Most Cited ICLR "optimal kronecker approximation" Papers
6,124 papers found • Page 13 of 31
Conference
Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM
Zheng Wei Lim, Nitish Gupta, Honglin Yu et al.
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar et al.
Kronecker Mask and Interpretive Prompts are Language-Action Video Learners
Jingyi Yang, Zitong YU, Nixiuming et al.
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Jasmine Bayrooti, Carl Ek, Amanda Prorok
DUALFormer: Dual Graph Transformer
Zhuo Jiaming, Yuwei Liu, Yintong Lu et al.
Causal Information Prioritization for Efficient Reinforcement Learning
Hongye Cao, Fan Feng, Tianpei Yang et al.
Progressive Fourier Neural Representation for Sequential Video Compilation
Haeyong Kang, Jaehong Yoon, DaHyun Kim et al.
Uni$^2$Det: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection
Yubin Wang, Zhikang Zou, Xiaoqing Ye et al.
$InterLCM$: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
Senmao Li, Kai Wang, Joost van de Weijer et al.
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
Linlin Yu, Bowen Yang, Tianhao Wang et al.
AugKD: Ingenious Augmentations Empower Knowledge Distillation for Image Super-Resolution
Yun Zhang, Wei Li, Simiao Li et al.
ReGen: Generative Robot Simulation via Inverse Design
Peter (Phat) Nguyen, Johnson (Tsun-Hsuan) Wang, Zhang-Wei Hong et al.
Calibrating LLMs with Information-Theoretic Evidential Deep Learning
Yawei Li, David Rügamer, Bernd Bischl et al.
No Need to Talk: Asynchronous Mixture of Language Models
Anastasiia Filippova, Angelos Katharopoulos, David Grangier et al.
PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
Sunghyeon Woo, Sol Namkung, SunWoo Lee et al.
Learning the Complexity of Weakly Noisy Quantum States
Yusen Wu, Bujiao Wu, Yanqi Song et al.
Learning Hierarchical Polynomials of Multiple Nonlinear Features
Hengyu Fu, Zihao Wang, Eshaan Nichani et al.
ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition
Joseph Fioresi, Ishan Rajendrakumar Dave, Mubarak Shah
Selective Unlearning via Representation Erasure Using Domain Adversarial Training
Nazanin Sepahvand, Eleni Triantafillou, Hugo Larochelle et al.
MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection
Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh et al.
NL-Eye: Abductive NLI For Images
Mor Ventura, Michael Toker, Nitay Calderon et al.
Random Is All You Need: Random Noise Injection on Feature Statistics for Generalizable Deep Image Denoising
Zhengwei Yin, Hongjun Wang, Guixu Lin et al.
Out-Of-Domain Unlabeled Data Improves Generalization
seyed amir hossein saberi, Amir Najafi, Alireza Heidari et al.
Contextualizing biological perturbation experiments through language
Menghua (Rachel) Wu, Russell Littman, Jacob Levine et al.
LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
Zhekai Du, Yinjie Min, Jingjing Li et al.
Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images
Hannah Kniesel, Leon Sick, Tristan Payer et al.
Expected Return Symmetries
Darius Muglich, Johannes Forkel, Elise van der Pol et al.
econSG: Efficient and Multi-view Consistent Open-Vocabulary 3D Semantic Gaussians
Can Zhang, Gim H Lee
Moner: Motion Correction in Undersampled Radial MRI with Unsupervised Neural Representation
Qing Wu, Chenhe Du, Xuanyu Tian et al.
RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
Tanya Chowdhury, Yair Zick, James Allan
An Exploration with Entropy Constrained 3D Gaussians for 2D Video Compression
Xiang Liu, Bin Chen, Zimo Liu et al.
Language Models are Advanced Anonymizers
Robin Staab, Mark Vero, Mislav Balunovic et al.
