Most Cited ICML "roadside perception systems" Papers
5,975 papers found • Page 23 of 30
Conference
An Empirical Study of Realized GNN Expressiveness
Yanbo Wang, Muhan Zhang
Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning
Wenke Huang, Zekun Shi, Mang Ye et al.
Bottleneck-Minimal Indexing for Generative Document Retrieval
Xin Du, Lixin Xiu, Kumiko Tanaka-Ishii
EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens
Sunil Hwang, Jaehong Yoon, Youngwan Lee et al.
STELLA: Continual Audio-Video Pre-training with SpatioTemporal Localized Alignment
Jaewoo Lee, Jaehong Yoon, Wonjae Kim et al.
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
Daeun Lee, Jaehong Yoon, Sung Ju Hwang
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation
Danny Halawi, Alexander Wei, Eric Wallace et al.
What is Dataset Distillation Learning?
William Yang, Ye Zhu, Zhiwei Deng et al.
DPZero: Private Fine-Tuning of Language Models without Backpropagation
Liang Zhang, Bingcong Li, Kiran Thekumparampil et al.
Sampling in Unit Time with Kernel Fisher-Rao Flow
Aimee Maurais, Youssef Marzouk
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks
Duy Nguyen, Nina Lukashina, Tai Nguyen et al.
Hidden Traveling Waves bind Working Memory Variables in Recurrent Neural Networks
Arjun Karuvally, Terrence Sejnowski, Hava Siegelmann
Disentangled 3D Scene Generation with Layout Learning
Dave Epstein, Ben Poole, Ben Mildenhall et al.
A New Computationally Efficient Algorithm to solve Feature Selection for Functional Data Classification in High-dimensional Spaces
Tobia Boschi, FRANCESCA BONIN, Rodrigo Ordonez-Hurtado et al.
A Sparsity Principle for Partially Observable Causal Representation Learning
Danru Xu, Dingling Yao, Sébastien Lachapelle et al.
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations
Henrik Schopmans, Pascal Friederich
Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization
Hao Wang, Kaifeng Yang, Michael Affenzeller
Understanding Forgetting in Continual Learning with Linear Regression
Meng Ding, Kaiyi Ji, Di Wang et al.
Quality-Diversity with Limited Resources
Ren-Jian Wang, Ke Xue, Cong Guan et al.
On the Independence Assumption in Neurosymbolic Learning
Emile van Krieken, Pasquale Minervini, Edoardo Ponti et al.
diff History for Neural Language Agents
Ulyana Piterbarg, Lerrel Pinto, Rob Fergus
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi et al.
CuTS: Customizable Tabular Synthetic Data Generation
Mark Vero, Mislav Balunovic, Martin Vechev
Mimicking Better by Matching the Approximate Action Distribution
Joao A. Candido Ramos, Lionel Blondé, Naoya Takeishi et al.
Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches
David Glukhov, Ilia Shumailov, Yarin Gal et al.
Bifurcated Attention for Single-Context Large-Batch Sampling
Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda et al.
Smoothing Proximal Gradient Methods for Nonsmooth Sparsity Constrained Optimization: Optimality Conditions and Global Convergence
Ganzhao Yuan
Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
Parand A. Alamdari, Toryn Q. Klassen, Elliot Creager et al.
Predictive Linear Online Tracking for Unknown Targets
Anastasios Tsiamis, Aren Karapetyan, Yueshan Li et al.
Sub-token ViT Embedding via Stochastic Resonance Transformers
Dong Lao, Yangchao Wu, Tian Yu Liu et al.
Graph2Tac: Online Representation Learning of Formal Math Concepts
Lasse Blaauwbroek, Mirek Olšák, Jason Rute et al.
Accelerated Speculative Sampling Based on Tree Monte Carlo
Zhengmian Hu, Heng Huang
Random Latent Exploration for Deep Reinforcement Learning
Srinath Mahankali, Zhang-Wei Hong, Ayush Sekhari et al.
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
Haohui Wang, Yuzhen Mao, Yujun Yan et al.
Active Statistical Inference
Tijana Zrnic, Emmanuel J Candes
Protein Conformation Generation via Force-Guided SE(3) Diffusion Models
YAN WANG, Lihao Wang, Yuning Shen et al.
Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration
Xiong-Hui Chen, Junyin Ye, Hang Zhao et al.
