ICLR Papers
6,124 papers found • Page 121 of 123
Understanding Expressivity of GNN in Rule Learning
Haiquan Qiu, Yongqi Zhang, Yong Li et al.
Understanding In-Context Learning from Repetitions
Jianhao (Elliott) Yan, Jin Xu, Chiyu Song et al.
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
Satwik Bhattamishra, Arkil Patel, Phil Blunsom et al.
Understanding prompt engineering may not require rethinking generalization
Victor Akinwande, Yiding Jiang, Dylan Sam et al.
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation
Noel Loo, Ramin Hasani, Mathias Lechner et al.
Understanding the Effects of RLHF on LLM Generalisation and Diversity
Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis et al.
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods
Avery Ma, Yangchen Pan, Amir-massoud Farahmand
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
Yihao Xue, Siddharth Joshi, Dang Nguyen et al.
Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks
Hung Quang Nguyen, Yingjie Lao, Tung Pham et al.
Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP
Zixiang Chen, Yihe Deng, Yuanzhi Li et al.
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates
Nicholas Corrado, Josiah Hanna
Uni3D: Exploring Unified 3D Representation at Scale
Junsheng Zhou, Jinsheng Wang, Baorui Ma et al.
UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal Modeling
Haoyu Lu, Yuqi Huo, Guoxing Yang et al.
Unified Generative Modeling of 3D Molecules with Bayesian Flow Networks
Yuxuan Song, Jingjing Gong, Hao Zhou et al.
Unified Human-Scene Interaction via Prompted Chain-of-Contacts
Zeqi Xiao, Tai Wang, Jingbo Wang et al.
Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization
Yang Jin, Kun Xu, Kun Xu et al.
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization
Mohammad Pedramfar, Yididiya Nadew, Chris Quinn et al.
Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence
Sunghwan Hong, Seokju Cho, Seungryong Kim et al.
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
Kun LEI, Zhengmao He, Chenhao Lu et al.
Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
Yifu Yuan, Jianye HAO, Yi Ma et al.
UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science
Yazheng Yang, Yuqi Wang, Guang Liu et al.
Universal Backdoor Attacks
Benjamin Schneider, Nils Lukas, Florian Kerschbaum
Universal Guidance for Diffusion Models
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild et al.
Universal Humanoid Motion Representations for Physics-Based Control
Zhengyi Luo, Jinkun Cao, Josh Merel et al.
Universal Jailbreak Backdoors from Poisoned Human Feedback
Javier Rando, Florian Tramer
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
Wenxuan Zhou, Sheng Zhang, Yu Gu et al.
Unknown Domain Inconsistency Minimization for Domain Generalization
Seungjae Shin, HeeSun Bae, Byeonghu Na et al.
Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation
Hongtao Wu, Ya Jing, Chilam Cheang et al.
Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND
Qiyu Kang, Kai Zhao, Qinxu Ding et al.
Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning
Ruizhe Shi, Yuyao Liu, Yanjie Ze et al.
Unlocking the Power of Representations in Long-term Novelty-based Exploration
Alaa Saade, Steven Kapturowski, Daniele Calandriello et al.
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
Zhaowei Zhu, Jialu Wang, Hao Cheng et al.
Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation
Devavrat Tomar, Guillaume Vray, Jean-Philippe Thiran et al.
Unpaired Image-to-Image Translation via Neural Schrödinger Bridge
Beomsu Kim, Gihyun Kwon, Kwanyoung Kim et al.
Unprocessing Seven Years of Algorithmic Fairness
André F. Cruz, Moritz Hardt
Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space
Yufei Gu, Xiaoqing Zheng, Tomaso Aste
Unraveling the Key Components of OOD Generalization via Diversification
Harold Benoit, Liangze Jiang, Andrei Atanov et al.
UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models
Hyunju Kang, Geonhee Han, Hogun Park
Unsupervised Order Learning
Seon-Ho Lee, Nyeong-Ho Shin, Chang-Su Kim
Unsupervised Pretraining for Fact Verification by Language Model Distillation
Adrian Bazaga, Pietro Lio, Gos Micklem
Unveiling and Manipulating Prompt Influence in Large Language Models
Zijian Feng, Hanzhang Zhou, ZIXIAO ZHU et al.
Unveiling Options with Neural Network Decomposition
Mahdi Alikhasi, Levi Lelis
Unveiling the Pitfalls of Knowledge Editing for Large Language Models
Zhoubo Li, Ningyu Zhang, Yunzhi Yao et al.
Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels
Zahra Babaiee, Peyman Kiasari, Daniela Rus et al.
USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields
Moyang Li, Peng Wang, Lingzhe Zhao et al.
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation
Kim-Celine Kahl, Carsten Lüth, Maximilian Zenk et al.
Vanishing Gradients in Reinforcement Finetuning of Language Models
Noam Razin, Hattie Zhou, Omid Saremi et al.
Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits
Qiwei Di, Tao Jin, Yue Wu et al.
Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data
Xiong Zhou, Xianming Liu, Hao Yu et al.
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions
Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas