Most Cited ICLR "iterative feedback" Papers
6,124 papers found • Page 14 of 31
Conference
Exact Certification of (Graph) Neural Networks Against Label Poisoning
Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann et al.
Revisiting Mode Connectivity in Neural Networks with Bezier Surface
Jie Ren, Pin-Yu Chen, Ren Wang
Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
Byungjai Kim, Chanho Ahn, Wissam Baddar et al.
ClawMachine: Learning to Fetch Visual Tokens for Referential Comprehension
Tianren Ma, Lingxi Xie, Yunjie Tian 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.
Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
Iosif Sakos, Stefanos Leonardos, Stelios Stavroulakis et al.
Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers
Tiberiu Mușat
Aligning Visual Contrastive learning models via Preference Optimization
Amirabbas Afzali, Borna khodabandeh, Ali Rasekh et al.
Exploring a Principled Framework for Deep Subspace Clustering
Xianghan Meng, Zhiyuan Huang, Wei He et al.
Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off
Futa Waseda, Ching-Chun Chang, Isao Echizen
Fast Uncovering of Protein Sequence Diversity from Structure
Luca Alessandro Silva, Barthelemy Meynard-Piganeau, Carlo Lucibello et al.
Multi-Dimensional Conformal Prediction
Yam Tawachi, Bracha Laufer-Goldshtein
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
RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
Tanya Chowdhury, Yair Zick, James Allan
MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations
Shaochen Zhong, Yifan (Louie) Lu, Lize Shao et al.
PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
Rana Muhammad Shahroz Khan, Pingzhi Li, Sukwon Yun et al.
EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation
Carl Qi, Dan Haramati, Tal Daniel et al.
Out-Of-Domain Unlabeled Data Improves Generalization
seyed amir hossein saberi, Amir Najafi, Alireza Heidari et al.
Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks
Théophane Vallaeys, Matthew J Muckley, Jakob Verbeek et al.
Learning to Steer Markovian Agents under Model Uncertainty
Jiawei Huang, Vinzenz Thoma, Zebang Shen et al.
Spectrally Transformed Kernel Regression
Runtian Zhai, Rattana Pukdee, Roger Jin et al.
Direct Distributional Optimization for Provable Alignment of Diffusion Models
Ryotaro Kawata, Kazusato Oko, Atsushi Nitanda et al.
Towards Synergistic Path-based Explanations for Knowledge Graph Completion: Exploration and Evaluation
Tengfei Ma, Xiang song, Wen Tao et al.
DUALFormer: Dual Graph Transformer
Zhuo Jiaming, Yuwei Liu, Yintong Lu et al.
On-the-fly Preference Alignment via Principle-Guided Decoding
Mingye Zhu, Yi Liu, Lei Zhang et al.
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations
Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter et al.
DICE: Data Influence Cascade in Decentralized Learning
Tongtian Zhu, Wenhao Li, Can Wang et al.
Nonlinear multiregion neural dynamics with parametric impulse response communication channels
Matthew Dowling, Cristina Savin
Morphing Tokens Draw Strong Masked Image Models
Taekyung Kim, Byeongho Heo, Dongyoon Han
Storybooth: Training-Free Multi-Subject Consistency for Improved Visual Storytelling
Jaskirat Singh, Junshen K Chen, Jonas Kohler et al.
Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture
Sajad Movahedi, Antonio Orvieto, Seyed-Mohsen Moosavi-Dezfooli
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation
Tobias Leemann, Periklis Petridis, Giuseppe Vietri et al.
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar et al.
Task Descriptors Help Transformers Learn Linear Models In-Context
Ruomin Huang, Rong Ge
Certifying Language Model Robustness with Fuzzed Randomized Smoothing: An Efficient Defense Against Backdoor Attacks
Bowei He, Lihao Yin, Huiling Zhen et al.
Designing Mechanical Meta-Materials by Learning Equivariant Flows
Mehran Mirramezani, Anne Meeussen, Katia Bertoldi et al.
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
Indraneil Paul, Haoyi Yang, Goran Glavaš et al.
SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting
Huajian Huang, Yingshu Chen, Longwei Li et al.
Exploring The Loss Landscape Of Regularized Neural Networks Via Convex Duality
Sungyoon Kim, Aaron Mishkin, Mert Pilanci
FOSP: Fine-tuning Offline Safe Policy through World Models
Chenyang Cao, Yucheng Xin, Silang Wu et al.
Adaptive backtracking for faster optimization
Joao V. Cavalcanti, Laurent Lessard, Ashia Wilson
Divergence-Regularized Discounted Aggregation: Equilibrium Finding in Multiplayer Partially Observable Stochastic Games
Runyu Lu, Yuanheng Zhu, Dongbin Zhao
Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images
Hannah Kniesel, Leon Sick, Tristan Payer et al.
Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives
Marcel Hirt, Domenico Campolo, Victoria Leong et al.
COFlowNet: Conservative Constraints on Flows Enable High-Quality Candidate Generation
Yudong Zhang, Xuan Yu, Xu Wang et al.
Generalization of Scaled Deep ResNets in the Mean-Field Regime
Yihang Chen, Fanghui Liu, Yiping Lu et al.
SoftMatcha: A Soft and Fast Pattern Matcher for Billion-Scale Corpus Searches
Hiroyuki Deguchi, Go Kamoda, Yusuke Matsushita et al.
Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods
Hossein Taheri, Christos Thrampoulidis, Arya Mazumdar
Stabilizing Backpropagation Through Time to Learn Complex Physics
Patrick Schnell, Nils Thuerey
Brain-inspired $L_p$-Convolution benefits large kernels and aligns better with visual cortex
Jea Kwon, Sungjun Lim, Kyungwoo Song et al.
AutoCGP: Closed-Loop Concept-Guided Policies from Unlabeled Demonstrations
Pei Zhou, Ruizhe Liu, Qian Luo et al.
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Mathieu Chevalley, Patrick Schwab, Arash Mehrjou
Learned Reference-based Diffusion Sampler for multi-modal distributions
Maxence Noble, Louis Grenioux, Marylou Gabrié et al.
NetInfoF Framework: Measuring and Exploiting Network Usable Information
Meng-Chieh Lee, Haiyang Yu, Jian Zhang et al.
Privately Counting Partially Ordered Data
Matthew Joseph, Mónica Ribero, Alexander Yu
Teaching Human Behavior Improves Content Understanding Abilities Of VLMs
SOMESH SINGH, Harini S I, Yaman Singla et al.
CarbonSense: A Multimodal Dataset and Baseline for Carbon Flux Modelling
Matthew Fortier, Mats L. Richter, Oliver Sonnentag et al.
L-WISE: Boosting Human Visual Category Learning Through Model-Based Image Selection and Enhancement
Morgan B Talbot, Gabriel Kreiman, James DiCarlo et al.
Debiasing Mini-Batch Quadratics for Applications in Deep Learning
Lukas Nicola Tatzel, Bálint Mucsányi, Osane Hackel et al.
Bonsai: Gradient-free Graph Condensation for Node Classification
Mridul Gupta, Samyak Jain, Vansh Ramani et al.
Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
Luofeng Liao, Christian Kroer, Sergei Leonenkov et al.
Efficient Sparse PCA via Block-Diagonalization
Alberto Del Pia, Dekun Zhou, Yinglun Zhu
Spectro-Riemannian Graph Neural Networks
Karish Grover, Haiyang Yu, Xiang song et al.
Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model
Siyu Chen, Beining Wu, Miao Lu et al.
KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks
Dominik Scheuer, Frederic Runge, Jörg Franke et al.
Efficient Biological Data Acquisition through Inference Set Design
Ihor Neporozhnii, Julien Roy, Emmanuel Bengio et al.
Masked Distillation Advances Self-Supervised Transformer Architecture Search
Caixia Yan, Xiaojun Chang, Zhihui Li et al.
FLOPS: Forward Learning with OPtimal Sampling
Tao Ren, Zishi Zhang, Jinyang Jiang et al.
Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning
Xinsong Feng, Zihan Yu, Yanhai Xiong et al.
Learning 3D Perception from Others' Predictions
Jinsu Yoo, Zhenyang Feng, Tai-Yu Pan et al.
TimeInf: Time Series Data Contribution via Influence Functions
Yizi Zhang, Jingyan Shen, Xiaoxue Xiong et al.
Learning Spatiotemporal Dynamical Systems from Point Process Observations
Valerii Iakovlev, Harri Lähdesmäki
Matrix Product Sketching via Coordinated Sampling
Majid Daliri, Juliana Freire, Danrong Li et al.
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions
Adel Javanmard, Lin Chen, Vahab Mirrokni et al.
A Generalist Hanabi Agent
Arjun V Sudhakar, Hadi Nekoei, Mathieu Reymond et al.
Algorithmic Stability Based Generalization Bounds for Adversarial Training
Runzhi Tian, Yongyi Mao
Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression
Shuang Liang, Guido Montufar
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
Ziping Xu, Zifan Xu, Runxuan Jiang et al.