SILVER: Single-loop variance reduction and application to federated learning
Kazusato Oko, Shunta Akiyama, Denny Wu et al.
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution
Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon
InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning
Zhe Huang, Xiaowei Yu, Dajiang Zhu et al.
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
Md Musfiqur Rahman, Murat Kocaoglu
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
Yuwei Fu, Haichao Zhang, di wu et al.
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna et al.
Directly Denoising Diffusion Models
Dan Zhang, Jingjing Wang, Feng Luo
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Aaditya Singh, Ted Moskovitz, Feilx Hill et al.
Out-of-Domain Generalization in Dynamical Systems Reconstruction
Niclas Göring, Florian Hess, Manuel Brenner et al.
Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel
Uri Gadot, Kaixin Wang, Navdeep Kumar et al.
TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
Xiwen Chen, Peijie Qiu, Wenhui Zhu et al.
New Sample Complexity Bounds for Sample Average Approximation in Heavy-Tailed Stochastic Programming
Hongcheng Liu, Jindong Tong
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
Dachun Kai, Jiayao Lu, Yueyi Zhang et al.
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras et al.
SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization
Jialong Guo, Xinghao Chen, Yehui Tang et al.
Learning to Route Among Specialized Experts for Zero-Shot Generalization
Mohammed Muqeeth, Haokun Liu, Yufan Liu et al.
Fast Adversarial Attacks on Language Models In One GPU Minute
Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan et al.
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
Kaizhao Liu, Jose Blanchet, Lexing Ying et al.
EvIL: Evolution Strategies for Generalisable Imitation Learning
Silvia Sapora, Gokul Swamy, Christopher Lu et al.
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
Fahim Tajwar, Anikait Singh, Archit Sharma et al.
Probabilistic Constrained Reinforcement Learning with Formal Interpretability
YANRAN WANG, QIUCHEN QIAN, David Boyle
Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds
Noémie Jaquier, Leonel Rozo, Miguel González-Duque et al.
Light and Optimal Schrödinger Bridge Matching
Nikita Gushchin, Sergei Kholkin, Evgeny Burnaev et al.
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu et al.
Offline Training of Language Model Agents with Functions as Learnable Weights
Shaokun Zhang, Jieyu Zhang, Jiale Liu et al.
Error Feedback Can Accurately Compress Preconditioners
Ionut-Vlad Modoranu, Aleksei Kalinov, Eldar Kurtic et al.
AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios
Zhongzhan Huang, Mingfu Liang, Shanshan Zhong et al.
Ameliorate Spurious Correlations in Dataset Condensation
Jiaxing Cui, Ruochen Wang, Yuanhao Xiong et al.
Optimistic Multi-Agent Policy Gradient
Wenshuai Zhao, Yi Zhao, Zhiyuan Li et al.
Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast
Xiangming Gu, Xiaosen Zheng, Tianyu Pang et al.
Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing
Gabriel Arpino, Xiaoqi Liu, Ramji Venkataramanan
DITTO: Diffusion Inference-Time T-Optimization for Music Generation
Zachary Novack, Julian McAuley, Taylor Berg-Kirkpatrick et al.
Position: Technical Research and Talent is Needed for Effective AI Governance
Anka Reuel, Lisa Soder, Benjamin Bucknall et al.
Fast Sampling-Based Sketches for Tensors
William Swartworth, David Woodruff
Graph Neural Networks Use Graphs When They Shouldn't
Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach et al.
AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors
Yucen Wang, Shenghua Wan, Le Gan et al.
Data-free Distillation of Diffusion Models with Bootstrapping
Jiatao Gu, Chen Wang, Shuangfei Zhai et al.
Stochastic Interpolants with Data-Dependent Couplings
Michael Albergo, Mark Goldstein, Nicholas Boffi et al.
Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction
Chen-Yu Yen, raghav singhal, Umang Sharma et al.
COALA: A Practical and Vision-Centric Federated Learning Platform
Weiming Zhuang, Jian Xu, Chen Chen et al.
Arrows of Time for Large Language Models
Vassilis Papadopoulos, Jérémie Wenger, Clement Hongler
Overcoming Saturation in Density Ratio Estimation by Iterated Regularization
Lukas Gruber, Markus Holzleitner, Johannes Lehner et al.