Shadow Cones: A Generalized Framework for Partial Order Embeddings
Tao Yu, Toni Liu, Albert Tseng et al.
Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
Byungjai Kim, Chanho Ahn, Wissam Baddar et al.
Information Theoretic Text-to-Image Alignment
Chao Wang, Giulio Franzese, alessandro finamore et al.
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto et al.
Agent Skill Acquisition for Large Language Models via CycleQD
So Kuroki, Taishi Nakamura, Takuya Akiba et al.
Improving Neural Optimal Transport via Displacement Interpolation
Jaemoo Choi, Yongxin Chen, Jaewoong Choi
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
Doubly Optimal Policy Evaluation for Reinforcement Learning
Shuze Liu, Claire Chen, Shangtong Zhang
Convergence of Distributed Adaptive Optimization with Local Updates
Ziheng Cheng, Margalit Glasgow
Complexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness
Michael Crawshaw, Mingrui Liu
Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency
Kai Gan, Bo Ye, Min-Ling Zhang et al.
Diffusion Transformers for Tabular Data Time Series Generation
Fabrizio Garuti, Enver Sangineto, Simone Luetto et al.
Morphing Tokens Draw Strong Masked Image Models
Taekyung Kim, Byeongho Heo, Dongyoon Han
Indirect Gradient Matching for Adversarial Robust Distillation
Hongsin Lee, Seungju Cho, Changick Kim
HShare: Fast LLM Decoding by Hierarchical Key-Value Sharing
Huaijin Wu, Lianqiang Li, Hantao Huang et al.
SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning
Lei You, Hei Victor Cheng
GNeRP: Gaussian-guided Neural Reconstruction of Reflective Objects with Noisy Polarization Priors
LI Yang, RUIZHENG WU, Jiyong Li et al.
Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation
Jihyo Kim, Seulbi Lee, Sangheum Hwang
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment
Minh-Quan Le, Gaurav Mittal, Tianjian Meng et al.
Selective Label Enhancement Learning for Test-Time Adaptation
Yihao Hu, Congyu Qiao, Xin Geng et al.
Optimal Brain Apoptosis
Mingyuan Sun, Zheng Fang, Jiaxu Wang et al.
Feature-Based Online Bilateral Trade
Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni et al.
Multi-Accurate CATE is Robust to Unknown Covariate Shifts
Angela Zhou, Christoph Kern, Michael Kim
Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs
Xin Gao, Jian Pu
On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
GUOJUN XIONG, Shufan Wang, Daniel Jiang et al.
BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge Distillation
Zhengrui Guo, Fangxu Zhou, Wei Wu et al.
Perceptual Group Tokenizer: Building Perception with Iterative Grouping
Zhiwei Deng, Ting Chen, Yang Li
Certifying Language Model Robustness with Fuzzed Randomized Smoothing: An Efficient Defense Against Backdoor Attacks
Bowei He, Lihao Yin, Huiling Zhen et al.
EFFICIENT JAILBREAK ATTACK SEQUENCES ON LARGE LANGUAGE MODELS VIA MULTI-ARMED BANDIT-BASED CONTEXT SWITCHING
Aditya Ramesh, Shivam Bhardwaj, Aditya Saibewar et al.
ECD: A Machine Learning Benchmark for Predicting Enhanced-Precision Electronic Charge Density in Crystalline Inorganic Materials
Pin Chen, Zexin Xu, Qing Mo et al.
Global Convergence in Neural ODEs: Impact of Activation Functions
Tianxiang Gao, Siyuan Sun, Hailiang Liu et al.
Copyright-Protected Language Generation via Adaptive Model Fusion
Javier Abad, Konstantin Donhauser, Francesco Pinto et al.
Enhancing Graph Of Thought: Enhancing Prompts with LLM Rationales and Dynamic Temperature Control
Sunguk Shin, Youngjoon Kim
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance
Dominik Fuchsgruber, Tim Postuvan, Stephan Günnemann et al.
Large Language Models can Become Strong Self-Detoxifiers
Ching-Yun Ko, Pin-Yu Chen, Payel Das et al.
Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs
Wei Hung, Shao-Hua Sun, Ping-Chun Hsieh
Enhancing Robust Fairness via Confusional Spectral Regularization
Gaojie Jin, Sihao Wu, Jiaxu Liu et al.
Physics-aligned field reconstruction with diffusion bridge
Zeyu Li, Hongkun Dou, Shen Fang et al.
Exact Certification of (Graph) Neural Networks Against Label Poisoning
Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann et al.
No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
Changlong Wu, Ananth Grama, Wojciech Szpankowski
Aligning Visual Contrastive learning models via Preference Optimization
Amirabbas Afzali, Borna khodabandeh, Ali Rasekh et al.
From Models to Microtheories: Distilling a Model's Topical Knowledge for Grounded Question-Answering
Nathaniel Weir, Bhavana Dalvi Mishra, Orion Weller et al.
Metalic: Meta-Learning In-Context with Protein Language Models
Jacob Beck, Shikha Surana, Manus McAuliffe et al.
Neural Spacetimes for DAG Representation Learning
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T Law et al.
Representational Similarity via Interpretable Visual Concepts
Neehar Kondapaneni, Oisin Mac Aodha, Pietro Perona
An Effective Theory of Bias Amplification
Arjun Subramonian, Samuel Bell, Levent Sagun et al.
Learning to Solve Differential Equation Constrained Optimization Problems
Vincenzo Di Vito Francesco, Mostafa Mohammadian, Kyri Baker et al.
Approximation algorithms for combinatorial optimization with predictions
Antonios Antoniadis, Marek Elias, Adam Polak et al.
The Labyrinth of Links: Navigating the Associative Maze of Multi-modal LLMs
HONG LI, Nanxi Li, Yuanjie Chen et al.
BANGS: Game-theoretic Node Selection for Graph Self-Training
Fangxin Wang, Kay Liu, Sourav Medya et al.
Charting the Design Space of Neural Graph Representations for Subgraph Matching
Vaibhav Raj, Indradyumna Roy, Ashwin Ramachandran et al.
Robust Conformal Prediction with a Single Binary Certificate
Soroush H. Zargarbashi, Aleksandar Bojchevski
Let the Code LLM Edit Itself When You Edit the Code
Zhenyu He, Jun Zhang, Shengjie Luo et al.
Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers
Tiberiu Mușat
FOSP: Fine-tuning Offline Safe Policy through World Models
Chenyang Cao, Yucheng Xin, Silang Wu et al.
$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
Wenye Li, Jiacai Liu, Ke Wei
ClawMachine: Learning to Fetch Visual Tokens for Referential Comprehension
Tianren Ma, Lingxi Xie, Yunjie Tian et al.
Enhancing Learning with Label Differential Privacy by Vector Approximation
Puning Zhao, Jiafei Wu, Zhe Liu et al.
ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models
Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky et al.
Improved Sampling Of Diffusion Models In Fluid Dynamics With Tweedie's Formula
Youssef Shehata, Benjamin Holzschuh, Nils Thuerey
AniSDF: Fused-Granularity Neural Surfaces with Anisotropic Encoding for High-Fidelity 3D Reconstruction
Jingnan Gao, Zhuo Chen, Xiaokang Yang et al.
Multi-Dimensional Conformal Prediction
Yam Tawachi, Bracha Laufer-Goldshtein
Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder
Antoine Schnepf, Karim Kassab, Jean-Yves Franceschi et al.
Steering Protein Family Design through Profile Bayesian Flow
Jingjing Gong, Yu Pei, Siyu Long et al.
Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
Jingchu Gai, Yiheng Du, Bohang Zhang et al.
TAU-106K: A New Dataset for Comprehensive Understanding of Traffic Accident
Yixuan Zhou, Long Bai, Sijia Cai et al.
MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
Paul Garnier, Vincent Lannelongue, Jonathan Viquerat et al.
Chunk-Distilled Language Modeling
Yanhong Li, Karen Livescu, Jiawei Zhou
EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation
Carl Qi, Dan Haramati, Tal Daniel et al.
Regulatory DNA Sequence Design with Reinforcement Learning
Zhao Yang, Bing Su, Chuan Cao et al.
Learning to Steer Markovian Agents under Model Uncertainty
Jiawei Huang, Vinzenz Thoma, Zebang Shen et al.
Direct Distributional Optimization for Provable Alignment of Diffusion Models
Ryotaro Kawata, Kazusato Oko, Atsushi Nitanda et al.
Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning
Hyungkyu Kang, Min-hwan Oh
Nonlinear multiregion neural dynamics with parametric impulse response communication channels
Matthew Dowling, Cristina Savin
Towards Synergistic Path-based Explanations for Knowledge Graph Completion: Exploration and Evaluation
Tengfei Ma, Xiang song, Wen Tao et al.
Regretful Decisions under Label Noise
Sujay Nagaraj, Yang Liu, Flavio Calmon et al.
On-the-fly Preference Alignment via Principle-Guided Decoding
Mingye Zhu, Yi Liu, Lei Zhang et al.
Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
Hengyu Fu, Zehao Dou, Jiawei Guo et al.
Differentially private learners for heterogeneous treatment effects
Maresa Schröder, Valentyn Melnychuk, Stefan Feuerriegel
Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics
Runzhe Wu, Ayush Sekhari, Akshay Krishnamurthy et al.
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation
Tobias Leemann, Periklis Petridis, Giuseppe Vietri et al.
ChroKnowledge: Unveiling Chronological Knowledge of Language Models in Multiple Domains
Yein Park, Chanwoong Yoon, Jungwoo Park et al.
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations
Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter et al.
Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation
Jasper Dekoninck, Maximilian Baader, Martin Vechev
Exploring The Loss Landscape Of Regularized Neural Networks Via Convex Duality
Sungyoon Kim, Aaron Mishkin, Mert Pilanci
WardropNet: Traffic Flow Predictions via Equilibrium-Augmented Learning
Kai Jungel, Dario Paccagnan, Axel Parmentier et al.
Divergence-Regularized Discounted Aggregation: Equilibrium Finding in Multiplayer Partially Observable Stochastic Games
Runyu Lu, Yuanheng Zhu, Dongbin Zhao
Exploring a Principled Framework for Deep Subspace Clustering
Xianghan Meng, Zhiyuan Huang, Wei He et al.
Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks
Théophane Vallaeys, Matthew J Muckley, Jakob Verbeek et al.
A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
Mingyang Liu, Gabriele Farina, Asuman Ozdaglar
Unsupervised Meta-Learning via In-Context Learning
Anna Vettoruzzo, Lorenzo Braccaioli, Joaquin Vanschoren et al.
Subtask-Aware Visual Reward Learning from Segmented Demonstrations
Changyeon Kim, Minho Heo, Doohyun Lee et al.
Efficient Discovery of Pareto Front for Multi-Objective Reinforcement Learning
Ruohong Liu, Yuxin Pan, Linjie Xu et al.
ThunderKittens: Simple, Fast, and $\textit{Adorable}$ Kernels
Benjamin Spector, Simran Arora, Aaryan Singhal et al.
Large (Vision) Language Models are Unsupervised In-Context Learners
Artyom Gadetsky, Andrei Atanov, Yulun Jiang et al.
A Simple Framework for Open-Vocabulary Zero-Shot Segmentation
Thomas Stegmüller, Tim Lebailly, Nikola Đukić et al.
