Most Cited ICML "sparse attention computation" Papers
5,975 papers found • Page 6 of 30
Conference
Exploring Large Action Sets with Hyperspherical Embeddings using von Mises-Fisher Sampling
Walid Bendada, Guillaume Salha-Galvan, Romain Hennequin et al.
Confounder-Free Continual Learning via Recursive Feature Normalization
Yash Shah, Camila Gonzalez, MohammadHassan Abbasi et al.
Regression for the Mean: Auto-Evaluation and Inference with Few Labels through Post-hoc Regression
Benjamin Eyre, David Madras
Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance
Marta Gentiloni Silveri, Antonio Ocello
Label Distribution Propagation-based Label Completion for Crowdsourcing
Tong Wu, Liangxiao Jiang, Wenjun Zhang et al.
Adaptive Partitioning Schemes for Optimistic Optimization
Raja Sunkara, Ardhendu Tripathy
Average Certified Radius is a Poor Metric for Randomized Smoothing
Chenhao Sun, Yuhao Mao, Mark Müller et al.
CTBench: A Library and Benchmark for Certified Training
Yuhao Mao, Stefan Balauca, Martin Vechev
Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
Emiliano Penaloza, Tianyue Zhang, Laurent Charlin et al.
Cross-regularization: Adaptive Model Complexity through Validation Gradients
Carlos Stein Naves de Brito
Inverse problems with experiment-guided AlphaFold
Sai Advaith Maddipatla, Nadav Bojan, Meital Bojan et al.
CommVQ: Commutative Vector Quantization for KV Cache Compression
Junyan Li, Yang Zhang, Muhammad Yusuf Hassan et al.
Unveiling Markov heads in Pretrained Language Models for Offline Reinforcement Learning
Wenhao Zhao, Qiushui Xu, Linjie Xu et al.
Multi-Session Budget Optimization for Forward Auction-based Federated Learning
Xiaoli Tang, Han Yu, Zengxiang Li et al.
TraceGrad: a Framework Learning Expressive SO(3)-equivariant Non-linear Representations for Electronic-Structure Hamiltonian Prediction
Shi Yin, Xinyang Pan, fengyan wang et al.
Beyond Cropped Regions: New Benchmark and Corresponding Baseline for Chinese Scene Text Retrieval in Diverse Layouts
Li gengluo, Huawen Shen, Yu ZHOU
Efficient Federated Incomplete Multi-View Clustering
Suyuan Liu, Hao Yu, Hao Tan et al.
PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design
Zhenqiao Song, Tianxiao Li, Lei Li et al.
VerbalTS: Generating Time Series from Texts
Shuqi Gu, Chuyue Li, Baoyu Jing et al.
Improving Consistency Models with Generator-Augmented Flows
Thibaut Issenhuth, Sangchul Lee, Ludovic Dos Santos et al.
EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM
Zhuofan Zong, Dongzhi Jiang, Bingqi Ma et al.
Sample Complexity of Branch-length Estimation by Maximum Likelihood
David Clancy, Hanbaek Lyu, Sebastien Roch
MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning
Suning Huang, Zheyu Zhang, Tianhai Liang et al.
Lego Sketch: A Scalable Memory-augmented Neural Network for Sketching Data Streams
Yuan Feng, Yukun Cao, Hairu Wang et al.
Deep Streaming View Clustering
Honglin Yuan, Xingfeng Li, Jian Dai et al.
Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning
Zhenghai Xue, Lang Feng, Jiacheng Xu et al.
Feasible Action Search for Bandit Linear Programs via Thompson Sampling
Aditya Gangrade, Aldo Pacchiano, Clay Scott et al.
Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent
Santhosh Karnik, Anna Veselovska, Mark Iwen et al.
Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach
Jin Zhu, Jingyi Li, Hongyi Zhou et al.
Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques
Alon Arad, Saharon Rosset
Delay-DSGN: A Dynamic Spiking Graph Neural Network with Delay Mechanisms for Evolving Graph
Zhiqiang Wang, Jianghao Wen, Jianqing Liang
Structured Preconditioners in Adaptive Optimization: A Unified Analysis
Shuo Xie, Tianhao Wang, Sashank J. Reddi et al.
On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding
Kevin Xu, Issei Sato
T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling
Zhenyu Hou, Xin Lv, Rui Lu et al.
Benign Overfitting in Token Selection of Attention Mechanism
Keitaro Sakamoto, Issei Sato
Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents
Yifei Zhou, Qianlan Yang, Kaixiang Lin et al.
