Most Cited ICML "cross-modal selection" Papers
5,975 papers found • Page 25 of 30
Conference
Learnware Specification via Dual Alignment
Wei Chen, Jun-Xiang Mao, Xiaozheng Wang et al.
Causal Inference out of Control: Estimating Performativity without Treatment Randomization
Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
Let LLM Tell What to Prune and How Much to Prune
Mingzhe Yang, Sihao Lin, Changlin Li et al.
On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning
Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li
Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?
Yilong Wang, Haishan Ye, Guang Dai et al.
Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification
Jay Gala, Pengtao Xie
Data-free Neural Representation Compression with Riemannian Neural Dynamics
Zhengqi Pei, Anran Zhang, Shuhui Wang et al.
Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li et al.
Position: Constants are Critical in Regret Bounds for Reinforcement Learning
Simone Drago, Marco Mussi, Alberto Maria Metelli
Position: When Incentives Backfire, Data Stops Being Human
Sebastin Santy, Prasanta Bhattacharya, Manoel Ribeiro et al.
Position: Explainable AI Cannot Advance Without Better User Studies
Matej Pičulin, Bernarda Petek, Irena Ograjenšek et al.
Joint Localization and Activation Editing for Low-Resource Fine-Tuning
Wen Lai, Alexander Fraser, Ivan Titov
Position: Formal Mathematical Reasoning—A New Frontier in AI
Kaiyu Yang, Gabriel Poesia, Jingxuan He et al.
Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived
Yuhe Guo, Huayi Tang, Jiahong Ma et al.
Position: General Intelligence Requires Reward-based Pretraining
Seungwook Han, Jyothish Pari, Samuel Gershman et al.
M³HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
Ziyan Wang, Zhicheng Zhang, Fei Fang et al.
Position: Not All Explanations for Deep Learning Phenomena Are Equally Valuable
Alan Jeffares, Mihaela van der Schaar
Position: The Categorization of Race in ML is a Flawed Premise
Miriam Doh, Benedikt Höltgen, Piera Riccio et al.
Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus Kirkman, Graham Todd et al.
Position: Strong Consumer Protection is an Inalienable Defense for AI Safety in the United States
Serena Booth
Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods
Yedi Zhang, Yufan Cai, Xinyue Zuo et al.
GiLOT: Interpreting Generative Language Models via Optimal Transport
Xuhong Li, Jiamin Chen, Yekun Chai et al.
Symmetry-Robust 3D Orientation Estimation
Christopher Scarvelis, David Benhaim, Paul Zhang
Time Series Representations with Hard-Coded Invariances
Thibaut Germain, Chrysoula Kosma, Laurent Oudre
Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
Zhenglin Wan, Xingrui Yu, David Bossens et al.
Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly From Data
Krzysztof Kacprzyk, Julianna Piskorz, Mihaela van der Schaar
Unified Screening for Multiple Diseases
Yiğit Narter, Alihan Hüyük, Mihaela van der Schaar et al.
Attention-Level Speculation
Jack Cai, Ammar Vora, Randolph Zhang et al.
An Explicit Frame Construction for Normalizing 3D Point Clouds
Justin Baker, Shih-Hsin Wang, Tommaso de Fernex et al.
Telling Peer Direct Effects from Indirect Effects in Observational Network Data
Xiaojing Du, Jiuyong Li, Debo Cheng et al.
Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations
Jeet Mohapatra, Nima Dehmamy, Csaba Both et al.
Coresets for Multiple $\ell_p$ Regression
David Woodruff, Taisuke Yasuda
A Unified Adaptive Testing System Enabled by Hierarchical Structure Search
Junhao Yu, Yan Zhuang, Zhenya Huang et al.
Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data
Kishan Panaganti, Adam Wierman, Eric Mazumdar
Rényi Neural Processes
Xuesong Wang, He Zhao, Edwin V. Bonilla
How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective
Keyan Miao, Konstantinos Gatsis
Robust Sparsification via Sensitivity
Chansophea Wathanak In, Yi Li, David Woodruff et al.
Action Dubber: Timing Audible Actions via Inflectional Flow
Wenlong Wan, Weiying Zheng, Tianyi Xiang et al.
Editing Partially Observable Networks via Graph Diffusion Models
Puja Trivedi, Ryan A Rossi, David Arbour et al.
Meta Evidential Transformer for Few-Shot Open-Set Recognition
Hitesh Sapkota, Krishna Neupane, Qi Yu
Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers
Alireza Amiribavandpour, Xinting Huang, Mark Rofin et al.
Exploring Representations and Interventions in Time Series Foundation Models
Michal Wilinski, Mononito Goswami, Willa Potosnak et al.
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
Ningyi Liao, Zihao Yu, Ruixiao Zeng et al.
Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
Yucen Li, Daohan Lu, Polina Kirichenko et al.
Position: Social Environment Design Should be Further Developed for AI-based Policy-Making
Edwin Zhang, Sadie Zhao, Tonghan Wang et al.
Return Capping: Sample Efficient CVaR Policy Gradient Optimisation
Harry Mead, Clarissa Costen, Bruno Lacerda et al.
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability
Michael Crawshaw, Blake Woodworth, Mingrui Liu
Score-of-Mixture Training: One-Step Generative Model Training Made Simple via Score Estimation of Mixture Distributions
Tejas Jayashankar, Jongha (Jon) Ryu, Gregory Wornell
Cell2Sentence: Teaching Large Language Models the Language of Biology
Daniel Levine, Syed Rizvi, Sacha Lévy et al.
The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks
Songhua He, Periklis Papakonstantinou
Augmenting Decision with Hypothesis in Reinforcement Learning
Nguyen Minh Quang, Hady Lauw
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu et al.
Position: AI Safety should prioritize the Future of Work
Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty
Contrastive Predict-and-Search for Mixed Integer Linear Programs
Taoan Huang, Aaron Ferber, Arman Zharmagambetov et al.
A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
Zachary Roch, George Atia, Yue Wang
AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training
Li Ding, Wen Fei, Yuyang Huang et al.
Cross-City Latent Space Alignment for Consistency Region Embedding
Meng Chen, Hongwei Jia, Zechen Li et al.
Gridded Transformer Neural Processes for Spatio-Temporal Data
Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal, Sattar Vakili, Laura Toni et al.
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.
Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning
Zhiyao Zhang, Myeung Suk Oh, Hairi et al.
Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI
Francisco Eiras, Aleksandar Petrov, Bertie Vidgen et al.
Complexity Matters: Feature Learning in the Presence of Spurious Correlations
GuanWen Qiu, Da Kuang, Surbhi Goel
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jimenez Gutierrez, Yiheng Shu, Weijian Qi et al.
What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
Ching-Yun (Irene) Ko, Pin-Yu Chen, Payel Das et al.
Position: Data-driven Discovery with Large Generative Models
Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal et al.
FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting
Yue Jiang, Yile Chen, Xiucheng Li et al.
S4S: Solving for a Fast Diffusion Model Solver
Eric Frankel, Sitan Chen, Jerry Li et al.
Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
Ze Cheng, Zhuoyu Li, Wang Xiaoqiang et al.
On Fine-Grained Distinct Element Estimation
Ilias Diakonikolas, Daniel Kane, Jasper Lee et al.
Reliable Algorithm Selection for Machine Learning-Guided Design
Clara Fannjiang, Ji Won Park
Position: Open-Endedness is Essential for Artificial Superhuman Intelligence
Edward Hughes, Michael Dennis, Jack Parker-Holder et al.
Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra
Alan Amin, Andres Potapczynski, Andrew Wilson
Position: Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work.
Aviv Ovadya, Kyle Redman, Luke Thorburn et al.
Position: Beyond Assistance – Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care
Abeer Badawi, Md Tahmid Rahman Laskar, Jimmy Huang et al.
Position: LLM Social Simulations Are a Promising Research Method
Jacy Anthis, Ryan Liu, Sean Richardson et al.
Position: A Safe Harbor for AI Evaluation and Red Teaming
Shayne Longpre, Sayash Kapoor, Kevin Klyman et al.
Evaluation of Trajectory Distribution Predictions with Energy Score
Novin Shahroudi, Mihkel Lepson, Meelis Kull
Position: Future Directions in the Theory of Graph Machine Learning
Christopher Morris, Fabrizio Frasca, Nadav Dym et al.
Position: We Can’t Understand AI Using our Existing Vocabulary
John Hewitt, Robert Geirhos, Been Kim
Position: Future Research and Challenges Remain Towards AI for Software Engineering
Alex Gu, Naman Jain, Wen-Ding Li et al.
Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
Jan Blechschmidt, Tom-Christian Riemer, Max Winkler et al.
Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It
Jillian Fisher, Ruth Elisabeth Appel, Chan Young Park et al.
Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks
Judy Hanwen Shen
Position: You Can't Manufacture a NeRF
Marta An Kimmel, Mueed Rehman, Yonatan Bisk et al.
Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images
Jun-Peng Jiang, Han-Jia Ye, Leye Wang et al.
Position: AI Agents Need Authenticated Delegation
Tobin South, Samuele Marro, Thomas Hardjono et al.
No Double Descent in Principal Component Regression: A High-Dimensional Analysis
Daniel Gedon, Antonio Ribeiro, Thomas Schön
Dynamic Facility Location in High Dimensional Euclidean Spaces
Sayan Bhattacharya, Gramoz Goranci, Shaofeng Jiang et al.
Defense against Backdoor Attack on Pre-trained Language Models via Head Pruning and Attention Normalization
Xingyi Zhao, Depeng Xu, Shuhan Yuan
Rethinking the Flat Minima Searching in Federated Learning
Taehwan Lee, Sung Whan Yoon
Counterfactual Graphical Models: Constraints and Inference
Juan Correa, Elias Bareinboim
Investigating the Overlooked Hessian Structure: From CNNs to LLMs
Qian-Yuan Tang, Yufei Gu, Yunfeng Cai et al.
AutoOS: Make Your OS More Powerful by Exploiting Large Language Models
Huilai Chen, Yuanbo Wen, Limin Cheng et al.
Gradient-based Visual Explanation for Transformer-based CLIP
Chenyang ZHAO, Kun Wang, Xingyu Zeng et al.
Performance Bounds for Active Binary Testing with Information Maximization
Aditya Chattopadhyay, Benjamin Haeffele, Rene Vidal et al.
DynaMind: Reasoning over Abstract Video Dynamics for Embodied Decision-Making
Ziru Wang, Mengmeng Wang, Jade Dai et al.
Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective
Yajie Bao, Michael Crawshaw, Mingrui Liu
Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning
Hongyao Chen, Tianyang Xu, Xiaojun Wu et al.
Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention
Jiaqi Zhang, Joel Jennings, Agrin Hilmkil et al.
Survival Analysis via Density Estimation
Hiroki Yanagisawa, Shunta Akiyama
AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning
Dong Chen, Hongyuan Qu, Guangwu Xu
One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment
Chaochao Chen, Jiaming Zhang, Yuyuan Li et al.
Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics
Ankit Vani, Frederick Tung, Gabriel Oliveira et al.
Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations
Stefan Sylvius Wagner Martinez, Stefan Harmeling
NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders
Jun-En Ding, Dongsheng Luo, Chenwei Wu et al.
Towards a Self-contained Data-driven Global Weather Forecasting Framework
Yi Xiao, LEI BAI, Wei Xue et al.
To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models
George-Octavian Bărbulescu, Peter Triantafillou
S$\Omega$I: Score-based O-INFORMATION Estimation
Mustapha BOUNOUA, Giulio Franzese, Pietro Michiardi
SGD Jittering: A Training Strategy for Robust and Accurate Model-Based Architectures
Peimeng Guan, Mark Davenport
The Berkeley Function Calling Leaderboard (BFCL): From Tool Use to Agentic Evaluation of Large Language Models
Shishir G. Patil, Huanzhi Mao, Fanjia Yan et al.
Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection
Nils Palumbo, Yang Guo, Xi Wu et al.
Position: On the Possibilities of AI-Generated Text Detection
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu et al.
DTZO: Distributed Trilevel Zeroth Order Learning with Provable Non-Asymptotic Convergence
Yang Jiao, Kai Yang, Chengtao Jian
MMInference: Accelerating Pre-filling for Long-Context Visual Language Models via Modality-Aware Permutation Sparse Attention
Yucheng Li, Huiqiang Jiang, Chengruidong Zhang et al.
PAGER: Accurate Failure Characterization in Deep Regression Models
Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Puja Trivedi et al.
NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits
Tushar Aggarwal, Swayam Singh, Abhijeet Awasthi et al.
Breaking Barriers: Combinatorial Algorithms for Non-Monotone Submodular Maximization with Sublinear Adaptivity and $1/e$ Approximation
Yixin Chen, Wenjing Chen, Alan Kuhnle
Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency
Yangfan Liu, JIAQI LYU, Xin Geng et al.
Robust Noise Attenuation via Adaptive Pooling of Transformer Outputs
Greyson Brothers
Active Ranking and Matchmaking, with Perfect Matchings
Hafedh El Ferchichi, Matthieu LERASLE, Vianney Perchet
Towards Neural Architecture Search through Hierarchical Generative Modeling
Lichuan Xiang, Łukasz Dudziak, Mohamed Abdelfattah et al.
