Most Cited ICML "pre-trained models" Papers
5,975 papers found • Page 21 of 30
Conference
Privately Learning Smooth Distributions on the Hypercube by Projections
Clément Lalanne, Sébastien Gadat
Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments
Mikel Malagón, Josu Ceberio, Jose A Lozano
Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems
Tomoharu Iwata, Shinsaku Sakaue
Origin Identification for Text-Guided Image-to-Image Diffusion Models
Wenhao Wang, Yifan Sun, Zongxin Yang et al.
Discovering Latent Causal Graphs from Spatiotemporal Data
Kun Wang, Sumanth Varambally, Duncan Watson-Parris et al.
Discovering Spoofing Attempts on Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab et al.
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection
Moritz Vandenhirtz, Julia Vogt
SUICA: Learning Super-high Dimensional Sparse Implicit Neural Representations for Spatial Transcriptomics
Qingtian Zhu, Yumin Zheng, Yuling Sang et al.
Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms
Yuchen Li, Laura Balzano, Deanna Needell et al.
Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
Zhonglin Cao, Mario Geiger, Allan Costa et al.
Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
Michael S Yao, James Gee, Osbert Bastani
LAST SToP for Modeling Asynchronous Time Series
Shubham Gupta, Thibaut Durand, Graham Taylor et al.
A Recipe for Causal Graph Regression: Confounding Effects Revisited
Yujia Yin, Tianyi Qu, Zihao Wang et al.
Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features
Rodrigo Veiga, Anastasia Remizova, Nicolas Macris
ELMO : Efficiency via Low-precision and Peak Memory Optimization in Large Output Spaces
Jinbin Zhang, Nasib Ullah, Erik Schultheis et al.
Scalable Non-Equivariant 3D Molecule Generation via Rotational Alignment
Yuhui Ding, Thomas Hofmann
Efficient Skill Discovery via Regret-Aware Optimization
He ZHANG, Ming Zhou, shaopeng zhai et al.
Targeted control of fast prototyping through domain-specific interface
Yu-Zhe Shi, Mingchen Liu, Hanlu Ma et al.
Identifying and Understanding Cross-Class Features in Adversarial Training
Zeming Wei, Yiwen Guo, Yisen Wang
NTK-DFL: Enhancing Decentralized Federated Learning in Heterogeneous Settings via Neural Tangent Kernel
Gabriel Thompson, Kai Yue, Chau-Wai Wong et al.
Learning Fused State Representations for Control from Multi-View Observations
Zeyu Wang, Yao-Hui Li, Xin Li et al.
BILBO: BILevel Bayesian Optimization
Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low
Cross-regularization: Adaptive Model Complexity through Validation Gradients
Carlos Stein Naves de Brito
Towards Attributions of Input Variables in a Coalition
Xinhao Zheng, Huiqi Deng, Quanshi Zhang
Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning
Ngoc Bui, Menglin Yang, Runjin Chen et al.
Weakly-Supervised Contrastive Learning for Imprecise Class Labels
Zi-Hao Zhou, Jun-Jie Wang, Tong Wei et al.
Provably Efficient Long-Horizon Exploration in Monte Carlo Tree Search through State Occupancy Regularization
Liam Schramm, Abdeslam Boularias
SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets
Shenghua Wan, Ziyuan Chen, Le Gan et al.
VNN: Verification-Friendly Neural Networks with Hard Robustness Guarantees
Anahita Baninajjar, Ahmed Rezine, Amir Aminifar
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions
Jon Vadillo, Roberto Santana, Jose A Lozano
Towards Rationale-Answer Alignment of LVLMs via Self-Rationale Calibration
Yuanchen Wu, Ke Yan, Shouhong Ding et al.
Autonomous Sparse Mean-CVaR Portfolio Optimization
Yizun Lin, Yangyu Zhang, Zhao-Rong Lai et al.
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training
Geon-Woo Kim, Junbo Li, Shashidhar Gandham et al.
Decoupled SGDA for Games with Intermittent Strategy Communication
Ali Zindari, Parham Yazdkhasti, Anton Rodomanov et al.
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Dake Zhang, Boxiang Lyu, Shuang Qiu et al.
Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
Dominik Fuchsgruber, Tom Wollschläger, Johannes Bordne et al.
Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad
FreeMesh: Boosting Mesh Generation with Coordinates Merging
Jian Liu, Haohan Weng, Biwen Lei et al.
Tightening Causal Bounds via Covariate-Aware Optimal Transport
Sirui Lin, Zijun Gao, Jose Blanchet et al.
