Most Cited ICML "remote sensing applications" Papers

KoNODE: Koopman-Driven Neural Ordinary Differential Equations with Evolving Parameters for Time Series Analysis

Hanru Bai, Weiyang Ding

Structure Is All You Need: Structural Representation Learning on Hyper-Relational Knowledge Graphs

Jaejun Lee, Joyce Whang

Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection

Zhiyuan Yan, Jiangming Wang, Peng Jin et al.

Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic Transforms

Julius Von Rohrscheidt, Bastian Rieck

Stability and Generalization Capability of Subgraph Reasoning Models for Inductive Knowledge Graph Completion

Minsung Hwang, Jaejun Lee, Joyce Whang

Revisiting Unbiased Implicit Variational Inference

Tobias Pielok, Bernd Bischl, David Rügamer

LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits

Zikai Zhou, Qizheng Zhang, Hermann Kumbong et al.

Discovering Latent Causal Graphs from Spatiotemporal Data

Kun Wang, Sumanth Varambally, Duncan Watson-Parris et al.

How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic Segmentation

Yining Pan, Qiongjie Cui, Xulei Yang et al.

Causal Invariance-aware Augmentation for Brain Graph Contrastive Learning

Minqi Yu, Jinduo Liu, Junzhong Ji

Learnable Spatial-Temporal Positional Encoding for Link Prediction

Katherine Tieu, Dongqi Fu, Zihao Li et al.

Causality-Aware Contrastive Learning for Robust Multivariate Time-Series Anomaly Detection

HyunGi Kim, Jisoo Mok, Dong Jun Lee et al.

One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation

Zhendong Wang, Max Li, Ajay Mandlekar et al.

Flopping for FLOPs: Leveraging Equivariance for Computational Efficiency

Georg Bökman, David Nordström, Fredrik Kahl

Angle Domain Guidance: Latent Diffusion Requires Rotation Rather Than Extrapolation

Cheng Jin, Zhenyu Xiao, Chutao Liu et al.

Contract Design Under Approximate Best Responses

Francesco Bacchiocchi, Jiarui Gan, Matteo Castiglioni et al.

A Closer Look at Backdoor Attacks on CLIP

Shuo He, Zhifang Zhang, Feng Liu et al.

PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation

Albert Gong, Kamilė Stankevičiūtė, Chao Wan et al.

Conformal Anomaly Detection in Event Sequences

Shuai Zhang, Chuan Zhou, Yang Liu et al.

SAN: Hypothesizing Long-Term Synaptic Development and Neural Engram Mechanism in Scalable Model's Parameter-Efficient Fine-Tuning

Gaole Dai, Chun-Kai Fan, Yiming Tang et al.

Learning Invariant Causal Mechanism from Vision-Language Models

Zeen Song, Siyu Zhao, Xingyu Zhang et al.

Leveraging Predictive Equivalence in Decision Trees

Hayden McTavish, Zachery Boner, Jon Donnelly et al.

CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention

Han Li, Fei Liu, Zhi Zheng et al.

VCT: Training Consistency Models with Variational Noise Coupling

Gianluigi Silvestri, Luca Ambrogioni, Chieh-Hsin Lai et al.

Learning from True-False Labels via Multi-modal Prompt Retrieving

Zhongnian Li, Jinghao Xu, Peng Ying et al.

RAGGED: Towards Informed Design of Scalable and Stable RAG Systems

Jennifer Hsia, Afreen Shaikh, Zhiruo Wang et al.

ParallelComp: Parallel Long-Context Compressor for Length Extrapolation

Jing Xiong, Jianghan Shen, Chuanyang Zheng et al.

Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization

Zijian Liu, Zhengyuan Zhou

Topological Signatures of Adversaries in Multimodal Alignments

Minh Vu, Geigh Zollicoffer, Huy Mai et al.

Accelerated Diffusion Models via Speculative Sampling

Valentin De Bortoli, Alexandre Galashov, Arthur Gretton et al.

Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Zhenni Bi, Kai Han, Chuanjian Liu et al.

Predictive Performance of Deep Quantum Data Re-uploading Models

Xin Wang, Hanxiao Tao, Re-Bing Wu

Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes

Bhargav Ganguly, Yang Xu, Vaneet Aggarwal

Visual and Domain Knowledge for Professional-level Graph-of-Thought Medical Reasoning

Rina Bao, Shilong Dong, Zhenfang Chen et al.

Knowledge Swapping via Learning and Unlearning

Mingyu Xing, Lechao Cheng, Shengeng Tang et al.

Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees

William de Vazelhes, Xiaotong Yuan, Bin Gu

Teaching Physical Awareness to LLMs through Sounds

Weiguo Wang, Andy Nie, Wenrui Zhou et al.

Explicit Exploration for High-Welfare Equilibria in Game-Theoretic Multiagent Reinforcement Learning

Austin Nguyen, Anri Gu, Michael Wellman

Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces

Kevin Rojas, Yuchen Zhu, Sichen Zhu et al.

Memory Layers at Scale

Vincent-Pierre Berges, Barlas Oğuz, Daniel HAZIZA et al.

Autoencoder-Based Hybrid Replay for Class-Incremental Learning

Milad Khademi Nori, Il-Min Kim, Guanghui Wang

Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors

Jing Huang, Junyi Tao, Thomas Icard et al.

SERENA: A Unified Stochastic Recursive Variance Reduced Gradient Framework for Riemannian Non-Convex Optimization

Yan Liu, Mingjie Chen, Chaojie Ji et al.

Progressively Label Enhancement for Large Language Model Alignment

Biao Liu, Ning Xu, Xin Geng

Byzantine-Resilient Federated Alternating Gradient Descent and Minimization for Partly-Decoupled Low Rank Matrix Learning

Ankit Pratap Singh, Ahmed Abbasi, Namrata Vaswani

SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes

Yishan Shen, Yuyang Ye, Hui Xiong et al.

Scaling Large Motion Models with Million-Level Human Motions

Ye Wang, Sipeng Zheng, Bin Cao et al.

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache

Rishabh Tiwari, Haocheng Xi, Aditya Tomar et al.

Decomposition of Graphic Design with Unified Multimodal Model

Hui Nie, Zhao Zhang, Yutao Cheng et al.

Kinetic Langevin Diffusion for Crystalline Materials Generation

François Cornet, Federico Bergamin, Arghya Bhowmik et al.

A Manifold Perspective on the Statistical Generalization of Graph Neural Networks

Zhiyang Wang, Juan Cervino, Alejandro Ribeiro

SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference

Jintao Zhang, Chendong Xiang, Haofeng Huang et al.

$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting

Xingjian Wu, Xiangfei Qiu, Hongfan Gao et al.

Polynomial-Delay MAG Listing with Novel Locally Complete Orientation Rules

Tian-Zuo Wang, Wen-Bo Du, Zhi-Hua Zhou

Earley-Driven Dynamic Pruning for Efficient Structured Decoding

Xintong Sun, Chi Wei, Minghao Tian et al.

An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks

Valentyn Boreiko, Alexander Panfilov, Václav Voráček et al.

FDGen: A Fairness-Aware Graph Generation Model

Zichong Wang, Wenbin Zhang

Enhancing Foundation Models with Federated Domain Knowledge Infusion

Jiaqi Wang, Jingtao Li, Weiming Zhuang et al.

"Who experiences large model decay and why?" A Hierarchical Framework for Diagnosing Heterogeneous Performance Drift

Harvineet Singh, Fan Xia, Alexej Gossmann et al.

Great Models Think Alike and this Undermines AI Oversight

Shashwat Goel, Joschka Strüber, Ilze Amanda Auzina et al.

Mixture of Experts Made Intrinsically Interpretable

Xingyi Yang, Constantin Venhoff, Ashkan Khakzar et al.

Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer

Yihang Wang, Yuying Qiu, Peng Chen et al.

