Most Cited ICLR "vision-language context sparsification" Papers
6,124 papers found • Page 22 of 31
Conference
Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery
Amin Soleimani Abyaneh, Mahrokh Boroujeni, Hsiu-Chin Lin et al.
DRoP: Distributionally Robust Data Pruning
Artem Vysogorets, Kartik Ahuja, Julia Kempe
Symmetric Single Index Learning
Aaron Zweig, Joan Bruna
Tight Rates in Supervised Outlier Transfer Learning
Mohammadreza Mousavi Kalan, Samory Kpotufe
Higher-Order Graphon Neural Networks: Approximation and Cut Distance
Daniel Herbst, Stefanie Jegelka
Self-supervised contrastive learning performs non-linear system identification
Rodrigo Gonzalez Laiz, Tobias Schmidt, Steffen Schneider
Going Beyond Feature Similarity: Effective Dataset distillation based on Class-aware Conditional Mutual Information
Xinhao Zhong, Bin Chen, Hao Fang et al.
Operator Deep Smoothing for Implied Volatility
Ruben Wiedemann, Antoine (Jack) Jacquier, Lukas Gonon
Bandits with Replenishable Knapsacks: the Best of both Worlds
Martino Bernasconi, Matteo Castiglioni, Andrea Celli et al.
OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination
Tobias Gessler, Tin Dizdarevic, Ani Calinescu et al.
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks
Tianyu Fan, Lirong Wu, Yufei Huang et al.
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
Finn Rietz, Erik Schaffernicht, Stefan Heinrich et al.
Controllable Blur Data Augmentation Using 3D-Aware Motion Estimation
Insoo Kim, Hana Lee, Hyong-Euk Lee et al.
BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
Aly Lidayan, Michael Dennis, Stuart Russell
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
Kaixuan Ji, Qingyue Zhao, Jiafan He et al.
A Black Swan Hypothesis: The Role of Human Irrationality in AI Safety
Hyunin Lee, Chanwoo Park, David Abel et al.
Certifying Counterfactual Bias in LLMs
Isha Chaudhary, Qian Hu, Manoj Kumar et al.
Implicit Maximum a Posteriori Filtering via Adaptive Optimization
Gianluca Bencomo, Jake Snell, Thomas L. Griffiths
Doubly Robust Proximal Causal Learning for Continuous Treatments
Yong Wu, Yanwei Fu, Shouyan Wang et al.
Adversarial Causal Bayesian Optimization
Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova et al.
Second-Order Min-Max Optimization with Lazy Hessians
Lesi Chen, Chengchang Liu, Jingzhao Zhang
Improving Intrinsic Exploration by Creating Stationary Objectives
Roger Creus Castanyer, Joshua Romoff, Glen Berseth
Breaking the Reclustering Barrier in Centroid-based Deep Clustering
Lukas Miklautz, Timo Klein, Kevin Sidak et al.
Extending Mercer's expansion to indefinite and asymmetric kernels
Sungwoo Jeong, Alex Townsend
Certifying Language Model Robustness with Fuzzed Randomized Smoothing: An Efficient Defense Against Backdoor Attacks
Bowei He, Lihao Yin, Huiling Zhen et al.
The importance of feature preprocessing for differentially private linear optimization
Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
Training-Free Dataset Pruning for Instance Segmentation
Yalun Dai, Lingao Xiao, Ivor Tsang et al.
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning
Moonseok Choi, Hyungi Lee, Giung Nam et al.
UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation
Alexander Liu, Sang-gil Lee, Chao-Han Huck Yang et al.
The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation
Fredrik Carlsson, Fangyu Liu, Daniel Ward et al.
Copyright-Protected Language Generation via Adaptive Model Fusion
Javier Abad, Konstantin Donhauser, Francesco Pinto et al.
Transferring Learning Trajectories of Neural Networks
Daiki Chijiwa
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory
Jan Drgona, Mahantesh Halappanavar, Frank Liu et al.