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
Pedro Santos, Alberto Sardinha, Francisco S. Melo
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
Zhifa Ke, Zaiwen Wen, Junyu Zhang
Compositional Scene Understanding through Inverse Generative Modeling
Yanbo Wang, Justin Dauwels, Yilun Du
A Persuasive Approach to Combating Misinformation
Safwan Hossain, Andjela Mladenovic, Yiling Chen et al.
On the Learnability of Distribution Classes with Adaptive Adversaries
Tosca Lechner, Alex Bie, Gautam Kamath
TuCo: Measuring the Contribution of Fine-Tuning to Individual Responses of LLMs
Felipe Nuti, Tim Franzmeyer, Joao Henriques
Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics
Xinyu Zhang, Wenjie Qiu, Yi-Chen Li et al.
Learning Event Completeness for Weakly Supervised Video Anomaly Detection
Yu Wang, Shiwei Chen
The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli
Doron Cohen, Aryeh Kontorovich, Roi Weiss
Imitation Learning from Purified Demonstrations
Yunke Wang, Minjing Dong, Yukun Zhao et al.
A Chaotic Dynamics Framework Inspired by Dorsal Stream for Event Signal Processing
yu chen, Jing Lian, Zhaofei Yu et al.
HYGMA: Hypergraph Coordination Networks with Dynamic Grouping for Multi-Agent Reinforcement Learning
Chiqiang Liu, Dazi Li
KEA: Keeping Exploration Alive by Proactively Coordinating Exploration Strategies
Shih-Min Yang, Martin Magnusson, Johannes Stork et al.
FairICP: Encouraging Equalized Odds via Inverse Conditional Permutation
Yuheng Lai, Leying Guan
ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems
Yeqing Qiu, Ye XUE, Akang Wang et al.
Tracking Most Significant Shifts in Infinite-Armed Bandits
Joe Suk, Jung-hun Kim
CtrlSynth: Controllable Image Text Synthesis for Data-Efficient Multimodal Learning
Qingqing Cao, Mahyar Najibi, Sachin Mehta
EvoControl: Multi-Frequency Bi-Level Control for High-Frequency Continuous Control
Samuel Holt, Todor Davchev, Dhruva Tirumala et al.
Oracle-MoE: Locality-preserving Routing in the Oracle Space for Memory-constrained Large Language Model Inference
Jixian Zhou, Fang DONG(董方), Ruijun Huang et al.
Adversarial Combinatorial Semi-bandits with Graph Feedback
Yuxiao Wen
Mollification Effects of Policy Gradient Methods
Tao Wang, Sylvia Herbert, Sicun Gao
CUPS: Improving Human Pose-Shape Estimators with Conformalized Deep Uncertainty
Harry Zhang, Luca Carlone
Model Uncertainty Quantification by Conformal Prediction in Continual Learning
Rui Gao, Weiwei Liu
Test-Time Adaptation for Online Vision-Language Navigation with Feedback-based Reinforcement Learning
Sung June Kim, Gyeongrok Oh, Heeju Ko et al.
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Jie Gao, Rajesh Jayaram, Benedikt Kolbe et al.
Scale-Free Image Keypoints Using Differentiable Persistent Homology
Giovanni Barbarani, Francesco Vaccarino, Gabriele Trivigno et al.
PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models
Alex Velez-Arce, Marinka Zitnik
Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling
Xinxing Shi, Xiaoyu Jiang, Mauricio Álvarez
TextCenGen: Attention-Guided Text-Centric Background Adaptation for Text-to-Image Generation
Tianyi Liang, Jiangqi Liu, Yifei Huang et al.
Improved Approximations for Hard Graph Problems using Predictions
Anders Aamand, Justin Chen, Siddharth Gollapudi et al.
Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide Sequencing
Ye DU, Chen Yang, Nanxi Yu et al.
PAPM: A Physics-aware Proxy Model for Process Systems
Pengwei Liu, Zhongkai Hao, Xingyu Ren et al.
Interchangeable Token Embeddings for Extendable Vocabulary and Alpha-Equivalence
İlker Işık, Ramazan Gokberk Cinbis, Ebru Gol
Incremental Gradient Descent with Small Epoch Counts is Surprisingly Slow on Ill-Conditioned Problems
Yujun Kim, Jaeyoung Cha, Chulhee Yun
Cowpox: Towards the Immunity of VLM-based Multi-Agent Systems
YUTONG WU, Jie Zhang, Yiming Li et al.
Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field Games
Antonio Ocello, Daniil Tiapkin, Lorenzo Mancini et al.
A Bayesian Approach to Online Planning
Nir Greshler, David Ben Eli, Carmel Rabinovitz et al.
SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning
Matthias Weissenbacher, Rishabh Agarwal, Yoshinobu Kawahara
Arrow: Accelerator for Time Series Causal Discovery with Time Weaving
Yuanyuan Yao, Yuan Dong, Lu Chen et al.
Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects
Santiago Cortes-Gomez, Naveen Raman, Aarti Singh et al.
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery
Ning Liu, Yue Yu
On the Private Estimation of Smooth Transport Maps
Clément Lalanne, Franck Iutzeler, Loubes Jean-Michel et al.
LoRA-Gen: Specializing Large Language Model via Online LoRA Generation
Yicheng Xiao, Lin Song, Rui Yang et al.
Splitting with Importance-aware Updating for Heterogeneous Federated Learning with Large Language Models
Yangxu Liao, Wenke Huang, Guancheng Wan et al.
Reconstructing Cell Lineage Trees from Phenotypic Features with Metric Learning
Da Kuang, GuanWen Qiu, Junhyong Kim
Nonparametric Identification of Latent Concepts
Yujia Zheng, Shaoan Xie, Kun Zhang
Optimal and Practical Batched Linear Bandit Algorithm
Sanghoon Yu, Min-hwan Oh
An Intrinsic Vector Heat Network
Alexander Gao, Maurice Chu, Mubbasir Kapadia et al.
Gradient Aligned Regression via Pairwise Losses
Dixian Zhu, Tianbao Yang, Livnat Jerby
Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems
Roie Reshef, Kfir Levy
Info-Coevolution: An Efficient Framework for Data Model Coevolution
Ziheng Qin, Hailun Xu, Wei Yew et al.
A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
Ibrahim Alabdulmohsin, Andreas Steiner
Grammar-Forced Translation of Natural Language to Temporal Logic using LLMs
William English, Dominic Simon, Sumit Jha et al.
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions
Trenton Chang, Jenna Wiens
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
Daniel Dodd, Louis Sharrock, Chris Nemeth
Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective
Junze Deng, Qinhang Wu, Peizhong Ju et al.
Instruct2See: Learning to Remove Any Obstructions Across Distributions
Junhang Li, Yu Guo, Xian et al.
Leveraging Per-Instance Privacy for Machine Unlearning
Naz Sepahvand, Anvith Thudi, Berivan Isik et al.
Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens
Jihwan Jeong, Xiaoyu Wang, Jingmin Wang et al.
SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes
Yishan Shen, Yuyang Ye, Hui Xiong et al.
Efficient Online Set-valued Classification with Bandit Feedback
Zhou Wang, Xingye Qiao
Deep Stochastic Mechanics
Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang et al.
Modeling All-Atom Glycan Structures via Hierarchical Message Passing and Multi-Scale Pre-training
Minghao Xu, Jiaze Song, Keming Wu et al.
Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
Soobin Um, Beomsu Kim, Jong Chul YE
$S^2$FGL: Spatial Spectral Federated Graph Learning
Zihan Tan, Suyuan Huang, Guancheng Wan et al.
The Limits of Predicting Agents from Behaviour
Alexis Bellot, Jonathan Richens, Tom Everitt
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery
Caixing Wang, Ziliang Shen
Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization
Yuki Takezawa, Xiaowen Jiang, Anton Rodomanov et al.
FlexiClip: Locality-Preserving Free-Form Character Animation
Anant Khandelwal
Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation
Yassine Abbahaddou, Fragkiskos Malliaros, Johannes Lutzeyer et al.
Hide & Seek: Transformer Symmetries Obscure Sharpness & Riemannian Geometry Finds It
Marvin F, da Silva, Felix Dangel, Sageev Oore
AKRMap: Adaptive Kernel Regression for Trustworthy Visualization of Cross-Modal Embeddings
Yilin Ye, Junchao Huang, Xingchen ZENG et al.
A Mathematical Framework for AI-Human Integration in Work
L. Elisa Celis, Lingxiao Huang, Nisheeth K. Vishnoi
Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection
Zhijing Wan, Zhixiang Wang, Zheng Wang et al.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity
Shihao Zou, Qingfeng Li, Wei Ji et al.
Prediction models that learn to avoid missing values
Lena Stempfle, Anton Matsson, Newton Mwai et al.