Peripheral Memory for LLMs: Integration of Sequential Memory Banks with Adaptive Querying

Songlin Zhai, Yuan Meng, Yongrui Chen et al.

Learn Singularly Perturbed Solutions via Homotopy Dynamics

Chuqi CHEN, Yahong Yang, Yang Xiang et al.

A Simple Model of Inference Scaling Laws

Noam Levi

CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion Models

Sen Peng, Mingyue Wang, Jianfei He et al.

CAD-Editor: A Locate-then-Infill Framework with Automated Training Data Synthesis for Text-Based CAD Editing

Yu Yuan, Shizhao Sun, Qi Liu et al.

TimeStacker: A Novel Framework with Multilevel Observation for Capturing Nonstationary Patterns in Time Series Forecasting

Qinglong Liu, Cong Xu, Wenhao Jiang et al.

AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration

Wenhao SUN, Rong-Cheng Tu, Jingyi Liao et al.

Random Registers for Cross-Domain Few-Shot Learning

Shuai Yi, Yixiong Zou, Yuhua Li et al.

Sparse Autoencoders for Hypothesis Generation

Rajiv Movva, Kenny Peng, Nikhil Garg et al.

A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Attention Networks

Biswadeep Chakraborty, Harshit Kumar, Saibal Mukhopadhyay

Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation

Kosuke Nakanishi, Akihiro Kubo, Yuji Yasui et al.

Algorithm Development in Neural Networks: Insights from the Streaming Parity Task

Loek van Rossem, Andrew Saxe

Improving LLM Video Understanding with 16 Frames Per Second

Yixuan Li, Changli Tang, Jimin Zhuang et al.

MAS-GPT: Training LLMs to Build LLM-based Multi-Agent Systems

Rui Ye, shuo tang, Rui Ge et al.

Emergence in non-neural models: grokking modular arithmetic via average gradient outer product

Neil Mallinar, Daniel Beaglehole, Libin Zhu et al.

Agent-Centric Actor-Critic for Asynchronous Multi-Agent Reinforcement Learning

Whiyoung Jung, Sunghoon Hong, Deunsol Yoon et al.

Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach

Qian Peng, Yajie Bao, Haojie Ren et al.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting

Zhining Liu, Ze Yang, Xiao Lin et al.

Latent Action Learning Requires Supervision in the Presence of Distractors

Alexander Nikulin, Ilya Zisman, Denis Tarasov et al.

Understanding and Improving Length Generalization in Recurrent Models

Ricardo Buitrago Ruiz, Albert Gu

Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation

Juno Kim, Denny Wu, Jason Lee et al.

A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings

Shib S Dasgupta, Michael Boratko, Andrew McCallum

SPD: Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models

Han-Byul Kim, Duc Hoang, Arnav Kundu et al.

Mitigating Local Cohesion and Global Sparseness in Graph Contrastive Learning with Fuzzy Boundaries

Yuena Lin, Haichun Cai, Jun-Yi Hang et al.

Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding

Mingyu Jin, Kai Mei, Wujiang Xu et al.

A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models

Shivam Kumar, Yun Yang, Lizhen Lin

Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning

Cheol Kim, Jai Moondra, Shresth Verma et al.

Revisiting Differentially Private Algorithms for Decentralized Online Learning

Xiaoyu Wang, Wenhao Yang, Chang Yao et al.

Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework

Guan Huang, Tao Shu

sciLaMA: A Single-Cell Representation Learning Framework to Leverage Prior Knowledge from Large Language Models

Hongru Hu, Shuwen Zhang, Yongin Choi et al.

Procurement Auctions via Approximately Optimal Submodular Optimization

Yuan Deng, Amin Karbasi, Vahab Mirrokni et al.

Understanding Nonlinear Implicit Bias via Region Counts in Input Space

Jingwei Li, Jing Xu, Zifan Wang et al.

Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization

Zishun Yu, Tengyu Xu, Di Jin et al.

Position: Stop treating `AGI' as the north-star goal of AI research

Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li et al.

COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain Adaptation

Wenxu Wang, Rui Zhou, Jing Wang et al.

How Do Large Language Monkeys Get Their Power (Laws)?

Rylan Schaeffer, Joshua Kazdan, John Hughes et al.

Taming Knowledge Conflicts in Language Models

Gaotang Li, Yuzhong Chen, Hanghang Tong

Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language Models

Shizhan Gong, Yankai Jiang, DOU QI et al.

IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction

Zhangyi Hu, Jiemin Wu, Hua XU et al.

Generalized additive models via direct optimization of regularized decision stump forests

Magzhan Gabidolla, Miguel Carreira-Perpinan

Improving Parallel Program Performance with LLM Optimizers via Agent-System Interfaces

Anjiang Wei, Allen Nie, Thiago Teixeira et al.

Demystifying Singular Defects in Large Language Models

Haoqi Wang, Tong Zhang, Mathieu Salzmann

ToMA: Token Merge with Attention for Diffusion Models

Wenbo Lu, Shaoyi Zheng, Yuxuan Xia et al.

Efficient Length-Generalizable Attention via Causal Retrieval for Long-Context Language Modeling

Xiang Hu, Zhihao Teng, Jun Zhao et al.

SyncMind: Measuring Agent Out-of-Sync Recovery in Collaborative Software Engineering

Xuehang Guo, Xingyao Wang, Yangyi Chen et al.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates

Yunfei Huang, David S. Greenberg

Cross-Modal Alignment via Variational Copula Modelling

Feng Wu, Tsai Hor Chan, Fuying Wang et al.

Prompt-to-Leaderboard: Prompt-Adaptive LLM Evaluations

Evan Frick, Connor Chen, Joseph Tennyson et al.

The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking

Yuchun Miao, Sen Zhang, Liang Ding et al.

Flexibility-conditioned protein structure design with flow matching

Vsevolod Viliuga, Leif Seute, Nicolas Wolf et al.

GRADEO: Towards Human-Like Evaluation for Text-to-Video Generation via Multi-Step Reasoning

Zhun Mou, Bin Xia, Zhengchao Huang et al.

Compressing tree ensembles through Level-wise Optimization and Pruning

Laurens Devos, Timo Martens, Deniz Oruc et al.

Kernel Quantile Embeddings and Associated Probability Metrics

Masha Naslidnyk, Siu Lun Chau, Francois-Xavier Briol et al.

TeLoGraF: Temporal Logic Planning via Graph-encoded Flow Matching

Yue Meng, Chuchu Fan

Towards characterizing the value of edge embeddings in Graph Neural Networks

Dhruv Rohatgi, Tanya Marwah, Zachary Lipton et al.

IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck

Tian Bian, Yifan Niu, Chaohao Yuan et al.

DexScale: Automating Data Scaling for Sim2Real Generalizable Robot Control

Guiliang Liu, Yueci Deng, Runyi Zhao et al.

FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable Training

Filipp Zmushko, Aleksandr Beznosikov, Martin Takac et al.

Generative Data Mining with Longtail-Guided Diffusion

David Hayden, Mao Ye, Timur Garipov et al.

Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation

Hongyi Zhou, Josiah Hanna, Jin Zhu et al.

MetricEmbedding: Accelerate Metric Nearness by Tropical Inner Product

Muyang Cao, Jiajun Yu, Xin Du et al.

The Illusion of Role Separation: Hidden Shortcuts in LLM Role Learning (and How to Fix Them)

Zihao Wang, Yibo Jiang, Jiahao Yu et al.

Playmate: Flexible Control of Portrait Animation via 3D-Implicit Space Guided Diffusion

Xingpei Ma, Jiaran Cai, Yuansheng Guan et al.

SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training

Chao Ma, Wenbo Gong, Meyer Scetbon et al.

Generalization Performance of Ensemble Clustering: From Theory to Algorithm

Xu Zhang, Haoye Qiu, Weixuan Liang et al.