Towards Faster Decentralized Stochastic Optimization with Communication Compression
Rustem Islamov, Yuan Gao, Sebastian Stich
Multimodal Lego: Model Merging and Fine-Tuning Across Topologies and Modalities in Biomedicine
Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik
Enabling Lanuguage Models to Implicitly Learn Self-Improvement
Ziqi Wang, Le Hou, Tianjian Lu et al.
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
Yushun Dong, Patrick Soga, Yinhan He et al.
UIFace: Unleashing Inherent Model Capabilities to Enhance Intra-Class Diversity in Synthetic Face Recognition
Xiao Lin, Yuge Huang, Jianqing Xu et al.
Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs
Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham
MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion
Onkar Susladkar, Jishu Sen Gupta, Chirag Sehgal et al.
DS-LLM: Leveraging Dynamical Systems to Enhance Both Training and Inference of Large Language Models
Ruibing Song, Chuan Liu, Chunshu Wu 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.
Language-Assisted Feature Transformation for Anomaly Detection
EungGu Yun, Heonjin Ha, Yeongwoo Nam et al.
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.
Test-time Adaptation for Image Compression with Distribution Regularization
Kecheng Chen, Pingping Zhang, Tiexin Qin et al.
PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows
Huaguan Chen, Yang Liu, Hao Sun
Diffusion Sampling with Momentum for Mitigating Divergence Artifacts
Suttisak Wisadwongsa, Worameth Chinchuthakun, Pramook Khungurn et al.
Principled Architecture-aware Scaling of Hyperparameters
Wuyang Chen, Junru Wu, Zhangyang Wang et al.
No Location Left Behind: Measuring and Improving the Fairness of Implicit Representations for Earth Data
Daniel Cai, Randall Balestriero
Prototype antithesis for biological few-shot class-incremental learning
Binghao Liu, Han Yang, Fang Wan et al.
A Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Guang-Yuan Hao et al.
Isometric Regularization for Manifolds of Functional Data
Hyeongjun Heo, Seonghun Oh, JaeYong Lee et al.
Global Convergence of Policy Gradient in Average Reward MDPs
Navdeep Kumar, Yashaswini Murthy, Itai Shufaro et al.
Generalizable Motion Planning via Operator Learning
Sharath Matada, Luke Bhan, Yuanyuan Shi et al.
Mean Field Theory in Deep Metric Learning
Takuya Furusawa
Data-centric Prediction Explanation via Kernelized Stein Discrepancy
Mahtab Sarvmaili, Hassan Sajjad, Ga Wu
Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline
Hongjoon Ahn, Jinu Hyeon, Youngmin Oh et al.
Bounds on $L_p$ Errors in Density Ratio Estimation via $f$-Divergence Loss Functions
Yoshiaki Kitazawa
Enhancing Document Understanding with Group Position Embedding: A Novel Approach to Incorporate Layout Information
Yuke Zhu, Yue Zhang, Dongdong Liu et al.
Exact Community Recovery under Side Information: Optimality of Spectral Algorithms
Julia Gaudio, Nirmit Joshi
CBMA: Improving Conformal Prediction through Bayesian Model Averaging
Pankaj Bhagwat, Linglong Kong, Bei Jiang
ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Sentences
Yuxin Wang, Xiaomeng Zhu, Weimin Lyu et al.
DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking head Video Generation
Hanbo Cheng, Limin Lin, Chenyu Liu et al.
Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration
Heyang Zhao, Xingrui Yu, David Bossens et al.
Beyond Next Token Prediction: Patch-Level Training for Large Language Models
Chenze Shao, Fandong Meng, Jie Zhou
Efficient Online Pruning and Abstraction for Imperfect Information Extensive-Form Games
Boning Li, Longbo Huang
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
Yan Scholten, Stephan Günnemann
An Efficient Framework for Crediting Data Contributors of Diffusion Models
MingYu Lu, Chris Lin, Chanwoo Kim et al.
Content-Style Learning from Unaligned Domains: Identifiability under Unknown Latent Dimensions
Sagar Shrestha, Xiao Fu
Graph Transformers Dream of Electric Flow
Xiang Cheng, Lawrence Carin, Suvrit Sra
Fine-tuning with Reserved Majority for Noise Reduction
Shuyang Jiang, Yusheng Liao, Ya Zhang et al.
Inner Information Analysis Algorithm for Deep Neural Network based on Community
Guipeng Lan, Shuai Xiao, Meng Xi et al.
Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
Tianchi Xie, Jiangning Zhu, Guozu Ma et al.
Cross-Attention Head Position Patterns Can Align with Human Visual Concepts in Text-to-Image Generative Models
Jungwon Park, Jungmin Ko, Dongnam Byun et al.
Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation
Linda He, Jue Wang, Maurice Weber et al.
Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer
XINYUE HU, Zhibin Duan, Bo Chen et al.
Action abstractions for amortized sampling
Oussama Boussif, Léna Ezzine, Joseph Viviano et al.
A Statistical Approach for Controlled Training Data Detection
Zirui Hu, Yingjie Wang, Zheng Zhang et al.
SEBRA : Debiasing through Self-Guided Bias Ranking
Adarsh Kappiyath, Abhra Chaudhuri, AJAY JAISWAL et al.
Gradient correlation is a key ingredient to accelerate SGD with momentum
Julien Hermant, Marien Renaud, Jean-François Aujol et al.
Query-based Knowledge Transfer for Heterogeneous Learning Environments
Norah Alballa, Wenxuan Zhang, Ziquan Liu et al.
Gaussian Mixture Counterfactual Generator
Jong-Hoon Ahn, Akshay Vashist
Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection
Ziqing Fan, Siyuan Du, Shengchao Hu et al.
Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video
Xiangming Zhu, Huayu Deng, Haochen Yuan et al.
PianoMotion10M: Dataset and Benchmark for Hand Motion Generation in Piano Performance
Qijun Gan, Song Wang, Shengtao Wu et al.
Learning system dynamics without forgetting
Xikun ZHANG, Dongjin Song, Yushan Jiang et al.
Fast unsupervised ground metric learning with tree-Wasserstein distance
Kira Michaela Düsterwald, Samo Hromadka, Makoto Yamada
Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers
Runyi Zhao, Sheng Xu, Bo Yue et al.
Uncovering Gaps in How Humans and LLMs Interpret Subjective Language
Erik Jones, Arjun Patrawala, Jacob Steinhardt
Endowing Visual Reprogramming with Adversarial Robustness
Shengjie Zhou, Xin Cheng, Haiyang Xu et al.
Wavelet-based Positional Representation for Long Context
Yui Oka, Taku Hasegawa, Kyosuke Nishida et al.
Bayesian Analysis of Combinatorial Gaussian Process Bandits
Jack Sandberg, Niklas Åkerblom, Morteza Haghir Chehreghani
Residual Deep Gaussian Processes on Manifolds
Kacper Wyrwal, Andreas Krause, Viacheslav (Slava) Borovitskiy
On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation
Xinyu Ye, Hao Xiong, Jianhao Huang et al.
Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
Yupei Yang, Biwei Huang, Fan Feng et al.
INFER: A Neural-symbolic Model For Extrapolation Reasoning on Temporal Knowledge Graph
Ningyuan Li, Haihong E, Tianyu Yao et al.
Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models
Yongjin Yang, Sihyeon Kim, Hojung Jung et al.
Evaluating Semantic Variation in Text-to-Image Synthesis: A Causal Perspective
Xiangru Zhu, Penglei Sun, Yaoxian Song et al.
Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
Hoang Khoi Nguyen Do, Truc Nguyen, Malik Hassanaly et al.
Efficient Masked AutoEncoder for Video Object Counting and A Large-Scale Benchmark
Bing Cao, Quanhao Lu, Jiekang Feng et al.
Durable Quantization Conditioned Misalignment Attack on Large Language Models
Peiran Dong, Haowei Li, Song Guo
On the Byzantine-Resilience of Distillation-Based Federated Learning
Christophe Roux, Max Zimmer, Sebastian Pokutta
Exploring the Camera Bias of Person Re-identification
Myungseo Song, Jin-Woo Park, Jong-Seok Lee
Flash Inference: Near Linear Time Inference for Long Convolution Sequence Models and Beyond
Costin-Andrei Oncescu, Sanket Jayant Purandare, Stratos Idreos et al.
Toward Efficient Multi-Agent Exploration With Trajectory Entropy Maximization
Tianxu Li, Kun Zhu
SparsyFed: Sparse Adaptive Federated Learning
Adriano Guastella, Lorenzo Sani, Alex Iacob et al.
A Multiscale Frequency Domain Causal Framework for Enhanced Pathological Analysis
Xiaoyu Cui, Weixing Chen, Jiandong Su
Supervised and Semi-Supervised Diffusion Maps with Label-Driven Diffusion
Harel Mendelman, Ronen Talmon
Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows
Xiangxin Zhou, Yi Xiao, Haowei Lin et al.
TFG-Flow: Training-free Guidance in Multimodal Generative Flow
Haowei Lin, Shanda Li, Haotian Ye et al.
The adaptive complexity of parallelized log-concave sampling
Huanjian Zhou, Baoxiang Wang, Masashi Sugiyama
Accurate and Scalable Graph Neural Networks via Message Invariance
Zhihao Shi, Jie Wang, Zhiwei Zhuang et al.