Rethinking Benign Overfitting in Two-Layer Neural Networks
Ruichen Xu, Kexin Chen
Self-Play $Q$-Learners Can Provably Collude in the Iterated Prisoner's Dilemma
Quentin Bertrand, Juan Duque, Emilio Calvano et al.
VTGaussian-SLAM: RGBD SLAM for Large Scale Scenes with Splatting View-Tied 3D Gaussians
Pengchong Hu, Zhizhong Han
How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies
Piotr Kubaty, Bartosz Wójcik, Bartłomiej Krzepkowski et al.
Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrödinger Equation
Kevin Han Huang, Ni Zhan, Elif Ertekin et al.
Learning to Explore for Stochastic Gradient MCMC
SeungHyun Kim, Seohyeon Jung, SeongHyeon Kim et al.
HPS: Hard Preference Sampling for Human Preference Alignment
Xiandong Zou, Wanyu LIN, Yuchen Li et al.
Online Learning with Bounded Recall
Jon Schneider, Kiran Vodrahalli
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu, Pan Zhou, Zehao Xiao et al.
Learning Dynamics under Environmental Constraints via Measurement-Induced Bundle Structures
Dongzhe Zheng, Wenjie Mei
Risk Estimation in a Markov Cost Process: Lower and Upper Bounds
Gugan Chandrashekhar Mallika Thoppe, Prashanth L.A., Sanjay Bhat
Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization
Suryanarayana Sankagiri, Jalal Etesami, Matthias Grossglauser
A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation
Jongha (Jon) Ryu, Abhin Shah, Gregory Wornell
RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
David Reber, Sean Richardson, Todd Nief et al.
Learning from Streaming Data when Users Choose
Jinyan Su, Sarah Dean
BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assembly
Yan Shen, Ruihai Wu, Yubin Ke et al.
A Sample Efficient Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Xinshuai Dong et al.
Online Detection of LLM-Generated Texts via Sequential Hypothesis Testing by Betting
Can Chen, Jun-Kun Wang
Rank-One Modified Value Iteration
Arman Sharifi Kolarijani, Tolga Ok, Peyman Mohajerin Esfahani et al.
When do neural networks learn world models?
Tianren Zhang, Guanyu Chen, Feng Chen
Multi-View Stochastic Block Models
Vincent Cohen-Addad, Tommaso d'Orsi, Silvio Lattanzi et al.
N2GON: Neural Networks for Graph-of-Net with Position Awareness
Yejiang Wang, Yuhai Zhao, Zhengkui Wang et al.
Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift
chao ying, Jun Jin, Yi Guo et al.
Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models
peijie liu, Fengli Xu, Yong Li
Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
Yinong O Wang, Nivedha Sivakumar, Falaah Arif Khan et al.
Observation Interference in Partially Observable Assistance Games
Scott Emmons, Caspar Oesterheld, Vincent Conitzer et al.
Offline-to-Online Reinforcement Learning with Classifier-Free Diffusion Generation
Xiao Huang, Xu Liu, Enze Zhang et al.
Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models
Ding Huang, Ting Li, Jian Huang
SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
Nikolaos Chaidos, Angeliki Dimitriou, Maria Lymperaiou et al.
Learn to Vaccinate: Combining Structure Learning and Effective Vaccination for Epidemic and Outbreak Control
Sepehr Elahi, Paula Mürmann, Patrick Thiran
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning
Jungtaek Kim
Fast Estimation of Partial Dependence Functions using Trees
Jinyang Liu, Tessa Steensgaard, Marvin N. Wright et al.
Deep Unsupervised Hashing via External Guidance
Qihong Song, XitingLiu, Hongyuan Zhu et al.
DataFreeShield: Defending Adversarial Attacks without Training Data
Hyeyoon Lee, Kanghyun Choi, Dain Kwon et al.
Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
Xiaoyu Wu, Jiaru Zhang, Steven Wu
GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebras
Ekaterina Filimoshina, Dmitry Shirokov
Adaptive Robust Learning using Latent Bernoulli Variables
Aleksandr Karakulev, Dave Zachariah, Prashant Singh
Learning Single Index Models with Diffusion Priors
Anqi Tang, Youming Chen, Shuchen Xue et al.
When Can Proxies Improve the Sample Complexity of Preference Learning?
Yuchen Zhu, Daniel Augusto de Souza, Zhengyan Shi et al.
Compositional Condition Question Answering in Tabular Understanding
Jun-Peng Jiang, Tao Zhou, De-Chuan Zhan et al.
