ICLR Papers
6,124 papers found • Page 6 of 123
A Simple yet Effective $\Delta\Delta G$ Predictor is An Unsupervised Antibody Optimizer and Explainer
Lirong Wu, Yunfan Liu, Haitao Lin et al.
A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals
Grace Liu, Michael Tang, Benjamin Eysenbach
Ask, and it shall be given: On the Turing completeness of prompting
Ruizhong Qiu, Zhe Xu, Wenxuan Bao et al.
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
Yingyu Lin, Yuxing Huang, Wenqin Liu et al.
As large as it gets – Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters
Margret Keuper, Julia Grabinski, Janis Keuper
A Solvable Attention for Neural Scaling Laws
Bochen Lyu, Di Wang, Zhanxing Zhu
A Spark of Vision-Language Intelligence: 2-Dimensional Autoregressive Transformer for Efficient Finegrained Image Generation
Liang Chen, Sinan Tan, Zefan Cai et al.
AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly
Hongyu Guo, Yoshua Bengio, Shengchao Liu
As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss
Xin Mao, Huimin Xu, Feng-Lin Li et al.
Associative memory and dead neurons
Vladimir Fanaskov, Ivan Oseledets
A Statistical Approach for Controlled Training Data Detection
Zirui Hu, Yingjie Wang, Zheng Zhang et al.
A Statistical Framework for Ranking LLM-based Chatbots
Siavash Ameli, Siyuan Zhuang, Ion Stoica et al.
A Stochastic Approach to the Subset Selection Problem via Mirror Descent
Dan Greenstein, Elazar Gershuni, Ilan Ben-Bassat et al.
ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks
Prakash Chandra Chhipa, Gautam Vashishtha, Jithamanyu Settur et al.
AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data
Tuan Truong, Rithwik Sudharsan, Yibo Yang et al.
Asymmetric Factorized Bilinear Operation for Vision Transformer
Junjie Wu, Qilong Wang, Jiangtao Xie et al.
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
Samet Demir, Zafer Dogan
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis
Guangchen (Eric) Lan, Dong-Jun Han, Abolfazl Hashemi et al.
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux et al.
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
A Theoretical Framework for Partially-Observed Reward States in RLHF
Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano et al.
A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules
Shih-Hsin Wang, Yuhao Huang, Justin Baker et al.
A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops
Shi Fu, Yingjie Wang, Yuzhu Chen et al.
A Theory for Token-Level Harmonization in Retrieval-Augmented Generation
Shicheng Xu, Liang Pang, Huawei Shen et al.
A Theory of Initialisation's Impact on Specialisation
Devon Jarvis, Sebastian Lee, Clementine Domine et al.
A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems
Shulan Zhu, Chenglong Bao, Defeng Sun et al.
Atlas Gaussians Diffusion for 3D Generation
Haitao Yang, Yuan Dong, Hanwen Jiang et al.
Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation
Yikun Zhang, Geyan Ye, Chaohao Yuan et al.
AtomSurf: Surface Representation for Learning on Protein Structures
Vincent Mallet, Yangyang Miao, Souhaib Attaiki et al.
A Training-Free Sub-quadratic Cost Transformer Model Serving Framework with Hierarchically Pruned Attention
Heejun Lee, Geon Park, Youngwan Lee et al.
A Transfer Attack to Image Watermarks
Yuepeng Hu, Zhengyuan Jiang, Moyang Guo et al.
A transfer learning framework for weak to strong generalization
Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee et al.
A Truncated Newton Method for Optimal Transport
Mete Kemertas, Amir-massoud Farahmand, Allan Jepson
Attention as a Hypernetwork
Simon Schug, Seijin Kobayashi, Yassir Akram et al.
Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankers
Shijie Chen, Bernal Jimenez Gutierrez, Yu Su
Attention layers provably solve single-location regression
Pierre Marion, Raphaël Berthier, Gérard Biau et al.
Attention with Markov: A Curious Case of Single-layer Transformers
Ashok Makkuva, Marco Bondaschi, Adway Girish et al.
AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution
Fengyuan Liu, Nikhil Kandpal, Colin Raffel
Attribute-based Visual Reprogramming for Vision-Language Models
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Attributing Culture-Conditioned Generations to Pretraining Corpora
Huihan Li, Arnav Goel, Keyu He et al.
Audio Large Language Models Can Be Descriptive Speech Quality Evaluators
CHEN CHEN, Yuchen Hu, Siyin Wang et al.
AugKD: Ingenious Augmentations Empower Knowledge Distillation for Image Super-Resolution
Yun Zhang, Wei Li, Simiao Li et al.
A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations
Naveen Gupta, Medha Sawhney, Arka Daw et al.
A Unified Theory of Quantum Neural Network Loss Landscapes
Eric Anschuetz
A Unifying Framework for Representation Learning
Shaden Alshammari, John Hershey, Axel Feldmann et al.
AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark
Wenhao Chai, Enxin Song, Yilun Du et al.
AutoBencher: Towards Declarative Benchmark Construction
XIANG LI, Farzaan Kaiyom, Evan Liu et al.
AutoCGP: Closed-Loop Concept-Guided Policies from Unlabeled Demonstrations
Pei Zhou, Ruizhe Liu, Qian Luo et al.
AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models
Jan Metzen, Piyapat Saranrittichai, Chaithanya Kumar Mummadi
Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models
Fusheng Liu, Qianxiao Li