Non-Equilibrium Dynamics of Hybrid Continuous-Discrete Ground-State Sampling
Timothee Leleu, Sam Reifenstein
Precise Parameter Localization for Textual Generation in Diffusion Models
Łukasz Staniszewski, Bartosz Cywiński, Franziska Boenisch et al.
Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
Devon Jarvis, Richard Klein, Benjamin Rosman et al.
MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction
Cheng Tan, Zhenxiao Cao, Zhangyang Gao et al.
Unlocking the Potential of Model Calibration in Federated Learning
Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour et al.
Memory Efficient Transformer Adapter for Dense Predictions
Dong Zhang, Rui Yan, Pingcheng Dong et al.
Training-Free Message Passing for Learning on Hypergraphs
Bohan Tang, Zexi Liu, Keyue Jiang et al.
A Primal-Dual Approach to Solving Variational Inequalities with General Constraints
Tatjana Chavdarova, Tong Yang, Matteo Pagliardini et al.
A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization
Kim Youwang, Lee Hyun, Kim Sung-Bin et al.
Learning to Plan Before Answering: Self-Teaching LLMs to Learn Abstract Plans for Problem Solving
Jin Zhang, Flood Sung, Zhilin Yang et al.
Learning Mask Invariant Mutual Information for Masked Image Modeling
Tao Huang, Yanxiang Ma, Shan You et al.
Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition
Sangyu Han, Yearim Kim, Nojun Kwak
Visually Consistent Hierarchical Image Classification
Seulki Park, Youren Zhang, Stella Yu et al.
DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking head Video Generation
Hanbo Cheng, Limin Lin, Chenyu Liu et al.
Range, not Independence, Drives Modularity in Biologically Inspired Representations
Will Dorrell, Kyle Hsu, Luke Hollingsworth et al.
Improved algorithm and bounds for successive projection
Jiashun Jin, Tracy Ke, Gabriel Moryoussef et al.
Quality over Quantity in Attention Layers: When Adding More Heads Hurts
Noah Amsel, Gilad Yehudai, Joan Bruna
Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images
Yubo Wang, Jianting Tang, Liu et al.
Tree Search-Based Policy Optimization under Stochastic Execution Delay
David Valensi, Esther Derman, Shie Mannor et al.
Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning
Théo Vincent, Fabian Wahren, Jan Peters et al.
Transformer Learns Optimal Variable Selection in Group-Sparse Classification
Chenyang Zhang, Xuran Meng, Yuan Cao
ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models
Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky et al.
Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies
Yongxin Guo, Xiaoying Tang, Tao Lin
State Space Model Meets Transformer: A New Paradigm for 3D Object Detection
Chuxin Wang, Wenfei Yang, Xiang Liu et al.
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection
Lei Shen, Zhenheng Tang, Lijun Wu et al.
Augmented Bayesian Policy Search
Mahdi Kallel, Debabrota Basu, Riad Akrour et al.
ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models
Sunghyeon Woo, SunWoo Lee, Dongsuk Jeon
Personalized Representation from Personalized Generation
Shobhita Sundaram, Julia Chae, Yonglong Tian et al.
Do Deep Neural Network Solutions Form a Star Domain?
Ankit Sonthalia, Alexander Rubinstein, Ehsan Abbasnejad et al.
Lagrangian Flow Networks for Conservation Laws
Fabricio Arend Torres, Marcello Negri, Marco Inversi et al.
Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution
Simiao Li, Yun Zhang, Wei Li et al.
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
Hyunji Jung, Hanseul Cho, Chulhee Yun
Robust Simulation-Based Inference under Missing Data via Neural Processes
Yogesh Verma, Ayush Bharti, Vikas Garg
Pursuing Better Decision Boundaries for Long-Tailed Object Detection via Category Information Amount
Yanbiao Ma, Wei Dai, Jiayi Chen
Can Video LLMs Refuse to Answer? Alignment for Answerability in Video Large Language Models
Eunseop Yoon, Hee Suk Yoon, Mark Hasegawa-Johnson et al.