Representative Guidance: Diffusion Model Sampling with Coherence
Anh-Dung Dinh, Daochang Liu, Chang Xu
Fast Uncovering of Protein Sequence Diversity from Structure
Luca Alessandro Silva, Barthelemy Meynard-Piganeau, Carlo Lucibello et al.
Learning High-Degree Parities: The Crucial Role of the Initialization
Emmanuel Abbe, Elisabetta Cornacchia, Jan Hązła et al.
From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
Jie Yang, Yuwen Wang, Kaixuan Chen et al.
Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction
M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel et al.
DICE: Data Influence Cascade in Decentralized Learning
Tongtian Zhu, Wenhao Li, Can Wang et al.
Dimension Agnostic Neural Processes
Hyungi Lee, Chaeyun Jang, Dong Bok Lee et al.
SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting
Huajian Huang, Yingshu Chen, Longwei Li et al.
Language Models Are Implicitly Continuous
Samuele Marro, Davide Evangelista, X. Huang et al.
Designing Mechanical Meta-Materials by Learning Equivariant Flows
Mehran Mirramezani, Anne Meeussen, Katia Bertoldi et al.
Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation
Chen Xu, Yuxin Li, Wenjie Wang et al.
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
Saptarshi Chakraborty, Peter Bartlett
Learning Splitting Heuristics in Divide-and-Conquer SAT Solvers with Reinforcement Learning
Shumao Zhai, Ning Ge
HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
YUJIE MO, Runpeng Yu, Xiaofeng Zhu et al.
Classification with Conceptual Safeguards
Hailey Joren, Charles Marx, Berk Ustun
Maximum Entropy Model Correction in Reinforcement Learning
Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh et al.
Fair Clustering in the Sliding Window Model
Vincent Cohen-Addad, Shaofeng Jiang, Qiaoyuan Yang et al.
Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
Iosif Sakos, Stefanos Leonardos, Stelios Stavroulakis et al.
Rethinking Multiple-Instance Learning From Feature Space to Probability Space
Zhaolong Du, Shasha Mao, Xuequan Lu et al.
Linear Bandits with Memory
Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
Jonas Linkerhägner, Cheng Shi, Ivan Dokmanić
An Online Learning Theory of Trading-Volume Maximization
Tommaso Cesari, Roberto Colomboni
Training Free Exponential Context Extension via Cascading KV Cache
Jeff Willette, Heejun Lee, Youngwan Lee et al.
Neural Phylogeny: Fine-Tuning Relationship Detection among Neural Networks
Runpeng Yu, Xinchao Wang
Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models
Jeffrey Gu, Serena Yeung
CHAMP: Conformalized 3D Human Multi-Hypothesis Pose Estimators
Harry Zhang, Luca Carlone
Learning Color Equivariant Representations
Yulong Yang, Felix O'Mahony, Christine Allen-Blanchette
3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D Editing
Jiahua Dong, Yu-Xiong Wang
Graph Transformers Dream of Electric Flow
Xiang Cheng, Lawrence Carin, Suvrit Sra
Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
Hoang Khoi Nguyen Do, Truc Nguyen, Malik Hassanaly et al.
Flash Inference: Near Linear Time Inference for Long Convolution Sequence Models and Beyond
Costin-Andrei Oncescu, Sanket Jayant Purandare, Stratos Idreos et al.
Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
Tianchi Xie, Jiangning Zhu, Guozu Ma et al.
Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection
Ziqing Fan, Siyuan Du, Shengchao Hu et al.
Towards Faster Decentralized Stochastic Optimization with Communication Compression
Rustem Islamov, Yuan Gao, Sebastian Stich
UNIP: Rethinking Pre-trained Attention Patterns for Infrared Semantic Segmentation
Tao Zhang, Jinyong Wen, Zhen Chen et al.
On the Byzantine-Resilience of Distillation-Based Federated Learning
Christophe Roux, Max Zimmer, Sebastian Pokutta
Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression
Shuang Liang, Guido Montufar
MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion
Onkar Susladkar, Jishu Sen Gupta, Chirag Sehgal et al.
Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning
Jingyang Li, Jiachun Pan, Vincent Tan et al.
T2V-Turbo-v2: Enhancing Video Model Post-Training through Data, Reward, and Conditional Guidance Design
Jiachen Li, Qian Long, Jian (Skyler) Zheng et al.
Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition
Róisín Luo, James McDermott, Colm O'Riordan
How Low Can You Go? Searching for the Intrinsic Dimensionality of Complex Networks using Metric Node Embeddings
Nikolaos Nakis, Niels Raunkjær Holm, Andreas Lyhne Fiehn et al.
Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs
Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham
Evaluating Semantic Variation in Text-to-Image Synthesis: A Causal Perspective
Xiangru Zhu, Penglei Sun, Yaoxian Song et al.
UIFace: Unleashing Inherent Model Capabilities to Enhance Intra-Class Diversity in Synthetic Face Recognition
Xiao Lin, Yuge Huang, Jianqing Xu et al.
Efficient Masked AutoEncoder for Video Object Counting and A Large-Scale Benchmark
Bing Cao, Quanhao Lu, Jiekang Feng et al.
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev et al.
Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models
Theo Bourdais, Houman Owhadi
DS-LLM: Leveraging Dynamical Systems to Enhance Both Training and Inference of Large Language Models
Ruibing Song, Chuan Liu, Chunshu Wu et al.
Rational Decision-Making Agent with Learning Internal Utility Judgment
Yining Ye, Xin Cong, Shizuo Tian et al.
Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video
Xiangming Zhu, Huayu Deng, Haochen Yuan et al.
Progressive Parameter Efficient Transfer Learning for Semantic Segmentation
Nan Zhou, Huiqun Wang, Yaoyan Zheng et al.
The adaptive complexity of parallelized log-concave sampling
Huanjian Zhou, Baoxiang Wang, Masashi Sugiyama
Discovering Group Structures via Unitary Representation Learning
Dongsung Huh
Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games
Brian Zhang, Gabriele Farina, Tuomas Sandholm
Advancing Out-of-Distribution Detection via Local Neuroplasticity
Alessandro Canevaro, Julian Schmidt, Sajad Marvi et al.
Mean Field Theory in Deep Metric Learning
Takuya Furusawa
Debiasing Mini-Batch Quadratics for Applications in Deep Learning
Lukas Nicola Tatzel, Bálint Mucsányi, Osane Hackel et al.
ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs
Hao Di, Tong He, Haishan Ye et al.
Online Reinforcement Learning in Non-Stationary Context-Driven Environments
Pouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf et al.
Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks
Rushang Karia, Daniel Bramblett, Daksh Dobhal et al.
Prototype antithesis for biological few-shot class-incremental learning
Binghao Liu, Han Yang, Fang Wan et al.
Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing
Elad Romanov, Fangzhao Zhang, Mert Pilanci
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
Yushun Dong, Patrick Soga, Yinhan He et al.
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz et al.
Isometric Regularization for Manifolds of Functional Data
Hyeongjun Heo, Seonghun Oh, JaeYong Lee et al.
DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking head Video Generation
Hanbo Cheng, Limin Lin, Chenyu Liu et al.
Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning
Bo Yue, Shufan Wang, Ashish Gaurav et al.
How to Find the Exact Pareto Front for Multi-Objective MDPs?
Yining Li, Peizhong Ju, Ness Shroff
Probabilistic Geometric Principal Component Analysis with application to neural data
Han-Lin Hsieh, Maryam Shanechi
CoMotion: Concurrent Multi-person 3D Motion
Alejandro Newell, Peiyun Hu, Lahav Lipson et al.
The Rise and Down of Babel Tower: Investigating the Evolution Process of Multilingual Code Large Language Model
Jiawei Chen, Wentao Chen, Jing Su et al.