Near-Optimal Sample Complexity for MDPs via Anchoring

Jongmin Lee, Mario Bravo, Roberto Cominetti

Efficient Robotic Policy Learning via Latent Space Backward Planning

Dongxiu Liu, Haoyi Niu, Zhihao Wang et al.

Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence

Yinbin Han, Meisam Razaviyayn, Renyuan Xu

Perceptually Constrained Precipitation Nowcasting Model

Wenzhi Feng, Xutao Li, Zhe Wu et al.

QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles for model-monitoring

Nikhil Pratap Ghanathe, Steve Wilton

Benchmarking Quantum Reinforcement Learning

Nico Meyer, Christian Ufrecht, George Yammine et al.

Is Complex Query Answering Really Complex?

Cosimo Gregucci, Bo Xiong, Daniel Hernández et al.

On Path to Multimodal Generalist: General-Level and General-Bench

Hao Fei, Yuan Zhou, Juncheng Li et al.

Improved Online Confidence Bounds for Multinomial Logistic Bandits

Joongkyu Lee, Min-hwan Oh

Variance as a Catalyst: Efficient and Transferable Semantic Erasure Adversarial Attack for Customized Diffusion Models

Jiachen Yang, Yusong Wang, Yanmei Fang et al.

Stabilizing Sample Similarity in Representation via Mitigating Random Consistency

Jieting Wang, ZhangZelong Zhang, Feijiang Li et al.

On Explaining Equivariant Graph Networks via Improved Relevance Propagation

Hongyi Ling, Haiyang Yu, Zhimeng Jiang et al.

WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales

Drew Prinster, Xing Han, Anqi Liu et al.

GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebras

Ekaterina Filimoshina, Dmitry Shirokov

Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models

Xiaoyu Wu, Jiaru Zhang, Steven Wu

Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups

Vladimir Kostic, Karim Lounici, Hélène Halconruy et al.

Position: Language model developers should report train-test overlap

Andy Zhang, Kevin Klyman, Yifan Mai et al.

Symmetry-Aware GFlowNets

Hohyun Kim, Seunggeun Lee, Min-hwan Oh

FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing

Yingying Deng, Xiangyu He, Changwang Mei et al.

DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications

Ibrahim Fayad, Max Zimmer, Martin Schwartz et al.

ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via $\alpha$-$\beta$-Divergence

Guanghui Wang, Zhiyong Yang, Zitai Wang et al.

FreeMesh: Boosting Mesh Generation with Coordinates Merging

Jian Liu, Haohan Weng, Biwen Lei et al.

Expected Variational Inequalities

Brian Zhang, Ioannis Anagnostides, Emanuel Tewolde et al.

Offline Opponent Modeling with Truncated Q-driven Instant Policy Refinement

Yuheng Jing, Kai Li, Bingyun Liu et al.

A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization

Nuojin Cheng, Leonard Papenmeier, Stephen Becker et al.

Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton

Chengmei Niu, Zhenyu Liao, Zenan Ling et al.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning

Zihan Chen, Song Wang, Zhen Tan et al.

Learning Strategic Language Agents in the Werewolf Game with Iterative Latent Space Policy Optimization

Zelai Xu, Wanjun Gu, Chao Yu et al.

MissScore: High-Order Score Estimation in the Presence of Missing Data

Wenqin Liu, Haoze Hou, Erdun Gao et al.

COMRECGC: Global Graph Counterfactual Explainer through Common Recourse

Gregoire Fournier, Sourav Medya

RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior

Ching-Hua Lee, Chouchang Yang, Jaejin Cho et al.

Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model

Rachel Cummings, Alessandro Epasto, Jieming Mao et al.

Multi-Objective Causal Bayesian Optimization

Shriya Bhatija, Paul-David Zuercher, Jakob Thumm et al.

An Efficient Private GPT Never Autoregressively Decodes

Zhengyi Li, Yue Guan, Kang Yang et al.

From Complex to Atomic: Enhancing Augmented Generation via Knowledge-Aware Dual Rewriting and Reasoning

Jinyu Wang, Jingjing Fu, Rui Wang et al.

Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization

Kyurae Kim, Zuheng Xu, Jacob Gardner et al.

Conformity Score Averaging for Classification

Rui Luo, Zhixin Zhou

GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation

Mengzhu Wang, houcheng su, Jiao Li et al.

Provable Zero-Shot Generalization in Offline Reinforcement Learning

Zhiyong Wang, Chen Yang, John C. S. Lui et al.

Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization

Shira Vansover-Hager, Tomer Koren, Roi Livni

FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning

Ganyu Wang, Jinjie Fang, Maxwell (Juncheng) Yin et al.

Generalizable Multi-Camera 3D Object Detection from a Single Source via Fourier Cross-View Learning

Xue Zhao, Qinying Gu, Xinbing Wang et al.

Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy

Haoqi Wu, Wei Dai, Wang Li et al.

Zero-Shot Generalization of GNNs over Distinct Attribute Domains

Yangyi Shen, Jincheng Zhou, Beatrice Bevilacqua et al.

Residual Matrix Transformers: Scaling the Size of the Residual Stream

Brian Mak, Jeffrey Flanigan

ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features

Alec Helbling, Tuna Han Salih Meral, Benjamin Hoover et al.

Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks

Rui Xue, Tong Zhao, Neil Shah et al.

SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification

Shuo Yang, Bardh Prenkaj, Gjergji Kasneci

Rectifying Conformity Scores for Better Conditional Coverage

Vincent Plassier, Alexander Fishkov, Victor Dheur et al.

LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models

Parshin Shojaee, Ngoc Hieu Nguyen, Kazem Meidani et al.

Retrieval-Augmented Language Model for Knowledge-aware Protein Encoding

Zhang Jiasheng, Delvin Zhang, Shuang Liang et al.

HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks

Learning to Route LLMs with Confidence Tokens

Yu-Neng Chuang, Prathusha Sarma, Parikshit Gopalan et al.

UnHiPPO: Uncertainty-aware Initialization for State Space Models

Marten Lienen, Abdullah Saydemir, Stephan Günnemann

Preference learning made easy: Everything should be understood through win rate

Lily Zhang, Rajesh Ranganath

Achieving Linear Speedup and Near-Optimal Complexity for Decentralized Optimization over Row-stochastic Networks

Liyuan Liang, Xinyi Chen, Gan Luo et al.

LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification

Hang Gao, Huang Wenxuan, Fengge Wu et al.

Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold

Yilong Song, Peijin Li, Bin Gao et al.

ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans

Ashkan Shahbazi, Elaheh Akbari, Darian Salehi et al.

Online Linear Classification with Massart Noise

Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos et al.

Stay-Positive: A Case for Ignoring Real Image Features in Fake Image Detection

Anirudh Sundara Rajan, Yong Jae Lee

InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective

Yuanhong Zhang, Muyao Yuan, Weizhan Zhang et al.

Interpreting the Repeated Token Phenomenon in Large Language Models

Itay Yona, Ilia Shumailov, Jamie Hayes et al.

Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series

Zachary Brown, David Carlson

Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks

Jeongmo Kim, Yisak Park, Minung Kim et al.

Right Time to Learn: Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation

Guanglong Sun, Hongwei Yan, Liyuan Wang et al.

Learning Safe Control via On-the-Fly Bandit Exploration

Alexandre Capone, Ryan Cosner, Aaron Ames et al.

LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning

Zihang Liu, Tianyu Pang, Oleg Balabanov et al.

Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling

Xinxing Shi, Xiaoyu Jiang, Mauricio Álvarez

Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation

He Li, Haoang Chi, Mingyu Liu et al.

Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning

Le-Trung Nguyen, Aël Quélennec, Van-Tam Nguyen et al.

Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts

Haoyang Li, Xin Wang, Xueling Zhu et al.

PASS: Private Attributes Protection with Stochastic Data Substitution

Yizhuo Chen, Chun-Fu (Richard) Chen, Hsiang Hsu et al.