Most Cited ICLR "keyframe interpolation" Papers

Minimal Impact ControlNet: Advancing Multi-ControlNet Integration

Shikun Sun, Min Zhou, Zixuan Wang et al.

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings

Samuel Audia, Soheil Feizi, Matthias Zwicker et al.

Input Space Mode Connectivity in Deep Neural Networks

Jakub Vrabel, Ori Shem-ur, Yaron Oz et al.

Bandit Learning in Matching Markets with Indifference

Fang Kong, Jingqi Tang, Mingzhu Li et al.

Conservative Contextual Bandits: Beyond Linear Representations

Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee

Normed Spaces for Graph Embedding

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

Capability Localization: Capabilities Can be Localized rather than Individual Knowledge

Xiusheng Huang, Jiaxiang Liu, Yequan Wang et al.

New Algorithms for the Learning-Augmented k-means Problem

Junyu Huang, Qilong Feng, Ziyun Huang 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.

Learning Successor Features with Distributed Hebbian Temporal Memory

Evgenii Dzhivelikian, Petr Kuderov, Aleksandr Panov

Long-Context Linear System Identification

Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion

Privacy-Aware Lifelong Learning

Ozan Özdenizci, Elmar Rueckert, Robert Legenstein

Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives

Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori et al.

Entropy-based Activation Function Optimization: A Method on Searching Better Activation Functions

Haoyuan Sun, Zihao Wu, Bo Xia et al.

Incremental Causal Effect for Time to Treatment Initialization

Andrew Ying, Zhichen Zhao, Ronghui Xu

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

Zechen Zhang, Haim Sompolinsky

Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures

Ganchao Wei

Training Robust Ensembles Requires Rethinking Lipschitz Continuity

Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran

PT-T2I/V: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Image/Video-Task

Jing Wang, Ao Ma, Jiasong Feng et al.

Clique Number Estimation via Differentiable Functions of Adjacency Matrix Permutations

Indradyumna Roy, Eeshaan Jain, Soumen Chakrabarti et al.

Collapsed Language Models Promote Fairness

Jingxuan Xu, Wuyang Chen, Linyi Li et al.

Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making

Aliyah Hsu, Yeshwanth Cherapanamjeri, Briton Park et al.

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

Alonso Granados, Mohammadreza Ebrahimi, Jason Pacheco

DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity

Zhen Qin, Zhuqing Liu, Songtao Lu et al.

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

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

Scalable Universal T-Cell Receptor Embeddings from Adaptive Immune Repertoires

Paidamoyo Chapfuwa, Ilker Demirel, Lorenzo Pisani et al.

Distribution-Specific Agnostic Conditional Classification With Halfspaces

Jizhou Huang, Brendan Juba

Interactive Adjustment for Human Trajectory Prediction with Individual Feedback

Jianhua Sun, Yuxuan Li, Liang Chai et al.

Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions

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

Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport

Siqi Zeng, Sixian Du, Makoto Yamada et al.

Safety Representations for Safer Policy Learning

Kaustubh Mani, Vincent Mai, Charlie Gauthier et al.

PseDet: Revisiting the Power of Pseudo Label in Incremental Object Detection

Qiuchen Wang, Zehui Chen, Chenhongyi Yang et al.

Generative Adversarial Ranking Nets

Yinghua Yao, Yuangang Pan, Jing Li et al.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression

Michael Crawshaw, Blake Woodworth, Mingrui Liu

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

Daiyao Yi, Hao Dong, Michael Higley et al.

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

Haitian Jiang, Renjie Liu, Zengfeng Huang et al.

Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games

Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu et al.

Binary Losses for Density Ratio Estimation

Werner Zellinger

Strength Estimation and Human-Like Strength Adjustment in Games

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

Learning Regularized Graphon Mean-Field Games with Unknown Graphons

Fengzhuo Zhang, Vincent Tan, Zhaoran Wang et al.

Leveraging Uncertainty Estimates To Improve Classifier Performance

Gundeep Arora, Srujana Merugu, Anoop Saladi 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.

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.

Improving Graph Neural Networks by Learning Continuous Edge Directions

Seong Ho Pahng, Sahand Hormoz

Prompt as Knowledge Bank: Boost Vision-language model via Structural Representation for zero-shot medical detection

Yuguang Yang, Tongfei Chen, Haoyu Huang et al.

