Most Cited ICML "feature extractor analysis" Papers
5,975 papers found • Page 22 of 30
Conference
Conformalized Adaptive Forecasting of Heterogeneous Trajectories
Yanfei Zhou, Lars Lindemann, Matteo Sesia
Sequential Kernel Goodness-of-fit Testing
Zhengyu Zhou, Weiwei Liu
RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation
Jiawei Zhou, Linye Lyu, Daojing He et al.
CurBench: Curriculum Learning Benchmark
Yuwei Zhou, Zirui Pan, Xin Wang et al.
GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting
Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong et al.
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process
Xiangxin Zhou, Liang Wang, Yichi Zhou
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
Yifei Zhou, Andrea Zanette, Jiayi Pan et al.
Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm
Fuzhong Zhou, Chenyu Zhang, Xu Chen et al.
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation
Mingyuan Zhou, Huangjie Zheng, Zhendong Wang et al.
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
Yuhang Zhou, Zhao Zihua, Siyuan Du et al.
Iterative Search Attribution for Deep Neural Networks
Zhiyu Zhu, Huaming Chen, Xinyi Wang et al.
Generative Active Learning for Long-tailed Instance Segmentation
Muzhi Zhu, Chengxiang Fan, Hao Chen et al.
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
Banghua Zhu, Michael Jordan, Jiantao Jiao
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Lianghui Zhu, Bencheng Liao, Qian Zhang et al.
Switched Flow Matching: Eliminating Singularities via Switching ODEs
Qunxi Zhu, Wei Lin
Toward Availability Attacks in 3D Point Clouds
Yifan Zhu, Yibo Miao, Yinpeng Dong et al.
Antibody Design Using a Score-based Diffusion Model Guided by Evolutionary, Physical and Geometric Constraints
Tian Zhu, Milong Ren, Haicang Zhang
Online Learning in Betting Markets: Profit versus Prediction
Haiqing Zhu, Alexander Soen, Yun Kuen Cheung et al.
Dynamic Evaluation of Large Language Models by Meta Probing Agents
Kaijie Zhu, Jindong Wang, Qinlin Zhao et al.
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection
Lin Zhu, Yifeng Yang, Qinying Gu et al.
Translation Equivariant Transformer Neural Processes
Matthew Ashman, Cristiana Diaconu, Junhyuck Kim et al.
Language Models Represent Beliefs of Self and Others
Wentao Zhu, Zhining Zhang, Yizhou Wang
Stealthy Imitation: Reward-guided Environment-free Policy Stealing
Zhixiong Zhuang, Irina Nicolae, Mario Fritz
Reinformer: Max-Return Sequence Modeling for Offline RL
Zifeng Zhuang, Dengyun Peng, Jinxin Liu et al.
Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration
Zhengyang Zhuge, Peisong Wang, Xingting Yao et al.
Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption
Itamar Zimerman, Moran Baruch, Nir Drucker et al.
Viewing Transformers Through the Lens of Long Convolutions Layers
Itamar Zimerman, Lior Wolf
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
Yongshuo Zong, Ondrej Bohdal, Tingyang Yu et al.
Compositional Few-Shot Class-Incremental Learning
Yixiong Zou, Shanghang Zhang, haichen zhou et al.
BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization
Lancheng Zou, Wenqian Zhao, Shuo Yin et al.
Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning
Yuelin Zhang, Jiacheng Cen, Jiaqi Han et al.
REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates
Arshia Afzal, Grigorios Chrysos, Volkan Cevher et al.
Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models
Jie ZHANG, Xiaosong Ma, Song Guo et al.
Visual Representation Learning with Stochastic Frame Prediction
Huiwon Jang, Dongyoung Kim, Junsu Kim et al.
Exploration and Anti-Exploration with Distributional Random Network Distillation
Kai Yang, jian tao, Jiafei Lyu et al.
Position: Is machine learning good or bad for the natural sciences?
David W. Hogg, Soledad Villar
Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data
Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini
Sample Complexity Bounds for Estimating Probability Divergences under Invariances
Behrooz Tahmasebi, Stefanie Jegelka
AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA
Weitao Feng, Wenbo Zhou, Jiyan He et al.
On the Embedding Collapse when Scaling up Recommendation Models
Xingzhuo Guo, Junwei Pan, Ximei Wang et al.
Revisiting Character-level Adversarial Attacks for Language Models
Elias Abad Rocamora, Yongtao Wu, Fanghui Liu et al.
Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?
M. Saquib Sarfraz, Mei-Yen Chen, Lukas Layer et al.
Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
Yechan Kim, Hwijoon Lim, Dongsu Han
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
Zelai Xu, Chao Yu, Fei Fang et al.
COPAL: Continual Pruning in Large Language Generative Models
Srikanth Malla, Joon Hee Choi, Chiho Choi
Position: Understanding LLMs Requires More Than Statistical Generalization
Patrik Reizinger, Szilvia Ujváry, Anna Mészáros et al.
Online Isolation Forest
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer et al.
Multimodal Prototyping for cancer survival prediction
Andrew Song, Richard Chen, Guillaume Jaume et al.
Differentially Private Sum-Product Networks
Xenia Heilmann, Mattia Cerrato, Ernst Althaus
Log Neural Controlled Differential Equations: The Lie Brackets Make A Difference
Benjamin Walker, Andrew McLeod, Tiexin QIN et al.
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
Shentao Yang, Tianqi Chen, Mingyuan Zhou
Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements
Naman Agarwal, Satyen Kale, Karan Singh et al.
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Nianzu Yang, Kaipeng Zeng, Haotian Lu et al.
Expand-and-Cluster: Parameter Recovery of Neural Networks
Flavio Martinelli, Berfin Simsek, Wulfram Gerstner et al.
REMEDI: Corrective Transformations for Improved Neural Entropy Estimation
Viktor Nilsson, Anirban Samaddar, Sandeep Madireddy et al.
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF
Han Shen, Zhuoran Yang, Tianyi Chen
Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning
Long Qian, Juncheng Li, Yu Wu et al.
Counterfactual Metarules for Local and Global Recourse
Tom Bewley, Salim I. Amoukou, Saumitra Mishra et al.
UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs
Xi Han, Fei Hou, Hong Qin
RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Harrison Lee, Samrat Phatale, Hassan Mansoor et al.
Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction
Christoph Jürgen Hemmer, Manuel Brenner, Florian Hess et al.
Unmasking Vulnerabilities: Cardinality Sketches under Adaptive Inputs
Sara Ahmadian, Edith Cohen
StackSight: Unveiling WebAssembly through Large Language Models and Neurosymbolic Chain-of-Thought Decompilation
Weike Fang, Zhejian Zhou, Junzhou He et al.
Disentangled Continual Graph Neural Architecture Search with Invariant Modular Supernet
Zeyang Zhang, Xin Wang, Yijian Qin et al.
Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization
Haoyang Li, Xin Wang, Zeyang Zhang et al.
Knowledge-aware Reinforced Language Models for Protein Directed Evolution
Yuhao Wang, Qiang Zhang, Ming Qin et al.
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
On the Effectiveness of Supervision in Asymmetric Non-Contrastive Learning
Jeongheon Oh, Kibok Lee
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
DNCs Require More Planning Steps
Yara Shamshoum, Nitzan Hodos, Yuval Sieradzki et al.
I/O Complexity of Attention, or How Optimal is FlashAttention?
Barna Saha, Christopher Ye
Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?
Shayne Longpre, Robert Mahari, Naana Obeng-Marnu et al.
Lookbehind-SAM: k steps back, 1 step forward
Gonçalo Mordido, Pranshu Malviya, Aristide Baratin et al.
A Distributional Analogue to the Successor Representation
Harley Wiltzer, Jesse Farebrother, Arthur Gretton et al.
From Neurons to Neutrons: A Case Study in Interpretability
Ouail Kitouni, Niklas Nolte, Víctor Samuel Pérez-Díaz et al.
A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks
Boqi Li, Weiwei Liu
Do Transformer World Models Give Better Policy Gradients?
Michel Ma, Tianwei Ni, Clement Gehring et al.
Conformal prediction for multi-dimensional time series by ellipsoidal sets
Chen Xu, Hanyang Jiang, Yao Xie
Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation
Yididiya Nadew, Xuhui Fan, Christopher J Quinn
Understanding the Training Speedup from Sampling with Approximate Losses
Rudrajit Das, Xi Chen, Bertram Ieong et al.
Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation
Ignat Georgiev, Krishnan Srinivasan, Jie Xu et al.
Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
Kolby Nottingham, Bodhisattwa Prasad Majumder, Bhavana Dalvi et al.
Mathematical Framework for Online Social Media Auditing
Wasim Huleihel, Yehonathan Refael
Low-Rank Similarity Mining for Multimodal Dataset Distillation
Yue Xu, Zhilin Lin, Yusong Qiu et al.
MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations
Zhangyu Wang, Gengchen Mai, Krzysztof Janowicz et al.
Enforcing Constraints in RNA Secondary Structure Predictions: A Post-Processing Framework Based on the Assignment Problem
Geewon Suh, Gyeongjo Hwang, SeokjunKang et al.
Reshape and Adapt for Output Quantization (RAOQ): Quantization-aware Training for In-memory Computing Systems
Bonan Zhang, Chia-Yu Chen, Naveen Verma
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding
Hongkang Li, Meng Wang, Tengfei Ma et al.
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
Hongkang Li, Meng Wang, Songtao Lu et al.
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning
Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan et al.
ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Data
Xiangjian Jiang, Andrei Margeloiu, Nikola Simidjievski et al.
Controllable Prompt Tuning For Balancing Group Distributional Robustness
Hoang Phan, Andrew Wilson, Qi Lei
Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
Shomik Jain, Kathleen A. Creel, Ashia Wilson
Compositional Text-to-Image Generation with Dense Blob Representations
Weili Nie, Sifei Liu, Morteza Mardani et al.
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding
Chuanhao Sun, Zhihang Yuan, Kai Xu et al.
Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization
Yirui Liu, Xinghao Qiao, Yulong Pei et al.
A Neural-Preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions
Kai Weixian Lan, Elias Gueidon, Ayano Kaneda et al.
Diffusion Posterior Sampling is Computationally Intractable
Shivam Gupta, Ajil Jalal, Aditya Parulekar et al.
PerceptAnon: Exploring the Human Perception of Image Anonymization Beyond Pseudonymization for GDPR
Kartik Patwari, Chen-Nee Chuah, Lingjuan Lyu et al.
Do Topological Characteristics Help in Knowledge Distillation?
Jungeun Kim, Junwon You, Dongjin Lee et al.
Stochastic Optimization with Arbitrary Recurrent Data Sampling
William Powell, Hanbaek Lyu
Partially Stochastic Infinitely Deep Bayesian Neural Networks
Sergio Calvo Ordoñez, Matthieu Meunier, Francesco Piatti et al.
Neuro-Visualizer: A Novel Auto-Encoder-Based Loss Landscape Visualization Method With an Application in Knowledge-Guided Machine Learning
Mohannad Elhamod, Anuj Karpatne
Discovering Bias in Latent Space: An Unsupervised Debiasing Approach
Dyah Adila, Shuai Zhang, Boran Han et al.
Centralized Selection with Preferences in the Presence of Biases
L. Elisa Celis, Amit Kumar, Nisheeth K. Vishnoi et al.
Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization
Rui Li, Chaozhuo Li, Yanming Shen et al.
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems
Yair Schiff, Zhong Yi Wan, Jeffrey Parker et al.
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
Zhongzhi Yu, Zheng Wang, Yonggan Fu et al.
BAT: Learning to Reason about Spatial Sounds with Large Language Models
Zhisheng Zheng, Puyuan Peng, Ziyang Ma et al.
Rethinking Transformers in Solving POMDPs
Chenhao Lu, Ruizhe Shi, Yuyao Liu et al.
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
Hyeonah Kim, Minsu Kim, Sungsoo Ahn et al.
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions
Trenton Chang, Jenna Wiens
Embodied CoT Distillation From LLM To Off-the-shelf Agents
Wonje Choi, Woo Kyung Kim, Minjong Yoo et al.
A General Framework for Sequential Decision-Making under Adaptivity Constraints
Nuoya Xiong, Zhaoran Wang, Zhuoran Yang
How Does Goal Relabeling Improve Sample Efficiency?
Sirui Zheng, Chenjia Bai, Zhuoran Yang et al.
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling
Zehao Dou, Minshuo Chen, Mengdi Wang et al.
RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis
Yao Mu, Junting Chen, Qing-Long Zhang et al.
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Yujia Liu, Tong Bu, Ding Jianhao et al.
Layerwise Change of Knowledge in Neural Networks
Xu Cheng, Lei Cheng, Zhaoran Peng et al.
Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts
Xiao-Wen Yang, Wen-Da Wei, Jie-Jing Shao et al.
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song et al.
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai et al.
EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence
Chung-Yiu Yau, Hoi To Wai, Parameswaran Raman et al.
Smoothness Adaptive Hypothesis Transfer Learning
Haotian Lin, Matthew Reimherr
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
Chentao Cao, Zhun Zhong, Zhanke Zhou et al.
Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiers
Johann Schmidt, Sebastian Stober
WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer
Kumar Shubham, Aishwarya Jayagopal, Syed Danish et al.
Interacting Diffusion Processes for Event Sequence Forecasting
Mai Zeng, Florence Regol, Mark Coates
Recurrent Early Exits for Federated Learning with Heterogeneous Clients
Royson Lee, Javier Fernandez-Marques, Xu Hu et al.
On Interpolating Experts and Multi-Armed Bandits
Houshuang Chen, Yuchen He, Chihao Zhang
Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning
Xinran Li, Zifan LIU, Shibo Chen et al.
Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling
Guoqi Yu, Jing Zou, Xiaowei Hu et al.
NeuralIndicator: Implicit Surface Reconstruction from Neural Indicator Priors
Shi-Sheng Huang, Guo Chen, Li-heng Chen et al.
On the Calibration of Human Pose Estimation
Kerui Gu, Rongyu Chen, Xuanlong Yu et al.
MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
Kaining Ying, Fanqing Meng, Jin Wang et al.
Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection
Feiran Li, Qianqian Xu, Shilong Bao et al.
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling
Jiajun Ma, Shuchen Xue, Tianyang Hu et al.
RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
Yukinari Hisaki, Isao Ono
Smooth Tchebycheff Scalarization for Multi-Objective Optimization
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang et al.
DFD: Distilling the Feature Disparity Differently for Detectors
Kang Liu, Yingyi Zhang, Jingyun Zhang et al.
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model
Fei Liu, Tong Xialiang, Mingxuan Yuan et al.
In-Context Unlearning: Language Models as Few-Shot Unlearners
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences
Andi Nika, Debmalya Mandal, Parameswaran Kamalaruban et al.
Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs
Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal et al.
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki et al.
Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations
Ze Cheng, Zhongkai Hao, Wang Xiaoqiang et al.
Auto-Linear Phenomenon in Subsurface Imaging
Yinan Feng, Yinpeng Chen, Peng Jin et al.
Accelerating Parallel Sampling of Diffusion Models
Zhiwei Tang, Jiasheng Tang, Hao Luo et al.
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems
Jianliang He, Siyu Chen, Fengzhuo Zhang et al.
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
Onur Celik, Aleksandar Taranovic, Gerhard Neumann
DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)
Zongxin Yang, Guikun Chen, Xiaodi Li et al.
Distributed Bilevel Optimization with Communication Compression
Yutong He, Jie Hu, Xinmeng Huang et al.
Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks
Guanhua Zhang, Moritz Hardt
On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions
Denys Pushkin, Raphaël Berthier, Emmanuel Abbe
On the Weight Dynamics of Deep Normalized Networks
Christian H.X. Ali Mehmeti-Göpel, Michael Wand
Jacobian Regularizer-based Neural Granger Causality
Wanqi Zhou, Shuanghao Bai, Shujian Yu et al.
Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations
Jonas Beck, Nathanael Bosch, Michael Deistler et al.
Projecting Molecules into Synthesizable Chemical Spaces
Shitong Luo, Wenhao Gao, Zuofan Wu et al.
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts
Kuang-Huei Lee, Xinyun Chen, Hiroki Furuta et al.
Energy-based Backdoor Defense without Task-Specific Samples and Model Retraining
Yudong Gao, Honglong Chen, Peng Sun et al.
Break the Sequential Dependency of LLM Inference Using Lookahead Decoding
Yichao Fu, Peter Bailis, Ion Stoica et al.
Don’t Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget
Florian Dorner, Moritz Hardt
Causal Inference from Competing Treatments
Ana-Andreea Stoica, Vivian Y. Nastl, Moritz Hardt
Denoising Autoregressive Representation Learning
Yazhe Li, Jorg Bornschein, Ting Chen
On a Neural Implementation of Brenier's Polar Factorization
Nina Vesseron, Marco Cuturi
Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization
Xueyang Tang, Song Guo, Jingcai Guo et al.
Privacy Attacks in Decentralized Learning
Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet
Membership Inference Attacks on Diffusion Models via Quantile Regression
Shuai Tang, Steven Wu, Sergul Aydore et al.
Hybrid Neural Representations for Spherical Data
Hyomin Kim, Yunhui Jang, Jaeho Lee et al.
Premise Order Matters in Reasoning with Large Language Models
Xinyun Chen, Ryan Chi, Xuezhi Wang et al.
Graph As Point Set
Xiyuan Wang, Pan Li, Muhan Zhang
Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
Yannik Mahlau, Frederik Schubert, Bodo Rosenhahn
SparQ Attention: Bandwidth-Efficient LLM Inference
Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley et al.
An Analysis of Linear Time Series Forecasting Models
William Toner, Luke Darlow
Adaptive Stabilization Based on Machine Learning for Column Generation
Yunzhuang Shen, Yuan Sun, Xiaodong Li et al.
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
Jaejun Lee, Minsung Hwang, Joyce Whang
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective
Fabian Falck, Ziyu Wang, Christopher Holmes
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving
Sohei Arisaka, Qianxiao Li
Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning
Jiachen Li, Qiaozi Gao, Michael Johnston et al.
Optimizing Watermarks for Large Language Models
Bram Wouters
A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs
Lars Veefkind, Gabriele Cesa
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
Damien Teney, Jindong Wang, Ehsan Abbasnejad
Hieros: Hierarchical Imagination on Structured State Space Sequence World Models
Paul Mattes, Rainer Schlosser, Ralf Herbrich
Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm
Batiste Le Bars, Aurélien Bellet, Marc Tommasi et al.
Equivariant Diffusion for Crystal Structure Prediction
Peijia Lin, Pin Chen, Rui Jiao et al.
Online Variational Sequential Monte Carlo
Alessandro Mastrototaro, Jimmy Olsson
Generalized Preference Optimization: A Unified Approach to Offline Alignment
Yunhao Tang, Zhaohan Guo, Zeyu Zheng et al.
Leveraging VLM-Based Pipelines to Annotate 3D Objects
Rishabh Kabra, Loic Matthey, Alexander Lerchner et al.
Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach
Bin Zhang, Hangyu Mao, Lijuan Li et al.
MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data
Jian Wang, Xin Lan, Yuxin Tian et al.
DiffDA: a Diffusion model for weather-scale Data Assimilation
Langwen Huang, Lukas Gianinazzi, Yuejiang Yu et al.
Understanding Heterophily for Graph Neural Networks
Junfu Wang, Yuanfang Guo, Liang Yang et al.
The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline
Haonan Wang, Qianli Shen, Yao Tong et al.
Dynamic Spectral Clustering with Provable Approximation Guarantee
Steinar Laenen, He Sun
Adversarially Robust Deep Multi-View Clustering: A Novel Attack and Defense Framework
Haonan Huang, Guoxu Zhou, Yanghang Zheng et al.
PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation
Runze Liu, Yali Du, Fengshuo Bai et al.
On Stronger Computational Separations Between Multimodal and Unimodal Machine Learning
Ari Karchmer
Rich-Observation Reinforcement Learning with Continuous Latent Dynamics
Yuda Song, Lili Wu, Dylan Foster et al.
Ai-sampler: Adversarial Learning of Markov kernels with involutive maps
Evgenii Egorov, Riccardo Valperga, Efstratios Gavves