli Wang et al.

Fast and Accurate Blind Flexible Docking

Zizhuo Zhang, Lijun Wu, Kaiyuan Gao et al.

Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints

Yuxuan Wu, Ziyu Wang, Bhiksha Raj et al.

HADAMRNN: BINARY AND SPARSE TERNARY ORTHOGONAL RNNS

Armand Foucault, Francois Malgouyres, Franck Mamalet

Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem

Simon Segert

Adversarial Latent Feature Augmentation for Fairness

Hoin Jung, Junyi Chai, Xiaoqian Wang

Strength Estimation and Human-Like Strength Adjustment in Games

Chun Jung Chen, Chung-Chin Shih, Ti-Rong Wu

Normed Spaces for Graph Embedding

Wei Zhao, Diaaeldin Taha, J. Riestenberg et al.

Separation Power of Equivariant Neural Networks

Marco Pacini, Xiaowen Dong, Bruno Lepri et al.

Improved Diffusion-based Generative Model with Better Adversarial Robustness

Zekun Wang, Mingyang Yi, Shuchen Xue et al.

Zero-cost Proxy for Adversarial Robustness Evaluation

Yuqi Feng, Yuwei Ou, Jiahao Fan et al.

On the Almost Sure Convergence of the Stochastic Three Points Algorithm

Taha EL BAKKALI EL KADI, Omar Saadi

Minimal Impact ControlNet: Advancing Multi-ControlNet Integration

Shikun Sun, Min Zhou, Zixuan Wang et al.

Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning

Claire Chen, Shuze Liu, Shangtong Zhang

Generalized Video Moment Retrieval

Qin You, Qilong Wu, Yicong Li et al.

Generalizing Weisfeiler-Lehman Kernels to Subgraphs

Dongkwan Kim, Alice Oh

ReCogLab: a framework testing relational reasoning & cognitive hypotheses on LLMs

Andrew Liu, Henry Prior, Gargi Balasubramaniam et al.

Long-Context Linear System Identification

Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion

Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels

Hyeonsu Jeong, Hye Won Chung

Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios

Hongwei Wen, Annika Betken, Hanyuan Hang

Long-tailed Adversarial Training with Self-Distillation

Seungju Cho, Hongsin Lee, Changick Kim

On the Adversarial Vulnerability of Label-Free Test-Time Adaptation

Shahriar Rifat, Jonathan Ashdown, Michael De Lucia et al.

Graph Generation with $K^2$-trees

Yunhui Jang, Dongwoo Kim, Sungsoo Ahn

Injective flows for star-like manifolds

Marcello Negri, Jonathan Aellen, Volker Roth

Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation

Carlos Soto, Matthew Reimherr, Aleksandra Slavkovic et al.

Training Robust Ensembles Requires Rethinking Lipschitz Continuity

Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran

Collapsed Language Models Promote Fairness

Jingxuan Xu, Wuyang Chen, Linyi Li et al.

Risk-Sensitive Variational Actor-Critic: A Model-Based Approach

Alonso Granados, Mohammadreza Ebrahimi, Jason Pacheco

What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits

Harish Babu Manogaran, M. Maruf, Arka Daw et al.

Discrete Latent Plans via Semantic Skill Abstractions

Haobin Jiang, Wang, Zongqing Lu

Associative memory and dead neurons

Vladimir Fanaskov, Ivan Oseledets

InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma

Xiaoxuan Hou, Jiayi Yuan, Joel Z Leibo et al.

Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks

Hung Quang Nguyen, Yingjie Lao, Tung Pham et al.

Learning Robust Representations with Long-Term Information for Generalization in Visual Reinforcement Learning

Rui Yang, Jie Wang, Qijie Peng et al.

The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws

Tian Jin, Ahmed Imtiaz Humayun, Utku Evci et al.

Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory

Alexander Levine, Peter Stone, Amy Zhang

ADMM for Structured Fractional Minimization

Ganzhao Yuan

Union-over-Intersections: Object Detection beyond Winner-Takes-All

Aritra Bhowmik, Pascal Mettes, Martin R. Oswald et al.

RESfM: Robust Deep Equivariant Structure from Motion

Fadi Khatib, Yoni Kasten, Dror Moran et al.

SAVA: Scalable Learning-Agnostic Data Valuation

Samuel Kessler, Tam Le, Vu Nguyen

Fitting Networks with a Cancellation Trick

Jiashun Jin, Jingming Wang

InCoDe: Interpretable Compressed Descriptions For Image Generation

Armand Comas, Aditya Chattopadhyay, Feliu Formosa et al.

Democratic Training Against Universal Adversarial Perturbations

Bing Sun, Jun Sun, Wei Zhao

Certified Robustness Under Bounded Levenshtein Distance

Elias Abad Rocamora, Grigorios Chrysos, Volkan Cevher

Systems with Switching Causal Relations: A Meta-Causal Perspective

Moritz Willig, Tim Tobiasch, Florian Busch et al.