Concentration Distribution Learning from Label Distributions
Jiawei Tang, Yuheng Jia
Analytical Lyapunov Function Discovery: An RL-based Generative Approach
Haohan Zou, Jie Feng, Hao Zhao et al.
Video-Enhanced Offline Reinforcement Learning: A Model-Based Approach
Minting Pan, Yitao Zheng, Jiajian Li et al.
Open Your Eyes: Vision Enhances Message Passing Neural Networks in Link Prediction
Yanbin Wei, Xuehao Wang, Zhan Zhuang et al.
PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities
Daniel Zilberg, Ron Levie
Fully Dynamic Euclidean Bi-Chromatic Matching in Sublinear Update Time
Gramoz Goranci, Peter Kiss, Neel Patel et al.
CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration
Haoyun Jiang, Haolin li, jianwei zhang et al.
Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data
Xinshuai Dong, Ignavier Ng, Boyang Sun et al.
A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
Shivam Kumar, Yun Yang, Lizhen Lin
Mean-field Chaos Diffusion Models
Sungwoo Park, Dongjun Kim, Ahmed Alaa
A Versatile Influence Function for Data Attribution with Non-Decomposable Loss
Junwei Deng, Weijing Tang, Jiaqi Ma
Variance-Reduced Forward-Reflected-Backward Splitting Methods for Nonmonotone Generalized Equations
Quoc Tran-Dinh
FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames
Ruidong Wu, Ruihan Guo, Rui Wang et al.
La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse Activation
Kai Liu, Bowen Xu, Shaoyu Wu et al.
Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data
Erez Peterfreund, Ofir Lindenbaum, Yuval Kluger et al.
KGMark: A Diffusion Watermark for Knowledge Graphs
Hongrui Peng, Haolang Lu, Yuanlong Yu et al.
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh et al.
Fine-Grained Captioning of Long Videos through Scene Graph Consolidation
Sanghyeok Chu, Seonguk Seo, Bohyung Han
Binary Hypothesis Testing for Softmax Models and Leverage Score Models
Yuzhou Gu, Zhao Song, Junze Yin
Ergodic Generative Flows
Leo Brunswic, Mateo Clémente, Rui Heng Yang et al.
Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite et al.
Exploring Invariance in Images through One-way Wave Equations
Yinpeng Chen, Dongdong Chen, Xiyang Dai et al.
An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series
Qiang Huang, Chuizheng Meng, Defu Cao et al.
Gibbs Sampling of Continuous Potentials on a Quantum Computer
Arsalan Motamedi, Pooya Ronagh
Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks
Jeongmo Kim, Yisak Park, Minung Kim et al.
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
Hyunsu Kim, Ye Gon Kim, Hongseok Yang et al.
LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation
Piyush Lalitkumar Tiwary, Kinjawl Bhattacharyya, Prathosh AP
Spike Distance Function as a Learning Objective for Spike Prediction
Kevin Doran, Marvin Seifert, Carola Yovanovich et al.
Relative Error Fair Clustering in the Weak-Strong Oracle Model
Vladimir Braverman, Prathamesh Dharangutte, Shaofeng Jiang et al.
Learning Progress Driven Multi-Agent Curriculum
Wenshuai Zhao, Zhiyuan Li, Joni Pajarinen
LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models
Tzu-Tao (Tommy) Chang, Shivaram Venkataraman
ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Zhou Jie et al.
Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data
Siqi Guo, Ilgee Hong, Vicente Balmaseda et al.
Behavioral Exploration: Learning to Explore via In-Context Adaptation
Andrew Wagenmaker, Zhiyuan Zhou, Sergey Levine
QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration
HamidReza Imani, Jiaxin Peng, Peiman Mohseni et al.
Robot-Gated Interactive Imitation Learning with Adaptive Intervention Mechanism
Haoyuan Cai, Zhenghao Peng, Bolei Zhou
Noise Conditional Variational Score Distillation
Xinyu Peng, Ziyang Zheng, Yaoming Wang et al.
Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains
Zhuo He, Shuang Li, Wenze Song et al.
Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series
Zachary Brown, David Carlson
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning
Chamika Sudusinghe, Gerasimos Gerogiannis, Damitha Lenadora et al.
Sparse Autoencoders, Again?
Yin Lu, Xuening Zhu, Tong He et al.
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar et al.
Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More
Geonhui Yoo, Minhak Song, Chulhee Yun
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
Yang Zheng, Wen Li, Zhaoqiang Liu