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Vindula Jayawardana, Baptiste Freydt, Ao Qu et al.
STAFF: Speculative Coreset Selection for Task-Specific Fine-tuning
Xiaoyu Zhang, Juan Zhai, Shiqing Ma et al.
HyPoGen: Optimization-Biased Hypernetworks for Generalizable Policy Generation
Hanxiang Ren, Li Sun, Xulong Wang et al.
ReGen: Generative Robot Simulation via Inverse Design
Peter (Phat) Nguyen, Johnson (Tsun-Hsuan) Wang, Zhang-Wei Hong et al.
Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks
Zi Wang, Divyam Anshumaan, Ashish Hooda et al.
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
Shaopeng Fu, Di Wang
Complexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness
Michael Crawshaw, Mingrui Liu
Enhancing Robust Fairness via Confusional Spectral Regularization
Gaojie Jin, Sihao Wu, Jiaxu Liu et al.
Time-Varying Propensity Score to Bridge the Gap between the Past and Present
Rasool Fakoor, Jonas Mueller, Zachary Lipton et al.
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
Linus Bleistein, Agathe Guilloux
Robust Angular Synchronization via Directed Graph Neural Networks
Yixuan He, Gesine Reinert, David Wipf et al.
Advantage-Guided Distillation for Preference Alignment in Small Language Models
Shiping Gao, Fanqi Wan, Jiajian Guo et al.
A Quadratic Synchronization Rule for Distributed Deep Learning
Xinran Gu, Kaifeng Lyu, Sanjeev Arora et al.
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption
Joonsung Jeon, Woo Jae Kim, Suhyeon Ha et al.
Modeling Boundedly Rational Agents with Latent Inference Budgets
Athul Jacob, Abhishek Gupta, Jacob Andreas
Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference
Anton Xue, Avishree Khare, Rajeev Alur et al.
SBSC: Step-by-Step Coding for Improving Mathematical Olympiad Performance
Kunal Singh, Ankan Biswas, Sayandeep Bhowmick et al.
Causal-StoNet: Causal Inference for High-Dimensional Complex Data
Yaxin Fang, Faming Liang
Adversarial Mixup Unlearning
Zhuoyi Peng, Yixuan Tang, Yi Yang
Flow-based Variational Mutual Information: Fast and Flexible Approximations
Caleb Dahlke, Jason Pacheco
Occlusion-aware Non-Rigid Point Cloud Registration via Unsupervised Neural Deformation Correntropy
Mingyang Zhao, Gaofeng Meng, Dong-ming Yan
Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
Haoran Deng, Yang Yang, Jiahe Li et al.
Learning Hierarchical Polynomials of Multiple Nonlinear Features
Hengyu Fu, Zihao Wang, Eshaan Nichani et al.
Retrieval Augmented Diffusion Model for Structure-informed Antibody Design and Optimization
Zichen Wang, Yaokun Ji, Jianing Tian et al.
PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction
Shangyu Chen, Zizheng Pan, Jianfei Cai et al.
Noisy Test-Time Adaptation in Vision-Language Models
Chentao Cao, Zhun Zhong, (Andrew) Zhanke Zhou et al.
Selective Unlearning via Representation Erasure Using Domain Adversarial Training
Nazanin Sepahvand, Eleni Triantafillou, Hugo Larochelle et al.
Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference
Anpeng Wu, Haiyi Qiu, Zhengming Chen et al.
Conflict-Averse Gradient Aggregation for Constrained Multi-Objective Reinforcement Learning
Dohyeong Kim, Mineui Hong, Jeongho Park et al.
Safe and Robust Watermark Injection with a Single OoD Image
Shuyang Yu, Junyuan Hong, Haobo Zhang et al.