Towards Scalable Topological Regularizers

Wong Hiu-Tung, Darrick Lee, Hong Yan

CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution

Yunju Cho, Jay-Yoon Lee

Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure

Can Pouliquen, Mathurin Massias, Titouan Vayer

The "Law'' of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities

Yongwei Che, Benjamin Eysenbach

Learning Regularized Graphon Mean-Field Games with Unknown Graphons

Fengzhuo Zhang, Vincent Tan, Zhaoran Wang et al.

Satisficing Regret Minimization in Bandits

Qing Feng, Tianyi Ma, Ruihao Zhu

CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models

Shengzhuang Chen, Yikai Liao, Xiaoxiao Sun et al.

Three Mechanisms of Feature Learning in a Linear Network

Yizhou Xu, Liu Ziyin

Learning mirror maps in policy mirror descent

Carlo Alfano, Sebastian Towers, Silvia Sapora et al.

Learning under Temporal Label Noise

Sujay Nagaraj, Walter Gerych, Sana Tonekaboni et al.

qNBO: quasi-Newton Meets Bilevel Optimization

Sheng Fang, Yongjin Liu, Wei Yao et al.

Generalized Behavior Learning from Diverse Demonstrations

Varshith Sreeramdass, Rohan Paleja, Letian Chen et al.

Generating Less Certain Adversarial Examples Improves Robust Generalization

Minxing Zhang, Michael Backes, Xiao Zhang

The Hidden Cost of Waiting for Accurate Predictions

Ali Shirali, Ariel Procaccia, Rediet Abebe

Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations

Xiuchuan Li, Tongliang Liu

Pedestrian Motion Reconstruction: A Large-scale Benchmark via Mixed Reality Rendering with Multiple Perspectives and Modalities

Yichen Wang, Yiyi Zhang, Xinhao Hu et al.

Adversarial Training for Defense Against Label Poisoning Attacks

Melis Ilayda Bal, Volkan Cevher, Michael Muehlebach

Inverse decision-making using neural amortized Bayesian actors

Dominik Straub, Tobias Fabian Niehues, Jan Peters et al.

LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning

Minyoung Kim, Timothy Hospedales

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On the Benefits of Attribute-Driven Graph Domain Adaptation

Ruiyi Fang, Bingheng Li, zhao kang et al.

Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks

Simon Heilig, Alessio Gravina, Alessandro Trenta et al.

From an LLM Swarm to a PDDL-empowered Hive: Planning Self-executed Instructions in a Multi-modal Jungle

Kaustubh Vyas, Damien Graux, Yijun Yang et al.

Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding

Akash Kumar, Zsolt Kira, Yogesh S Rawat

Repurposing in AI: A Distinct Approach or an Extension of Creative Problem Solving?

Aissatou Diallo, Antonis Bikakis, Luke Dickens et al.

Compute-Optimal LLMs Provably Generalize Better with Scale

Marc Finzi, Sanyam Kapoor, Diego Granziol et al.

CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs

Dung Nguyen, Thang Phan, Nam Le Hai et al.

Decoupled Subgraph Federated Learning

Javad Aliakbari, Johan Östman, Alexandre Graell i Amat

Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?

Maxime Méloux, Silviu Maniu, François Portet et al.

Diffusion Bridge Implicit Models

Kaiwen Zheng, Guande He, Jianfei Chen et al.

Beyond Worst-Case Dimensionality Reduction for Sparse Vectors

Sandeep Silwal, David Woodruff, Qiuyi (Richard) Zhang

Elucidating the Preconditioning in Consistency Distillation

Kaiwen Zheng, Guande He, Jianfei Chen et al.

Improving Data Efficiency via Curating LLM-Driven Rating Systems

Jinlong Pang, Jiaheng Wei, Ankit Parag Shah et al.

Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization

Zhe Li, Bicheng Ying, Zidong Liu et al.

Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable

Chenxiao Yang, Zhiyuan Li, David Wipf

Understanding Warmup-Stable-Decay Learning Rates: A River Valley Loss Landscape View

Kaiyue Wen, Zhiyuan Li, Jason Wang et al.

nGPT: Normalized Transformer with Representation Learning on the Hypersphere

Ilya Loshchilov, Cheng-Ping Hsieh, Simeng Sun et al.

A Coefficient Makes SVRG Effective

Yida Yin, Zhiqiu Xu, Zhiyuan Li et al.

Homomorphism Counts as Structural Encodings for Graph Learning

Linus Bao, Emily Jin, Michael Bronstein et al.

PhysPDE: Rethinking PDE Discovery and a Physical HYpothesis Selection Benchmark

Mingquan Feng, Yixin Huang, Yizhou Liu et al.

Adam Exploits $\ell_\infty$-geometry of Loss Landscape via Coordinate-wise Adaptivity

Shuo Xie, Mohamad Amin Mohamadi, Zhiyuan Li

Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form

Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai et al.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression

Juno Kim, Dimitri Meunier, Arthur Gretton et al.

TC-MoE: Augmenting Mixture of Experts with Ternary Expert Choice

Shen Yan, Xingyan Bin, Sijun Zhang et al.

