ICLR 2024 Papers
2,297 papers found • Page 44 of 46
Tree-Planner: Efficient Close-loop Task Planning with Large Language Models
Mengkang Hu, Yao Mu, Xinmiao Yu et al.
Tree Search-Based Policy Optimization under Stochastic Execution Delay
David Valensi, Esther Derman, Shie Mannor et al.
T-Rep: Representation Learning for Time Series using Time-Embeddings
Archibald Fraikin, Adrien Bennetot, Stephanie Allassonniere
True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning
Weihao Tan, Wentao Zhang, Shanqi Liu et al.
Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning
Bingchen Zhao, Haoqin Tu, Chen Wei et al.
Turning large language models into cognitive models
Marcel Binz, Eric Schulz
TUVF: Learning Generalizable Texture UV Radiance Fields
An-Chieh Cheng, Xueting Li, Sifei Liu et al.
Two-stage LLM Fine-tuning with Less Specialization and More Generalization
Yihan Wang, Si Si, Daliang Li et al.
Two-timescale Extragradient for Finding Local Minimax Points
Jiseok Chae, Kyuwon Kim, Donghwan Kim
UC-NERF: Neural Radiance Field for Under-Calibrated Multi-View Cameras in Autonomous Driving
Kai Cheng, Xiaoxiao Long, Wei Yin et al.
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation
Luca Eyring, Dominik Klein, Théo Uscidda et al.
Unbiased Watermark for Large Language Models
Zhengmian Hu, Lichang Chen, Xidong Wu et al.
Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning
Sheng Xu, Guiliang Liu
Uncertainty-aware Graph-based Hyperspectral Image Classification
Linlin Yu, Yifei Lou, Feng Chen
Uncertainty Quantification via Stable Distribution Propagation
Felix Petersen, Aashwin Mishra, Hilde Kuehne et al.
Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning
James Chapman, Lennie Wells, Ana Lawry Aguila
Understanding Addition in Transformers
Philip Quirke, Fazl Barez
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
Hao Chen, Jindong Wang, Ankit Parag Shah et al.
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression
Runtian Zhai, Bingbin Liu, Andrej Risteski et al.
Understanding Catastrophic Forgetting in Language Models via Implicit Inference
Suhas Kotha, Jacob Springer, Aditi Raghunathan
Understanding Certified Training with Interval Bound Propagation
Yuhao Mao, Mark N Müller, Marc Fischer et al.
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory
Wei Huang, Ye Shi, Zhongyi Cai et al.
Understanding Domain Generalization: A Noise Robustness Perspective
Rui Qiao, Bryan Kian Hsiang Low
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.