Fluctuations of the largest eigenvalues of transformed spiked Wigner matrices
Aro Lee, Ji Oon Lee
Amortized Variational Deep Kernel Learning
Alan Matias, César Lincoln Mattos, Joao Paulo Gomes et al.
Policy Evaluation for Variance in Average Reward Reinforcement Learning
Shubhada Agrawal, Prashanth L.A., Siva Maguluri
SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP
Subhojyoti Mukherjee, Josiah Hanna, Robert Nowak
Gradient Descent Converges Arbitrarily Fast for Logistic Regression via Large and Adaptive Stepsizes
Ruiqi Zhang, Jingfeng Wu, Peter Bartlett
Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
Zhiyao Luo, Yangchen Pan, Peter Watkinson et al.
Graph Out-of-Distribution Detection Goes Neighborhood Shaping
Tianyi Bao, Qitian Wu, Zetian Jiang et al.
Consensus Is All You Get: The Role of Attention in Transformers
Alvaro Rodriguez Abella, João Pedro Silvestre, Paulo Tabuada
Position: On the Societal Impact of Open Foundation Models
Sayash Kapoor, Rishi Bommasani, Kevin Klyman et al.
Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition
Tong Wei, Zhen Mao, Zi-Hao Zhou et al.
Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Stochastic Bias and Remedies
Qiang Li, Michal Yemini, Hoi To Wai
Training Diffusion-based Generative Models with Limited Data
Zhaoyu Zhang, Yang Hua, Guanxiong Sun et al.
Optimizing Noise Distributions for Differential Privacy
Atefeh Gilani, Felipe Gomez, Shahab Asoodeh et al.
Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning
Wenke Huang, Zekun Shi, Mang Ye et al.
Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
Erchi Wang, Yuqing Zhu, Yu-Xiang Wang
Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL
Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi GNVV et al.
Faster Streaming and Scalable Algorithms for Finding Directed Dense Subgraphs in Large Graphs
Slobodan Mitrovic, Theodore Pan
Mahalanobis++: Improving OOD Detection via Feature Normalization
Maximilian Müller, Matthias Hein
Effect-Invariant Mechanisms for Policy Generalization
Sorawit Saengkyongam, Niklas Pfister, Predag Klasnja et al.
Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers
Lokesh Veeramacheneni, Moritz Wolter, Hilde Kuehne et al.
STELLA: Continual Audio-Video Pre-training with SpatioTemporal Localized Alignment
Jaewoo Lee, Jaehong Yoon, Wonjae Kim et al.
Putnam-AXIOM: A Functional & Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs
Aryan Gulati, Brando Miranda, Eric Chen et al.
Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning
Zhiwei XU, Kun Hu, Xin Xin et al.
Sampling from Binary Quadratic Distributions via Stochastic Localization
Chenguang Wang, Kaiyuan Cui, Weichen Zhao et al.
MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation
Bowen Tao, Xin-Chun Li, De-Chuan Zhan
Efficient Graph Continual Learning via Lightweight Graph Neural Tangent Kernels-based Dataset Distillation
Rihong Qiu, Xinke Jiang, Yuchen Fang et al.
Online Sparsification of Bipartite-Like Clusters in Graphs
Joyentanuj Das, Suranjan De, He Sun
Global-Local Dirichlet Processes for Clustering Grouped Data in the Presence of Group-Specific Idiosyncratic Variables
Arhit Chakrabarti, Yang Ni, Debdeep Pati et al.
What Makes In-context Learning Effective for Mathematical Reasoning
Jiayu Liu, Zhenya Huang, Chaokun Wang et al.
Improved Dimensionality Dependence for Zeroth-Order Optimisation over Cross-Polytopes
Weijia Shao
A Reasoning-Based Approach to Cryptic Crossword Clue Solving
Martin Andrews, Sam Witteveen
Hgformer: Hyperbolic Graph Transformer for Collaborative Filtering
Yang Xin, Xingrun Li, Heng Chang et al.
Position: Medical Large Language Model Benchmarks Should Prioritize Construct Validity
Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini et al.
Physics and Lie symmetry informed Gaussian processes
David Dalton, Dirk Husmeier, Hao Gao
Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy
Lucas Spangher, Allen Wang, Andrew Maris et al.