FADAS: Towards Federated Adaptive Asynchronous Optimization
Yujia Wang, Shiqiang Wang, Songtao Lu et al.
Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network
Hyunseok Oh, Youngki Lee
Theoretical Analysis of Learned Database Operations under Distribution Shift through Distribution Learnability
Sepanta Zeighami, Cyrus Shahabi
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction
yang zhang, Zhewei Wei, Ye Yuan et al.
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization
Sam Reifenstein, Timothee Leleu, Yoshihisa Yamamoto
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations
Kailas Vodrahalli, James Zou
Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
Gergely Neu, Nneka Okolo
Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation
Weiming Liu, Xiaolin Zheng, Chaochao Chen et al.
Understanding Finetuning for Factual Knowledge Extraction
Gaurav Ghosal, Tatsunori Hashimoto, Aditi Raghunathan
Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning
Lirong Wu, Yijun Tian, Haitao Lin et al.
The Pitfalls of Next-Token Prediction
Gregor Bachmann, Vaishnavh Nagarajan
Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models
Som Sagar, Aditya Taparia, Ransalu Senanayake
Navigating Scaling Laws: Compute Optimality in Adaptive Model Training
Sotiris Anagnostidis, Gregor Bachmann, Imanol Schlag et al.
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
Bingheng Li, Linxin Yang, Yupeng Chen et al.
Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought
Zhen-Yu Zhang, Siwei Han, Huaxiu Yao et al.
Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
Toru Shirakawa, Yi Li, Yulun Wu et al.
Accelerating Federated Learning with Quick Distributed Mean Estimation
Ran Ben Basat, Shay Vargaftik, Amit Portnoy et al.
Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning
Jinsoo Yoo, Yunpeng Liu, Frank Wood et al.
Fast Peer Adaptation with Context-aware Exploration
Long Ma, Yuanfei Wang, Fangwei Zhong et al.
Learning to Infer Generative Template Programs for Visual Concepts
R. Kenny Jones, Siddhartha Chaudhuri, Daniel Ritchie
Dual Operating Modes of In-Context Learning
Ziqian Lin, Kangwook Lee
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
Xiang Cheng, Yuxin Chen, Suvrit Sra
Unveiling the Dynamics of Information Interplay in Supervised Learning
Kun Song, Zhiquan Tan, Bochao Zou et al.
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
Yair Schiff, Chia Hsiang Kao, Aaron Gokaslan et al.
Integrating Global Context Contrast and Local Sensitivity for Blind Image Quality Assessment
Xudong Li, Runze Hu, Jingyuan Zheng et al.
Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity
Xudong Li, Timin Gao, Runze Hu et al.
Can AI Assistants Know What They Don't Know?
Qinyuan Cheng, Tianxiang Sun, Xiangyang Liu et al.
Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery
Yassir Jedra, William Réveillard, Stefan Stojanovic et al.
Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration
Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim et al.
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
Undral Byambadalai, Tatsushi Oka, Shota Yasui
Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning
Bowen Zheng, Da-Wei Zhou, Han-Jia Ye et al.
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models
Jinhao Li, Haopeng Li, Sarah Erfani et al.
Learning to Explore in POMDPs with Informational Rewards
Annie Xie, Logan M. Bhamidipaty, Evan Liu et al.
Can Mamba Learn How To Learn? A Comparative Study on In-Context Learning Tasks
Jong Ho Park, Jaden Park, Zheyang Xiong et al.
Structure Your Data: Towards Semantic Graph Counterfactuals
Angeliki Dimitriou, Maria Lymperaiou, Giorgos Filandrianos et al.
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
Yizhe Huang, Anji Liu, Fanqi Kong et al.
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
Nikhil Sardana, Jacob Portes, Alexandre (Sasha) Doubov et al.
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
Shangda Yang, Vitaly Zankin, Maximilian Balandat et al.
Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization
Haocheng Xi, Yuxiang Chen, Kang Zhao et al.
Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity
Hyunki Seong, Hyunchul Shim
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling
Yuxuan Yin, Yu Wang, Peng Li
Observable Propagation: Uncovering Feature Vectors in Transformers
Jacob Dunefsky, Arman Cohan
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
Yuhui Li, Fangyun Wei, Chao Zhang et al.