Remove Symmetries to Control Model Expressivity and Improve Optimization

Liu Ziyin, Yizhou Xu, Isaac Chuang

JPEG Inspired Deep Learning

Ahmed Hussien Salamah, Kaixiang Zheng, Yiwen Liu et al.

ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities

Peng Xu, Wei Ping, Xianchao Wu et al.

gRNAde: Geometric Deep Learning for 3D RNA inverse design

Chaitanya Joshi, Arian Jamasb, Ramon Viñas et al.

Boltzmann priors for Implicit Transfer Operators

Juan Viguera Diez, Mathias Schreiner, Ola Engkvist et al.

Biologically Constrained Barrel Cortex Model Integrates Whisker Inputs and Replicates Key Brain Network Dynamics

Tianfang Zhu, Dongli Hu, Jiandong Zhou et al.

Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy

Ishank Juneja, Carlee Joe-Wong, Osman Yagan

In-Context Editing: Learning Knowledge from Self-Induced Distributions

Siyuan Qi, Bangcheng Yang, Kailin Jiang et al.

Towards Understanding the Universality of Transformers for Next-Token Prediction

Michael Sander, Gabriel Peyré

Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning

Menglong Zhang, Fuyuan Qian, Quanying Liu

CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction

Yunfei Teng, Yuxuan Ren, Kai Chen et al.

KAN: Kolmogorov–Arnold Networks

Ziming Liu, Yixuan Wang, Sachin Vaidya et al.

Online Clustering with Nearly Optimal Consistency

T-H. Hubert Chan, Shaofeng Jiang, Tianyi Wu et al.

Simplifying, Stabilizing and Scaling Continuous-time Consistency Models

Cheng Lu, Yang Song

The Geometry of Categorical and Hierarchical Concepts in Large Language Models

Kiho Park, Yo Joong Choe, Yibo Jiang et al.

Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data

Binghui Li, Yuanzhi Li

TRENDy: Temporal Regression of Effective Nonlinear Dynamics

Matthew Ricci, Guy Pelc, Zoe Piran et al.

Regularized Proportional Fairness Mechanism for Resource Allocation Without Money

Sujay Bhatt, Alec Koppel, Sumitra Ganesh et al.

Dynamic Neural Fortresses: An Adaptive Shield for Model Extraction Defense

Siyu Luan, Zhenyi Wang, Li Shen et al.

Protein Language Model Fitness is a Matter of Preference

Cade Gordon, Amy Lu, Pieter Abbeel

Watch Less, Do More: Implicit Skill Discovery for Video-Conditioned Policy

Wang, Zongqing Lu

Learning and aligning single-neuron invariance manifolds in visual cortex

Mohammad Bashiri, Luca Baroni, Ján Antolík et al.

From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities

Wanpeng Zhang, Zilong Xie, Yicheng Feng et al.

Cross-Domain Offline Policy Adaptation with Optimal Transport and Dataset Constraint

Jiafei Lyu, Mengbei Yan, Zhongjian Qiao et al.

Robustness Inspired Graph Backdoor Defense

Zhiwei Zhang, Minhua Lin, Junjie Xu et al.

Do You Keep an Eye on What I Ask? Mitigating Multimodal Hallucination via Attention-Guided Ensemble Decoding

Yeongjae Cho, Keonwoo Kim, Taebaek Hwang et al.

Lost in Prediction: Why Social Media Narratives Don't Help Macroeconomic Forecasting?

Almog Gueta, Roi Reichart, Amir Feder et al.

Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching

Zijing Ou, Mingtian Zhang, Andi Zhang et al.

TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes

Minghao Guo, Bohan Wang, Kaiming He et al.

Procedural Synthesis of Synthesizable Molecules

Michael Sun, Alston Lo, Minghao Guo et al.

Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks

Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang et al.

LOIRE: LifelOng learning on Incremental data via pre-trained language model gRowth Efficiently

Xue Han, Yitong Wang, Junlan Feng et al.

Conditional Testing based on Localized Conformal $p$-values

Xiaoyang Wu, Lin Lu, Zhaojun Wang et al.

Occlusion-aware Non-Rigid Point Cloud Registration via Unsupervised Neural Deformation Correntropy

Mingyang Zhao, Gaofeng Meng, Dong-ming Yan

3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting

Qihang Zhang, Yinghao Xu, Chaoyang Wang et al.

On Disentangled Training for Nonlinear Transform in Learned Image Compression

Han Li, Shaohui Li, Wenrui Dai et al.

Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence

Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker et al.

Optimality of Matrix Mechanism on $\ell_p^p$-metric

Zongrui Zou, Jingcheng Liu, Jalaj Upadhyay

Adversarial Mixup Unlearning

Zhuoyi Peng, Yixuan Tang, Yi Yang

Time-to-Event Pretraining for 3D Medical Imaging

Zepeng Frazier Huo, Jason Fries, Alejandro Lozano et al.

Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement

Bryan Bo Cao, Lawrence OGorman, Michael Coss et al.