GMAIL: Generative Modality Alignment for generated Image Learning
Shentong Mo, Sukmin Yun
TopInG: Topologically Interpretable Graph Learning via Persistent Rationale Filtration
Cheng Xin, Fan Xu, Xin Ding et al.
Unifying Knowledge from Diverse Datasets to Enhance Spatial-Temporal Modeling: A Granularity-Adaptive Geographical Embedding Approach
Zhigaoyuan Wang, Ying Sun, Hengshu Zhu
Quantum Algorithms for Finite-horizon Markov Decision Processes
Bin Luo, Yuwen Huang, Jonathan Allcock et al.
Large Language Model-driven Large Neighborhood Search for Large-Scale MILP Problems
Huigen Ye, Hua Xu, An Yan et al.
MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future Knowledge
Yue Dai, Liang Liu, Xulong Tang et al.
The Power of Random Features and the Limits of Distribution-Free Gradient Descent
Ari Karchmer, Eran Malach
BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in Healthcare
Yanchao Tan, Hang Lv, Yunfei Zhan et al.
Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches
David Glukhov, Ilia Shumailov, Yarin Gal et al.
Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing
Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam et al.
Bifurcated Attention for Single-Context Large-Batch Sampling
Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda et al.
Breadth-First Exploration on Adaptive Grid for Reinforcement Learning
Youngsik Yoon, Gangbok Lee, Sungsoo Ahn et al.
Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering
Yaoqin He, Junchen Fu, Kaiwen Zheng et al.
PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction
Aaron Wenteler, Martina Occhetta, Nikhil Branson et al.
Safely Learning Optimal Auctions: A Testable Learning Framework for Mechanism Design
Vikram Kher, Manolis Zampetakis
GSM-$\infty$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?
Yang Zhou, Hongyi Liu, Zhuoming Chen et al.
FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials
Seung Lee, Hojoon Kim, Yutack Park et al.
Scalable Private Partition Selection via Adaptive Weighting
Justin Chen, Vincent Cohen-Addad, Alessandro Epasto et al.
Strong and Weak Identifiability of Optimization-based Causal Discovery in Non-linear Additive Noise Models
Mingjia Li, Hong Qian, Tian-Zuo Wang et al.
Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic Regressions
Supratim Shit, Gurmehak chadha, Surendra kumar et al.
Dynamic Metric Embedding into lp Space
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Dariusz Kowalski et al.
Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead
Won-Jun Jang, Hyeon-Seo Park, Si-Hyeon Lee
DIS-CO: Discovering Copyrighted Content in VLMs Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving
Yeonju Ro, Zhenyu Zhang, Souvik Kundu et al.
Federated Learning for Feature Generalization with Convex Constraints
Dongwon Kim, Donghee Kim, Sung Kuk Shyn et al.
Dynamic Similarity Graph Construction with Kernel Density Estimation
Steinar Laenen, Peter Macgregor, He Sun
The Emergence of Reproducibility and Consistency in Diffusion Models
Huijie Zhang, Jinfan Zhou, Yifu Lu et al.
Accelerated Speculative Sampling Based on Tree Monte Carlo
Zhengmian Hu, Heng Huang
MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification
Suchith Chidananda Prabhu, Bhavyajeet Singh, Anshul Mittal 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.
Policy-conditioned Environment Models are More Generalizable
Ruifeng Chen, Xiong-Hui Chen, Yihao Sun et al.
SILVER: Single-loop variance reduction and application to federated learning
Kazusato Oko, Shunta Akiyama, Denny Wu et al.
Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems
Botao Chen, Jongyeong Lee, Junya Honda
InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning
Zhe Huang, Xiaowei Yu, Dajiang Zhu et al.
EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption
Leo de Castro, Daniel Escudero, Adya Agrawal et al.
Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification
Martin Mihelich, François Castagnos, Charles Dognin
One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
Gabriel Kasmi, Amandine Brunetto, Thomas Fel 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.
Flow Matching for Few-Trial Neural Adaptation with Stable Latent Dynamics
Puli Wang, Yu Qi, Yueming Wang et al.
Online Learning in Risk Sensitive constrained MDP
Arnob Ghosh, Mehrdad Moharrami
The Best of Both Worlds: Bridging Quality and Diversity in Data Selection with Bipartite Graph
Minghao Wu, Thuy-Trang Vu, Lizhen Qu et al.
Adaptive Data Collection for Robust Learning Across Multiple Distributions
Chengbo Zang, Mehmet Turkcan, Gil Zussman et al.
Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms
Kei Sen Fong, Mehul Motani