$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
Wenye Li, Jiacai Liu, Ke Wei
No Location Left Behind: Measuring and Improving the Fairness of Implicit Representations for Earth Data
Daniel Cai, Randall Balestriero
Graph Parsing Networks
Yunchong Song, Siyuan Huang, Xinbing Wang et al.
TEDDY: Trimming Edges with Degree-based Discrimination Strategy
Hyunjin Seo, Jihun Yun, Eunho Yang
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra
Roman Worschech, Bernd Rosenow
Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
Baiting Luo, Ava Pettet, Aron Laszka et al.
econSG: Efficient and Multi-view Consistent Open-Vocabulary 3D Semantic Gaussians
Can Zhang, Gim H Lee
Let's do the time-warp-attend: Learning topological invariants of dynamical systems
Noa Moriel, Matt Ricci, Mor Nitzan
Action abstractions for amortized sampling
Oussama Boussif, Léna Ezzine, Joseph Viviano et al.
FOSP: Fine-tuning Offline Safe Policy through World Models
Chenyang Cao, Yucheng Xin, Silang Wu et al.
BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards
Zhaohui JIANG, Xuening Feng, Paul Weng et al.
Rethinking Multiple-Instance Learning From Feature Space to Probability Space
Zhaolong Du, Shasha Mao, Xuequan Lu et al.
Multi-Dimensional Conformal Prediction
Yam Tawachi, Bracha Laufer-Goldshtein
Understanding the Stability-based Generalization of Personalized Federated Learning
Yingqi Liu, Qinglun Li, Jie Tan et al.
Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps
Henry Li, Ronen Basri, Yuval Kluger
Oracle Efficient Algorithms for Groupwise Regret
Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan et al.
Probabilistic Geometric Principal Component Analysis with application to neural data
Han-Lin Hsieh, Maryam Shanechi
Robust Conformal Prediction with a Single Binary Certificate
Soroush H. Zargarbashi, Aleksandar Bojchevski
Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
Hengyu Fu, Zehao Dou, Jiawei Guo et al.
ChroKnowledge: Unveiling Chronological Knowledge of Language Models in Multiple Domains
Yein Park, Chanwoong Yoon, Jungwoo Park et al.
BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge Distillation
Zhengrui Guo, Fangxu Zhou, Wei Wu et al.
Differentially private learners for heterogeneous treatment effects
Maresa Schröder, Valentyn Melnychuk, Stefan Feuerriegel
Forget the Data and Fine-Tuning! Just Fold the Network to Compress
Dong Wang, Haris Šikić, Lothar Thiele et al.
Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning
Jingyang Li, Jiachun Pan, Vincent Tan et al.
An Effective Theory of Bias Amplification
Arjun Subramonian, Samuel Bell, Levent Sagun et al.
Exploiting Distribution Constraints for Scalable and Efficient Image Retrieval
Mohammad Omama, Po-han Li, Sandeep Chinchali
Re-Aligning Language to Visual Objects with an Agentic Workflow
Yuming Chen, Jiangyan Feng, Haodong Zhang et al.
An Exploration with Entropy Constrained 3D Gaussians for 2D Video Compression
Xiang Liu, Bin Chen, Zimo Liu et al.
Defining Expertise: Applications to Treatment Effect Estimation
Alihan Hüyük, Qiyao Wei, Alicia Curth et al.
Rethinking Classifier Re-Training in Long-Tailed Recognition: Label Over-Smooth Can Balance
Siyu Sun, Han Lu, Jiangtong Li et al.
Principled Architecture-aware Scaling of Hyperparameters
Wuyang Chen, Junru Wu, Zhangyang Wang et al.
Dimension Agnostic Neural Processes
Hyungi Lee, Chaeyun Jang, Dong Bok Lee et al.
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
Saptarshi Chakraborty, Peter Bartlett
Training Free Exponential Context Extension via Cascading KV Cache
Jeff Willette, Heejun Lee, Youngwan Lee et al.