Conformal Tail Risk Control for Large Language Model Alignment
Catherine Chen, Jingyan Shen, Xinyu Yang et al.
Analytical Lyapunov Function Discovery: An RL-based Generative Approach
Haohan Zou, Jie Feng, Hao Zhao et al.
A Mixture-Based Framework for Guiding Diffusion Models
Yazid Janati, Badr MOUFAD, Mehdi Qassime et al.
GMAIL: Generative Modality Alignment for generated Image Learning
Shentong Mo, Sukmin Yun
Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan
Reducing Variance of Stochastic Optimization for Approximating Nash Equilibria in Normal-Form Games
Linjian Meng, Wubing Chen, Wenbin Li et al.
On the Power of Learning-Augmented Search Trees
Jingbang Chen, Xinyuan Cao, Alicia Stepin et al.
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N
Tianyu Zhang, Andrew Williams, Phillip Wozny et al.
FourierMamba: Fourier Learning Integration with State Space Models for Image Deraining
Dong Li, Yidi Liu, Xueyang Fu et al.
Separating Knowledge and Perception with Procedural Data
Adrian Rodriguez-Munoz, Manel Baradad, Phillip Isola et al.
Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data
Mohammad Hosseini, Maryam Shanechi
Stability and Generalization Analysis of Decentralized SGD: Sharper Bounds Beyond Lipschitzness and Smoothness
Shuang Zeng, Yunwen Lei
Position: Current Model Licensing Practices are Dragging Us into a Quagmire of Legal Noncompliance
Moming Duan, Mingzhe Du, Rui Zhao et al.
Understanding Chain-of-Thought in LLMs through Information Theory
Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu
How to set AdamW's weight decay as you scale model and dataset size
Xi Wang, Laurence Aitchison
Learn to Vaccinate: Combining Structure Learning and Effective Vaccination for Epidemic and Outbreak Control
Sepehr Elahi, Paula Mürmann, Patrick Thiran
High-Dimensional Tensor Regression With Oracle Properties
Wenbin Wang, Yu Shi, Ziping Zhao
Visual Autoregressive Modeling for Image Super-Resolution
Yunpeng Qu, Kun Yuan, Jinhua Hao et al.
Revisiting Cooperative Off-Policy Multi-Agent Reinforcement Learning
yueheng li, Guangming Xie, Zongqing Lu
In-Context Fine-Tuning for Time-Series Foundation Models
Matthew Faw, Rajat Sen, Yichen Zhou et al.
A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization
Kunjie Ren, Luo Luo
Accelerating Spectral Clustering under Fairness Constraints
Francesco Tonin, Alex Lambert, Johan Suykens et al.
A-PSRO: A Unified Strategy Learning Method with Advantage Metric for Normal-form Games
Yudong Hu, Haoran Li, Congying Han et al.
Quantum Algorithms for Finite-horizon Markov Decision Processes
Bin Luo, Yuwen Huang, Jonathan Allcock et al.
Inference-Time Alignment of Diffusion Models with Direct Noise Optimization
Zhiwei Tang, Jiangweizhi Peng, Jiasheng Tang et al.
Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax Optimization
Zhangyi Liu, Feng Liu, Rui Gao et al.
PDUDT: Provable Decentralized Unlearning under Dynamic Topologies
Jing Qiao, Yu Liu, Zengzhe Chen et al.
polybasic Speculative Decoding Through a Theoretical Perspective
Ruilin Wang, Huixia Li, Yuexiao Ma et al.
Learning Changes in Graphon Attachment Network Models
Xinyuan Fan, Bufan Li, Chenlei Leng et al.
Latent Variable Estimation in Bayesian Black-Litterman Models
Thomas Y.L. Lin, Jerry Yao-Chieh Hu, Wan-Jiun Paul Chiou et al.
Unnatural Languages Are Not Bugs but Features for LLMs
Keyu Duan, Yiran Zhao, Zhili Feng et al.
QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration
HamidReza Imani, Jiaxin Peng, Peiman Mohseni et al.
Aligning LLMs by Predicting Preferences from User Writing Samples
Stéphane Aroca-Ouellette, Natalie Mackraz, Barry-John Theobald et al.
Concept Reachability in Diffusion Models: Beyond Dataset Constraints
Marta Aparicio Rodriguez, Xenia Miscouridou, Anastasia Borovykh
Unifying Knowledge from Diverse Datasets to Enhance Spatial-Temporal Modeling: A Granularity-Adaptive Geographical Embedding Approach
Zhigaoyuan Wang, Ying Sun, Hengshu Zhu
One-Pass Feature Evolvable Learning with Theoretical Guarantees
Cun-Yuan Xing, Meng-Zhang Qian, Wu-Yang Chen et al.
SEAD: Unsupervised Ensemble of Streaming Anomaly Detectors
Saumya Gaurang Shah, Abishek Sankararaman, Balakrishnan Narayanaswamy et al.
COExpander: Adaptive Solution Expansion for Combinatorial Optimization
Jiale Ma, Wenzheng Pan, Yang Li et al.
Towards Understanding Parametric Generalized Category Discovery on Graphs
Bowen Deng, Lele Fu, Jialong Chen et al.
Understanding the Unfairness in Network Quantization
Bing Liu, wenjun Miao, Boyu Zhang et al.
MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future Knowledge
Yue Dai, Liang Liu, Xulong Tang et al.
Improving LLM Safety Alignment with Dual-Objective Optimization
Xuandong Zhao, Will Cai, Tianneng Shi et al.
Adversarial Robustness via Deformable Convolution with Stochasticity
Yanxiang Ma, Zixuan Huang, Minjing Dong et al.
Independence Tests for Language Models
Sally Zhu, Ahmed Ahmed, Rohith Kuditipudi et al.
Online Conformal Prediction via Online Optimization
Felipe Areces, Christopher Mohri, Tatsunori Hashimoto et al.
Causal Attribution Analysis for Continuous Outcomes
Shanshan Luo, Yu yixuan, Chunchen LIU et al.
Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation
D. Sculley, William Cukierski, Phil Culliton et al.
Robust Multi-bit Text Watermark with LLM-based Paraphrasers
Xiaojun Xu, jinghan jia, Yuanshun Yao et al.
Deep Bayesian Filter for Bayes-Faithful Data Assimilation
Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda
Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion
Binchi Zhang, Zaiyi Zheng, Zhengzhang Chen et al.
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
KaShun SHUM, Yuzhen Huang, Hongjian Zou et al.
Backdoor Attacks in Token Selection of Attention Mechanism
Yunjuan Wang, Raman Arora
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal et al.
Model-Based Exploration in Monitored Markov Decision Processes
Alireza Kazemipour, Matthew Taylor, Michael Bowling
Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
Jintao Tong, Yixiong Zou, Guangyao Chen et al.
Ensemble Distribution Distillation via Flow Matching
Jonggeon Park, Giung Nam, Hyunsu Kim et al.
Does Data Scaling Lead to Visual Compositional Generalization?
Arnas Uselis, Andrea Dittadi, Seong Joon Oh
Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning
Fangwen Wu, Lechao Cheng, Shengeng Tang et al.
Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective
Lele Fu, Bowen Deng, Sheng Huang et al.
Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging
Pierre Ablin, Angelos Katharopoulos, Skyler Seto et al.
Sparse Autoencoders, Again?
Yin Lu, Xuening Zhu, Tong He 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.
Fragments to Facts: Partial-Information Fragment Inference from LLMs
Lucas Rosenblatt, Bin Han, Robert Wolfe et al.
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
Taehyun Cho, Seungyub Han, Seokhun Ju et al.
Phase transitions for the existence of unregularized M-estimators in single index models
Takuya Koriyama, Pierre C Bellec
Safely Learning Optimal Auctions: A Testable Learning Framework for Mechanism Design
Vikram Kher, Manolis Zampetakis
CVE-Bench: A Benchmark for AI Agents’ Ability to Exploit Real-World Web Application Vulnerabilities
Yuxuan Zhu, Antony Kellermann, Dylan Bowman et al.
DS-VLM: Diffusion Supervision Vision Language Model
Zhen Sun, Yunhang Shen, Jie Li et al.
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
Stefano Viel, Luca Viano, Volkan Cevher
Nonlinear transformers can perform inference-time feature learning
Naoki Nishikawa, Yujin Song, Kazusato Oko et al.
LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
Shreshth Saini, Ru-Ling Liao, Yan Ye et al.
Scalable Gaussian Processes with Latent Kronecker Structure
Jihao Andreas Lin, Sebastian Ament, Maximilian Balandat et al.
Robust Spatio-Temporal Centralized Interaction for OOD Learning
Jiaming Ma, Binwu Wang, Pengkun Wang et al.
TinyMIG: Transferring Generalization from Vision Foundation Models to Single-Domain Medical Imaging
Chuang Liu, Hongyan Xu, Yichao Cao et al.
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion
Anle Ke, Xu Zhang, Tong Chen et al.
On the Local Complexity of Linear Regions in Deep ReLU Networks
Niket Patel, Guido Montufar
GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs
Yue Wang, Qizhou Wang, Feng Liu et al.
FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials
Seung Lee, Hojoon Kim, Yutack Park et al.
Learning with Expected Signatures: Theory and Applications
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
Enhancing Spectral GNNs: From Topology and Perturbation Perspectives
Taoyang Qin, Ke-Jia CHEN, Zheng Liu
Scalable Generation of Spatial Transcriptomics from Histology Images via Whole-Slide Flow Matching
Tinglin Huang, Tianyu Liu, Mehrtash Babadi et al.
Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective
Aojun Lu, Hangjie Yuan, Tao Feng et al.
Resolving Lexical Bias in Model Editing
Hammad Rizwan, Domenic Rosati, Ga Wu et al.
Quadratic Upper Bound for Boosting Robustness
Euijin You, Hyang-Won Lee
Diffusion Sampling Correction via Approximately 10 Parameters
Guangyi Wang, Wei Peng, lijiang Li et al.
MiraGe: Editable 2D Images using Gaussian Splatting
Joanna Waczyńska, Tomasz Szczepanik, Piotr Borycki et al.
Learning with Selectively Labeled Data from Multiple Decision-makers
Jian Chen, Zhehao Li, Xiaojie Mao
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
Jintao Tong, Ran Ma, Yixiong Zou et al.
Representation Preserving Multiclass Agnostic to Realizable Reduction
Steve Hanneke, Qinglin Meng, Amirreza Shaeiri
New Bounds for Sparse Variational Gaussian Processes
Michalis Titsias
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
Paris Giampouras, HanQin Cai, Rene Vidal
Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design
Marino Kühne, Panagiotis D. Grontas, Giulia De Pasquale et al.
NEAR: Neural Electromagnetic Array Response
Yinyan Bu, Jiajie Yu, Kai Zheng et al.
NExtLong: Toward Effective Long-Context Training without Long Documents
Chaochen Gao, Xing W, Zijia Lin et al.
Federated Causal Structure Learning with Non-identical Variable Sets
Yunxia Wang, Fuyuan CAO, Kui Yu et al.
Approximate Differential Privacy of the $\ell_2$ Mechanism
Matthew Joseph, Alex Kulesza, Alexander Yu
Action-Constrained Imitation Learning
Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio et al.
BDC-CLIP: Brownian Distance Covariance for Adapting CLIP to Action Recognition
Fei Long, Xiaoou Li, jiaming Lv et al.
From Theory to Practice: Rethinking Green and Martin Kernels for Unleashing Graph Transformers
Yoon Hyeok Lee, Jaemin Park, Taejin Paik et al.
Reinforcement Learning with Random Time Horizons
Enric Borrell, Lorenz Richter, Christof Schuette
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Mengyang Sun, Yihao Wang, Tao Feng et al.
Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models
Quan Nguyen, Minh Vu, Truc Nguyen et al.
TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization
Haowen Ma, Zhiguo Long, Hua Meng
Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation
Junyu Luo, Yuhao Tang, Yiwei Fu et al.
Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification
Jie Wen, Yadong Liu, Zhanyan Tang et al.
RepoAudit: An Autonomous LLM-Agent for Repository-Level Code Auditing
Jinyao Guo, Chengpeng Wang, Xiangzhe Xu et al.
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Gaozheng Pei, Ke Ma, Yingfei Sun et al.
Efficient Network Automatic Relevance Determination
Hongwei Zhang, Ziqi Ye, Xinyuan Wang et al.
Improving Diversity in Language Models: When Temperature Fails, Change the Loss
Alexandre Verine, Florian Le Bronnec, Kunhao Zheng et al.
Let LLM Tell What to Prune and How Much to Prune
Mingzhe Yang, Sihao Lin, Changlin Li et al.
Chaos Meets Attention: Transformers for Large-Scale Dynamical Prediction
Yi He, Yiming Yang, Xiaoyuan Cheng et al.
Time-Aware World Model for Adaptive Prediction and Control
Anh Nhu, Sanghyun Son, Ming Lin
LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
Dachuan Shi, Yonggan Fu, Xiangchi Yuan et al.
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Blake Bordelon, Cengiz Pehlevan
Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li et al.
Self-supervised Adversarial Purification for Graph Neural Networks
Woohyun Lee, Hogun Park
Position: Explainable AI Cannot Advance Without Better User Studies
Matej Pičulin, Bernarda Petek, Irena Ograjenšek et al.
Cover learning for large-scale topology representation
Luis Scoccola, Uzu Lim, Heather Harrington
SketchDNN: Joint Continuous-Discrete Diffusion for CAD Sketch Generation
Sathvik Chereddy, John Femiani
Off-Policy Evaluation under Nonignorable Missing Data
Han Wang, Yang Xu, Wenbin Lu et al.