Probabilistic Neural Pruning via Sparsity Evolutionary Fokker-Planck-Kolmogorov Equation

Zhanfeng Mo, Haosen Shi, Sinno Jialin Pan

Locally Connected Echo State Networks for Time Series Forecasting

Filip Matzner, František Mráz

Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics

Josiah Kratz, Jacob Adamczyk

SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation

Teng Hu, Jiangning Zhang, Ran Yi et al.

Inverse decision-making using neural amortized Bayesian actors

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

A Robust Method to Discover Causal or Anticausal Relation

Yu Yao, Yang Zhou, Bo Han et al.

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

Minyoung Kim, Timothy Hospedales

Balanced Ranking with Relative Centrality: A multi-core periphery perspective

Chandra Sekhar Mukherjee, Jiapeng Zhang

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

Zhenyu Zhu, Fanghui Liu, Volkan Cevher

Event-Driven Online Vertical Federated Learning

Ganyu Wang, Boyu Wang, Bin Gu et al.

TDDBench: A Benchmark for Training data detection

Zhihao Zhu, Yi Yang, Defu Lian

SWEb: A Large Web Dataset for the Scandinavian Languages

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

MP-Mat: A 3D-and-Instance-Aware Human Matting and Editing Framework with Multiplane Representation

Siyi Jiao, Wenzheng Zeng, Yerong Li et al.

Neural networks on Symmetric Spaces of Noncompact Type

Xuan Son Nguyen, Yang, Aymeric Histace

EvA: Erasing Spurious Correlations with Activations

Qiyuan He, Kai Xu, Angela Yao

Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Power

Lijia Yu, Yibo Miao, Yifan Zhu et al.

The Computational Complexity of Positive Non-Clashing Teaching in Graphs

Robert Ganian, Liana Khazaliya, Fionn Mc Inerney et al.

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.

From Tokens to Lattices: Emergent Lattice Structures in Language Models

Bo Xiong, Steffen Staab

Near-optimal Active Regression of Single-Index Models

Yi Li, Wai Ming Tai

High-Quality Joint Image and Video Tokenization with Causal VAE

Dawit Mureja Argaw, Xian Liu, Qinsheng Zhang et al.

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

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

Associative memory and dead neurons

Vladimir Fanaskov, Ivan Oseledets

Learning under Temporal Label Noise

Sujay Nagaraj, Walter Gerych, Sana Tonekaboni et al.

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

Can Pouliquen, Mathurin Massias, Titouan Vayer

Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning

Hongye Cao, Fan Feng, Meng Fang et al.

Generalized Video Moment Retrieval

Qin You, Qilong Wu, Yicong Li et al.

Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem

Simon Segert

On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning

Roman Belaire, Arunesh Sinha, Pradeep Varakantham

A Large-scale Dataset and Benchmark for Commuting Origin-Destination Flow Generation

Can Rong, Jingtao Ding, Yan Liu et al.

ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge

Eslam Abdelrahman, Liangbing Zhao, Tao Hu et al.

Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception

Ziqi Pang, Xin Xu, Yu-Xiong Wang

Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees

Gautam Chandrasekaran, Adam Klivans, Lin Lin Lee et al.

Zero-cost Proxy for Adversarial Robustness Evaluation

Yuqi Feng, Yuwei Ou, Jiahao Fan et al.

Multi-agent cooperation through learning-aware policy gradients

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

Discrete Latent Plans via Semantic Skill Abstractions

Haobin Jiang, Wang, Zongqing Lu

Which Tasks Should Be Compressed Together? A Causal Discovery Approach for Efficient Multi-Task Representation Compression

Sha Guo, Jing Chen, Zixuan Hu et al.

Complementary Label Learning with Positive Label Guessing and Negative Label Enhancement

Yuhang Li, Zhuying Li, Yuheng Jia

A Large-scale Training Paradigm for Graph Generative Models

Yu Wang, Ryan Rossi, Namyong Park et al.

Generating Less Certain Adversarial Examples Improves Robust Generalization

Minxing Zhang, Michael Backes, Xiao Zhang

SelKD: Selective Knowledge Distillation via Optimal Transport Perspective

Liangliang Shi, Zhengyan Shi, Junchi Yan

Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory

Alexander Levine, Peter Stone, Amy Zhang

Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios

Hongwei Wen, Annika Betken, Hanyuan Hang

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

Yichen Wang, Yiyi Zhang, Xinhao Hu et al.