Charting the Design Space of Neural Graph Representations for Subgraph Matching
Vaibhav Raj, Indradyumna Roy, Ashwin Ramachandran et al.
Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Transformers
Shaobo Wang, Hongxuan Tang, Mingyang Wang et al.
SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting
Huajian Huang, Yingshu Chen, Longwei Li et al.
Partial Gromov-Wasserstein Metric
Yikun Bai, Rocio Diaz Martin, Abihith Kothapalli et al.
CL-MFAP: A Contrastive Learning-Based Multimodal Foundation Model for Molecular Property Prediction and Antibiotic Screening
Gen Zhou, Sugitha Janarthanan, Yutong Lu et al.
Linear Bandits with Memory
Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Jasmine Bayrooti, Carl Ek, Amanda Prorok
Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models
Negin Raoof, Litu Rout, Giannis Daras et al.
Designing Mechanical Meta-Materials by Learning Equivariant Flows
Mehran Mirramezani, Anne Meeussen, Katia Bertoldi et al.
Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning
Hyungkyu Kang, Min-hwan Oh
GNeRP: Gaussian-guided Neural Reconstruction of Reflective Objects with Noisy Polarization Priors
LI Yang, RUIZHENG WU, Jiyong Li et al.
Approximation algorithms for combinatorial optimization with predictions
Antonios Antoniadis, Marek Elias, Adam Polak et al.
SIM: Surface-based fMRI Analysis for Inter-Subject Multimodal Decoding from Movie-Watching Experiments
Simon Dahan, Gabriel Bénédict, Logan Williams et al.
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
Firas Al-Hafez, Guoping Zhao, Jan Peters et al.
Learning to Steer Markovian Agents under Model Uncertainty
Jiawei Huang, Vinzenz Thoma, Zebang Shen et al.
3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D Editing
Jiahua Dong, Yu-Xiong Wang
Online Reinforcement Learning in Non-Stationary Context-Driven Environments
Pouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf et al.
Towards Synergistic Path-based Explanations for Knowledge Graph Completion: Exploration and Evaluation
Tengfei Ma, Xiang song, Wen Tao et al.
Accurate and Scalable Graph Neural Networks via Message Invariance
Zhihao Shi, Jie Wang, Zhiwei Zhuang et al.
Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision
Yaowen Ye, Cassidy Laidlaw, Jacob Steinhardt
Neural Phylogeny: Fine-Tuning Relationship Detection among Neural Networks
Runpeng Yu, Xinchao Wang
Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition
Jean-Rémy Conti, Stephan CLEMENCON
Classification with Conceptual Safeguards
Hailey Joren, Charles Marx, Berk Ustun
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
Samet Demir, Zafer Dogan
AugKD: Ingenious Augmentations Empower Knowledge Distillation for Image Super-Resolution
Yun Zhang, Wei Li, Simiao Li et al.
PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
Utsav Singh, Vinay Purushothaman Namboodiri
Learning to Solve Differential Equation Constrained Optimization Problems
Vincenzo Di Vito Francesco, Mostafa Mohammadian, Kyri Baker et al.
Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate
Miao Lu, Beining Wu, Xiaodong Yang et al.
Representational Similarity via Interpretable Visual Concepts
Neehar Kondapaneni, Oisin Mac Aodha, Pietro Perona
Nonlinear multiregion neural dynamics with parametric impulse response communication channels
Matthew Dowling, Cristina Savin
Adaptive Camera Sensor for Vision Models
Eunsu Baek, Sung-hwan Han, Taesik Gong et al.
Chunk-Distilled Language Modeling
Yanhong Li, Karen Livescu, Jiawei Zhou
Neural Spacetimes for DAG Representation Learning
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T Law et al.
Morphing Tokens Draw Strong Masked Image Models
Taekyung Kim, Byeongho Heo, Dongyoon Han
Storybooth: Training-Free Multi-Subject Consistency for Improved Visual Storytelling
Jaskirat Singh, Junshen K Chen, Jonas Kohler et al.