Tree-Sliced Wasserstein Distance: A Geometric Perspective
Viet Hoang Tran, Trang Pham, Tho Tran Huu et al.
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
Ossi Räisä, Boris van Breugel, Mihaela van der Schaar
Dialogue Without Limits: Constant-Sized KV Caches for Extended Response in LLMs
Ravi Ghadia, Avinash Kumar, Gaurav Jain et al.
What Has a Foundation Model Found? Inductive Bias Reveals World Models
Keyon Vafa, Peter Chang, Ashesh Rambachan et al.
Joint Localization and Activation Editing for Low-Resource Fine-Tuning
Wen Lai, Alexander Fraser, Ivan Titov
Generative Audio Language Modeling with Continuous-valued Tokens and Masked Next-Token Prediction
Shu-wen Yang, Byeonggeun Kim, Kuan Po Huang et al.
Position: Uncertainty Quantification Needs Reassessment for Large Language Model Agents
Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci
Stochastic Forward–Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets
Haoye Lu, Qifan Wu, Yaoliang Yu
Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting
Chen Huang, Skyler Seto, Hadi Pouransari 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.
WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs
Lukas Thede, Karsten Roth, Matthias Bethge et al.
Understanding the difficulties of posterior predictive estimation
Abhinav Agrawal, Justin Domke
Graph Adaptive Autoregressive Moving Average Models
Moshe Eliasof, Alessio Gravina, Andrea Ceni et al.
Probably Approximately Global Robustness Certification
Peter Blohm, Patrick Indri, Thomas Gärtner et al.
Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus Kirkman, Graham Todd et al.
BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing
Dongliang Guo, Mengxuan Hu, Zihan Guan et al.
System-Aware Unlearning Algorithms: Use Lesser, Forget Faster
Linda Lu, Ayush Sekhari, Karthik Sridharan
Computing Voting Rules with Improvement Feedback
Evi Micha, Vasilis Varsamis
Can DBNNs Robust to Environmental Noise for Resource-constrained Scenarios?
Wendong Zheng, Junyang Chen, Husheng Guo et al.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck et al.
Position: Strong Consumer Protection is an Inalienable Defense for AI Safety in the United States
Serena Booth
Efficient Noise Calculation in Deep Learning-based MRI Reconstructions
Onat Dalmaz, Arjun Desai, Reinhard Heckel et al.
Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods
Yedi Zhang, Yufan Cai, Xinyue Zuo et al.
DIS-CO: Discovering Copyrighted Content in VLMs Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
Rethinking Benign Overfitting in Two-Layer Neural Networks
Ruichen Xu, Kexin Chen
A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres
Efficient Core-set Selection for Deep Learning Through Squared Loss Minimization
Jianting Chen
Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models
peijie liu, Fengli Xu, Yong Li
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.
TabSDS: a Lightweight, Fully Non-Parametric, and Model Free Approach for Generating Synthetic Tabular Data
Elias Chaibub Neto
Taming Diffusion for Dataset Distillation with High Representativeness
Lin Zhao, Yushu Wu, Xinru Jiang et al.
DiffusionVLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression
Junjie Wen, Yichen Zhu, Minjie Zhu et al.
Batch List-Decodable Linear Regression via Higher Moments
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
Siddarth Venkatraman, Mohsin Hasan, Minsu Kim et al.
FEAT-KD: Learning Concise Representations for Single and Multi-Target Regression via TabNet Knowledge Distillation
Kei Sen Fong, Mehul Motani
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
Mohamad Chehade, Wenting Li, Brian Bell et al.
Online Learning in the Random-Order Model
Martino Bernasconi, Andrea Celli, Riccardo Colini Baldeschi et al.
Sum-of-Parts: Self-Attributing Neural Networks with End-to-End Learning of Feature Groups
Weiqiu You, Helen Qu, Marco Gatti et al.
Private Model Personalization Revisited
Conor Snedeker, Xinyu Zhou, Raef Bassily
Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres
Muskan Dosi, Chiranjeev Chiranjeev, Kartik Thakral et al.
MVA: Linear Attention with High-order Query-Keys Integration and Multi-level Vocabulary Decomposition
ning wang, Zekun Li, Tongxin Bai et al.
Stochastic Encodings for Active Feature Acquisition
Alexander Norcliffe, Changhee Lee, Fergus Imrie et al.
Elucidating the Design Space of Multimodal Protein Language Models
Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang et al.