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

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

Certified Robustness Under Bounded Levenshtein Distance

Elias Abad Rocamora, Grigorios Chrysos, Volkan Cevher

Exploring Learning Complexity for Efficient Downstream Dataset Pruning

Wenyu Jiang, Zhenlong Liu, Zejian Xie et al.

Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling

Cristian Rodriguez-Opazo, Ehsan Abbasnejad, Damien Teney et al.

Adaptive Energy Alignment for Accelerating Test-Time Adaptation

Wonjeong Choi, Do-Yeon Kim, Jungwuk Park et al.

Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning

Yixian Zhang, Huaze Tang, Huijing Lin et al.

Pareto Prompt Optimization

Guang Zhao, Byung-Jun Yoon, Gilchan Park et al.

LocoVR: Multiuser Indoor Locomotion Dataset in Virtual Reality

Kojiro Takeyama, Yimeng Liu, Misha Sra

Generalized Behavior Learning from Diverse Demonstrations

Varshith Sreeramdass, Rohan Paleja, Letian Chen 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.

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.

On the Importance of Language-driven Representation Learning for Heterogeneous Federated Learning

Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo et al.

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

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

DyCAST: Learning Dynamic Causal Structure from Time Series

Yue Cheng, Bochen Lyu, Weiwei Xing et al.

PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph

Dazhou Yu, Genpei Zhang, Liang Zhao

THE ROBUSTNESS OF DIFFERENTIABLE CAUSAL DISCOVERY IN MISSPECIFIED SCENARIOS

Huiyang Yi, Yanyan He, Duxin Chen et al.

Learning Gain Map for Inverse Tone Mapping

yinuo liao, Yuanshen Guan, Ruikang Xu et al.

Neuron Platonic Intrinsic Representation From Dynamics Using Contrastive Learning

Wei Wu, Can Liao, Zizhen Deng et al.

Gaussian Splatting Lucas-Kanade

Liuyue Xie, Joel Julin, Koichiro Niinuma et al.

Contrastive Learning from Synthetic Audio Doppelgängers

Manuel Cherep, Nikhil Singh

RESfM: Robust Deep Equivariant Structure from Motion

Fadi Khatib, Yoni Kasten, Dror Moran et al.

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

Wonhyeok Choi, Kyumin Hwang, Wei Peng et al.

On Rollouts in Model-Based Reinforcement Learning

Bernd Frauenknecht, Devdutt Subhasish, Friedrich Solowjow et al.

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

Trajectory-Class-Aware Multi-Agent Reinforcement Learning

Hyungho Na, Kwanghyeon Lee, Sumin Lee et al.

Scale-aware Recognition in Satellite Images under Resource Constraints

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

Elliptic Loss Regularization

Ali Hasan, Haoming Yang, Yuting Ng et al.

On the Almost Sure Convergence of the Stochastic Three Points Algorithm

Taha EL BAKKALI EL KADI, Omar Saadi

Satisficing Regret Minimization in Bandits

Qing Feng, Tianyi Ma, Ruihao Zhu

FACTS: A Factored State-Space Framework for World Modelling

Li Nanbo, Firas Laakom, Yucheng XU et al.

Filtered not Mixed: Filtering-Based Online Gating for Mixture of Large Language Models

Raeid Saqur, Anastasis Kratsios, Florian Krach et al.

Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction

Huawen Feng, ZekunYao, Junhao Zheng et al.

Fitting Networks with a Cancellation Trick

Jiashun Jin, Jingming Wang

Policy Gradient with Kernel Quadrature

Tetsuro Morimura, Satoshi Hayakawa

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.

Optimizing importance weighting in the presence of sub-population shifts

Floris Holstege, Bram Wouters, Noud Giersbergen et al.

The Hidden Cost of Waiting for Accurate Predictions

Ali Shirali, Ariel Procaccia, Rediet Abebe

Regret Bounds for Episodic Risk-Sensitive Linear Quadratic Regulator

Wenhao Xu, Xuefeng Gao, Xuedong He

R2Det: Exploring Relaxed Rotation Equivariance in 2D Object Detection

Zhiqiang Wu, Yingjie Liu, Hanlin Dong et al.

Injective flows for star-like manifolds

Marcello Negri, Jonathan Aellen, Volker Roth

Scale-Free Graph-Language Models

Jianglin Lu, Yixuan Liu, Yitian Zhang et al.

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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.