Learning Regularized Graphon Mean-Field Games with Unknown Graphons
Fengzhuo Zhang, Vincent Tan, Zhaoran Wang et al.
SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning
Lei You, Hei Victor Cheng
Counterfactual Realizability
Arvind Raghavan, Elias Bareinboim
MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion
Onkar Susladkar, Jishu Sen Gupta, Chirag Sehgal et al.
Uncovering Gaps in How Humans and LLMs Interpret Subjective Language
Erik Jones, Arjun Patrawala, Jacob Steinhardt
Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks
Bhaskar Mukhoty, Hilal AlQuabeh, Bin Gu
Distribution-Free Data Uncertainty for Neural Network Regression
Domokos M. Kelen, Ádám Jung, Péter Kersch et al.
Shadow Cones: A Generalized Framework for Partial Order Embeddings
Tao Yu, Toni Liu, Albert Tseng et al.
Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods
Hossein Taheri, Christos Thrampoulidis, Arya Mazumdar
Learning Color Equivariant Representations
Yulong Yang, Felix O'Mahony, Christine Allen-Blanchette
Kronecker Mask and Interpretive Prompts are Language-Action Video Learners
Jingyi Yang, Zitong YU, Nixiuming et al.
Disentangled Representation Learning with the Gromov-Monge Gap
Théo Uscidda, Luca Eyring, Karsten Roth et al.
SoftMatcha: A Soft and Fast Pattern Matcher for Billion-Scale Corpus Searches
Hiroyuki Deguchi, Go Kamoda, Yusuke Matsushita et al.
Moner: Motion Correction in Undersampled Radial MRI with Unsupervised Neural Representation
Qing Wu, Chenhe Du, Xuanyu Tian et al.
Aligning Visual Contrastive learning models via Preference Optimization
Amirabbas Afzali, Borna khodabandeh, Ali Rasekh et al.
Adaptive backtracking for faster optimization
Joao V. Cavalcanti, Laurent Lessard, Ashia Wilson
Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video
Xiangming Zhu, Huayu Deng, Haochen Yuan et al.
EFFICIENT JAILBREAK ATTACK SEQUENCES ON LARGE LANGUAGE MODELS VIA MULTI-ARMED BANDIT-BASED CONTEXT SWITCHING
Aditya Ramesh, Shivam Bhardwaj, Aditya Saibewar et al.
The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric
Daniel Severo, Lucas Theis, Johannes Ballé
GSBA$^K$: $top$-$K$ Geometric Score-based Black-box Attack
Md Farhamdur Reza, Richeng Jin, Tianfu Wu et al.
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
Milad Sefidgaran, Abdellatif Zaidi, Piotr Krasnowski
Horizon-Free Regret for Linear Markov Decision Processes
Zihan Zhang, Jason Lee, Yuxin Chen et al.
Learning Shape-Independent Transformation via Spherical Representations for Category-Level Object Pose Estimation
Huan Ren, Wenfei Yang, Xiang Liu et al.
Vision CNNs trained to estimate spatial latents learned similar ventral-stream-aligned representations
Yudi Xie, Weichen Huang, Esther Alter et al.
PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
Sunghyeon Woo, Sol Namkung, SunWoo Lee et al.
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
Indraneil Paul, Haoyi Yang, Goran Glavaš et al.
MuHBoost: Multi-Label Boosting For Practical Longitudinal Human Behavior Modeling
Nguyen Thach, Patrick Habecker, Anika Eisenbraun et al.
Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient
Wenlong Wang, Ivana Dusparic, Yucheng Shi et al.
PETRA: Parallel End-to-end Training with Reversible Architectures
Stéphane Rivaud, Louis Fournier, Thomas Pumir et al.
Unsupervised Meta-Learning via In-Context Learning
Anna Vettoruzzo, Lorenzo Braccaioli, Joaquin Vanschoren et al.