Non-Stationary Dueling Bandits Under a Weighted Borda Criterion
Joe Suk, Arpit Agarwal
Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data
Xinran Liu, Yikun Bai, Rocio Diaz Martin et al.
MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds
Leon Hetzel, Johanna Sommer, Bastian Rieck et al.
Progressive Parameter Efficient Transfer Learning for Semantic Segmentation
Nan Zhou, Huiqun Wang, Yaoyan Zheng et al.
Graph Neural Networks Can (Often) Count Substructures
Paolo Pellizzoni, Till Schulz, Karsten Borgwardt
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
Ruikun Li, Huandong Wang, Qingmin Liao et al.
Geometry-Aware Approaches for Balancing Performance and Theoretical Guarantees in Linear Bandits
Yuwei Luo, Mohsen Bayati
AI2TALE: An Innovative Information Theory-based Approach for Learning to Localize Phishing Attacks
Van Nguyen, Tingmin Wu, Xingliang YUAN et al.
Swing-by Dynamics in Concept Learning and Compositional Generalization
Yongyi Yang, Core Francisco Park, Ekdeep Singh Lubana 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.
Gaussian Head & Shoulders: High Fidelity Neural Upper Body Avatars with Anchor Gaussian Guided Texture Warping
Tianhao Wu, Jing Yang, Zhilin Guo et al.
Dreamweaver: Learning Compositional World Models from Pixels
Junyeob Baek, Yi-Fu Wu, Gautam Singh et al.
Learning from Imperfect Human Feedback: A Tale from Corruption-Robust Dueling
Yuwei Cheng, Fan Yao, Xuefeng Liu et al.
ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs
Hao Di, Tong He, Haishan Ye et al.
CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical Systems
Long Wei, Haodong Feng, Yuchen Yang et al.
UNIP: Rethinking Pre-trained Attention Patterns for Infrared Semantic Segmentation
Tao Zhang, Jinyong Wen, Zhen Chen et al.
The Complexity of Two-Team Polymatrix Games with Independent Adversaries
Alexandros Hollender, Gilbert Maystre, Sai Ganesh Nagarajan
DEPT: Decoupled Embeddings for Pre-training Language Models
Alex Iacob, Lorenzo Sani, Meghdad Kurmanji et al.
Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks
Rushang Karia, Daniel Bramblett, Daksh Dobhal et al.
Easing Training Process of Rectified Flow Models Via Lengthening Inter-Path Distance
Shifeng Xu, Yanzhu Liu, Adams Kong
Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density
Sabine Susstrunk, Mathieu Salzmann, Chen Liu et al.
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs
Thien Le, Luana Ruiz, Stefanie Jegelka
Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension ability
Yujin Han, Lei Xu, Sirui Chen et al.
PaLD: Detection of Text Partially Written by Large Language Models
Eric Lei, Hsiang Hsu, Chun-Fu Chen
Towards a learning theory of representation alignment
Francesco Maria Gabriele Insulla, Shuo Huang, Lorenzo Rosasco
Identification of Intermittent Temporal Latent Process
Yuke Li, Yujia Zheng, Guangyi Chen et al.
Rational Decision-Making Agent with Learning Internal Utility Judgment
Yining Ye, Xin Cong, Shizuo Tian et al.
Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Transformers
Shaobo Wang, Hongxuan Tang, Mingyang Wang 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
Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers
Yuchen Liang, Peizhong Ju, Yingbin Liang et al.
GeSubNet: Gene Interaction Inference for Disease Subtype Network Generation
Ziwei Yang, Zheng Chen, XIN LIU et al.
Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization
Yuanchao Wang, Zhao-Rong Lai, Tianqi Zhong
ProtoSnap: Prototype Alignment For Cuneiform Signs
Rachel Mikulinsky, Morris Alper, Shai Gordin et al.
From Search to Sampling: Generative Models for Robust Algorithmic Recourse
Prateek Garg, Lokesh Nagalapatti, Sunita Sarawagi
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.
Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification
Mehdi Naouar, Hanne Raum, Jens Rahnfeld et al.
VICtoR: Learning Hierarchical Vision-Instruction Correlation Rewards for Long-horizon Manipulation
Kuo-Han Hung, Pang-Chi Lo, Jia-Fong Yeh et al.
Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition
Róisín Luo, James McDermott, Colm O'Riordan
AutoG: Towards automatic graph construction from tabular data
Zhikai Chen, Han Xie, Jian Zhang et al.
Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models
Zeyu Zhou, Ruqi Bai, Sean Kulinski et al.