PAGER: Accurate Failure Characterization in Deep Regression Models
Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Puja Trivedi et al.
Interpreting Equivariant Representations
Andreas Abildtrup Hansen, Anna Calissano, Aasa Feragen
Risk Estimation in a Markov Cost Process: Lower and Upper Bounds
Gugan Chandrashekhar Mallika Thoppe, Prashanth L.A., Sanjay Bhat
Physics and Lie symmetry informed Gaussian processes
David Dalton, Dirk Husmeier, Hao Gao
Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension
Fan Yin, Jayanth Srinivasa, Kai-Wei Chang
On the Trajectory Regularity of ODE-based Diffusion Sampling
Defang Chen, Zhenyu Zhou, Can Wang et al.
CF-OPT: Counterfactual Explanations for Structured Prediction
Germain Vivier-Ardisson, Alexandre Forel, Axel Parmentier et al.
Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds
Yuyang Zhang, Shahriar Talebi, Na Li
RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation
Mahdi Nikdan, Soroush Tabesh, Elvir Crnčević et al.
Otter: Generating Tests from Issues to Validate SWE Patches
Toufique Ahmed, Jatin Ganhotra, Rangeet Pan et al.
Power Mean Estimation in Stochastic Continuous Monte-Carlo Tree Search
Tuan Dam
Position: The Future of Bayesian Prediction Is Prior-Fitted
Samuel Gabriel Müller, Arik Reuter, Noah Hollmann et al.
Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong et al.
Contrastive Visual Data Augmentation
Yu Zhou, Bingxuan Li, Mohan Tang et al.
From Logits to Hierarchies: Hierarchical Clustering made Simple
Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser et al.
FedSSI: Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence
Yichen Li, Yuying Wang, Haozhao Wang et al.
Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives
Elliot Meyerson, Xin Qiu
Low-Rank Tensor Transitions (LoRT) for Transferable Tensor Regression
Andong Wang, Yuning Qiu, Zhong Jin et al.
StealthInk: A Multi-bit and Stealthy Watermark for Large Language Models
Ya Jiang, Chuxiong Wu, Massieh Kordi Boroujeny et al.
Inverse Optimization via Learning Feasible Regions
Ke Ren, Peyman Mohajerin Esfahani, Angelos Georghiou
GRAIL: Graph Edit Distance and Node Alignment using LLM-Generated Code
Samidha Verma, Arushi Goyal, Ananya Mathur et al.
Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points
Justin Lee, Behnaz Moradi-Jamei, Heman Shakeri
Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel Images
Zhengrui Guo, Qichen Sun, Jiabo MA et al.
Meta-Black-Box-Optimization through Offline Q-function Learning
Zeyuan Ma, Zhiguang Cao, Zhou Jiang et al.
Determinant Estimation under Memory Constraints and Neural Scaling Laws
Siavash Ameli, Chris van der Heide, Liam Hodgkinson et al.
Inverse Bridge Matching Distillation
Nikita Gushchin, David Li, Daniil Selikhanovych et al.
A Non-isotropic Time Series Diffusion Model with Moving Average Transitions
Chenxi Wang, Linxiao Yang, Zhixian Wang et al.
Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
RISHI JINKA, Venkata Sai Mothish Gonugunta, Deepak N. Subramani
SAND: One-Shot Feature Selection with Additive Noise Distortion
Pedram Pad, Hadi Hammoud, Mohamad Dia et al.
Unpaired Point Cloud Completion via Unbalanced Optimal Transport
Taekyung Lee, Jaemoo Choi, Jaewoong Choi et al.
Online Curvature-Aware Replay: Leveraging $\mathbf{2^{nd}}$ Order Information for Online Continual Learning
Edoardo Urettini, Antonio Carta
Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models
Xin Zou, Yizhou WANG, Yibo Yan et al.
Guided Search Strategies in Non-Serializable Environments with Applications to Software Engineering Agents
Karina Zainullina, Aleksandr Golubev, Maria Trofimova et al.
Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
Yeseul Cho, Baekrok Shin, Changmin Kang et al.
Discrete Neural Algorithmic Reasoning
Gleb Rodionov, Liudmila Prokhorenkova
TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree
Yu-Yang Qian, Yuan-Ze Xu, Zhen-Yu Zhang et al.
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane et al.
An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints
Jiahui Zhu, Kihyun Yu, Dabeen Lee et al.
KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors
Benson Chen, Tomasz Danel, Gabriel Dreiman et al.
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca et al.
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach
Changdae Oh, zhen fang, Shawn Im et al.
Towards a Formal Theory of Representational Compositionality
Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio et al.
Reinforcement Learning with Adaptive Reward Modeling for Expensive-to-Evaluate Systems
Hongyuan Su, Yu Zheng, Yuan Yuan et al.
Differentiable Structure Learning with Ancestral Constraints
Taiyu Ban, Changxin Rong, Xiangyu Wang et al.
MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
Sebastian Farquhar, Vikrant Varma, David Lindner et al.
Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations
Aditya Taparia, Som Sagar, Ransalu Senanayake
Robust Secure Swap: Responsible Face Swap With Persons of Interest Redaction and Provenance Traceability
Yunshu Dai, Jianwei Fei, Fangjun Huang et al.
Stronger Neyman Regret Guarantees for Adaptive Experimental Design
Georgy Noarov, Riccardo Fogliato, Martin A Bertran et al.
When, Where and Why to Average Weights?
Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping
BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
Yunlong Hou, Fengzhuo Zhang, Cunxiao Du et al.
Minimum Width for Universal Approximation using Squashable Activation Functions
Jonghyun Shin, Namjun Kim, Geonho Hwang et al.
On the Learnability of Distribution Classes with Adaptive Adversaries
Tosca Lechner, Alex Bie, Gautam Kamath
Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs
Xun Wang, Jing Xu, Franziska Boenisch et al.
Towards Attributions of Input Variables in a Coalition
Xinhao Zheng, Huiqi Deng, Quanshi Zhang
B-score: Detecting biases in large language models using response history
An Vo, Mohammad Reza Taesiri, Daeyoung Kim et al.
Discovering Spoofing Attempts on Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab et al.
Integration-free Kernels for Equivariant Gaussian Process Modelling
Tim Steinert, David Ginsbourger, August Lykke-Møller et al.
Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments
Mikel Malagón, Josu Ceberio, Jose A Lozano
Discovering Physics Laws of Dynamical Systems via Invariant Function Learning
Shurui Gui, Xiner Li, Shuiwang Ji
Human-Aligned Image Models Improve Visual Decoding from the Brain
Nona Rajabi, Antonio Ribeiro, Miguel Vasco et al.
Test-Time Learning for Large Language Models
Jinwu Hu, Zitian Zhang, Guohao Chen et al.
The Batch Complexity of Bandit Pure Exploration
Adrienne Tuynman, Rémy Degenne
ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks
Saurabh Jha, Rohan Arora, Yuji Watanabe et al.
NeuralCohort: Cohort-aware Neural Representation Learning for Healthcare Analytics
Changshuo Liu, Lingze Zeng, Kaiping Zheng et al.
Private Federated Learning using Preference-Optimized Synthetic Data
Charlie Hou, Mei-Yu Wang, Yige Zhu et al.
EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations
Haotian Zhai, Connor Lawless, Ellen Vitercik et al.
Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves
Amer Krivosija, Alexander Munteanu, André Nusser et al.
Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach
Xu Zhang, Kaidi Xu, Ziqing Hu et al.
A Generic Family of Graphical Models: Diversity, Efficiency, and Heterogeneity
Yufei Huang, Changhu Wang, Junjie Tang et al.
TabFlex: Scaling Tabular Learning to Millions with Linear Attention
Yuchen Zeng, Tuan Dinh, Wonjun Kang et al.
Efficiently Vectorized MCMC on Modern Accelerators
Hugh Dance, Pierre Glaser, Peter Orbanz et al.
Understanding Complexity in VideoQA via Visual Program Generation
Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave et al.
Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Lukas Pirch, Felix Weissberg et al.
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
Yitian Zhang, Liheng Ma, Antonios Valkanas et al.
Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective
Steve Azzolin, SAGAR MALHOTRA, Andrea Passerini et al.
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik et al.
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
Jiawei Zhang, Xuan Yang, Taiqi Wang et al.
Nemotron-CORTEXA: Enhancing LLM Agents for Software Engineering Tasks via Improved Localization and Solution Diversity
Atefeh Sohrabizadeh, Jialin Song, Mingjie Liu et al.