International Conference on Learning Representations
ICLR
A*
CORE rank
CORE rank (raw)
A*
Acceptance rate
31.7% (2024)
Fields of research
Machine Learning
Papers indexed
11,991
2017–2025
Papers per year
20173,704 peak2025
Most published authors
ICLR papers
11,991 records sourced from DBLP. Search titles, filter by year, sort by recency.
| Year | Title | Authors |
|---|---|---|
| 2025 | Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits. | Zihan Zhang, Xiangyang Ji, Yuan Zhou |
| 2025 | I Can Hear You: Selective Robust Training for Deepfake Audio Detection. | Zirui Zhang, Wei Hao, Aroon Sankoh, William Lin, Emanuel Mendiola-Ortiz, Junfeng Yang, Chengzhi Mao |
| 2025 | ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization. | Chen Bo Calvin Zhang, Zhang-Wei Hong, Aldo Pacchiano, Pulkit Agrawal |
| 2025 | Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents. | Hanrong Zhang, Jingyuan Huang, Kai Mei, Yifei Yao, Zhenting Wang, Chenlu Zhan, Hongwei Wang, Yongfeng Zhang |
| 2025 | Do Vision-Language Models Represent Space and How? Evaluating Spatial Frame of Reference under Ambiguities. | Zheyuan Zhang, Fengyuan Hu, Jayjun Lee, Freda Shi, Parisa Kordjamshidi, Joyce Chai, Ziqiao Ma |
| 2025 | PABBO: Preferential Amortized Black-Box Optimization. | Xinyu Zhang, Daolang Huang, Samuel Kaski, Julien Martinelli |
| 2025 | Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation. | Chenbin Zhang, Zhiqiang Hu, Chuchu Jiang, Wen Chen, Jie Xu, Shaoting Zhang |
| 2025 | Diffusion Models are Evolutionary Algorithms. | Yanbo Zhang, Benedikt Hartl, Hananel Hazan, Michael Levin |
| 2025 | Generative Verifiers: Reward Modeling as Next-Token Prediction. | Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal |
| 2025 | RFMamba: Frequency-Aware State Space Model for RF-Based Human-Centric Perception. | Rui Zhang, Ruixu Geng, Yadong Li, Ruiyuan Song, Hanqin Gong, Dongheng Zhang, Yang Hu, Yan Chen |
| 2025 | Ctrl-U: Robust Conditional Image Generation via Uncertainty-aware Reward Modeling. | Guiyu Zhang, Huan-ang Gao, Zijian Jiang, Hao Zhao, Zhedong Zheng |
| 2025 | Video In-context Learning: Autoregressive Transformers are Zero-Shot Video Imitators. | Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian |
| 2025 | MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning. | Haotian Zhang, Mingfei Gao, Zhe Gan, Philipp Dufter, Nina Wenzel, Forrest Huang, Dhruti Shah, Xianzhi Du, Bowen Zhang, Yanghao Li, Sam Dodge, Keen You, Zhen Yang, Aleksei Timofeev, Mingze Xu, Hong-You Chen, Jean-Philippe Fauconnier, Zhengfeng Lai, Haoxuan You, Zirui Wang, et al. |
| 2025 | Zero-shot forecasting of chaotic systems. | Yuanzhao Zhang, William Gilpin |
| 2025 | LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token. | Shaolei Zhang, Qingkai Fang, Zhe Yang, Yang Feng |
| 2025 | DiffPuter: Empowering Diffusion Models for Missing Data Imputation. | Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu |
| 2025 | Iterative Substructure Extraction for Molecular Relational Learning with Interactive Graph Information Bottleneck. | Shuai Zhang, Junfeng Fang, Xuqiang Li, Hongxin Xiang, Alan Xia, Ye Wei, Wenjie Du, Yang Wang |
| 2025 | Model-Free Offline Reinforcement Learning with Enhanced Robustness. | Chi Zhang, Zain Ulabedeen Farhat, George K. Atia, Yue Wang |
| 2025 | Controllable Safety Alignment: Inference-Time Adaptation to Diverse Safety Requirements. | Jingyu Zhang, Ahmed Elgohary, Ahmed Magooda, Daniel Khashabi, Benjamin Van Durme |
| 2025 | ScImage: How good are multimodal large language models at scientific text-to-image generation? | Leixin Zhang, Steffen Eger, Yinjie Cheng, Weihe Zhai, Jonas Belouadi, Fahimeh Moafian, Zhixue Zhao |
| 2025 | Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning. | Jingyuan Zhang, Yiyang Duan, Shuaicheng Niu, Yang Cao, Wei Yang Bryan Lim |
| 2025 | GEVRM: Goal-Expressive Video Generation Model For Robust Visual Manipulation. | Hongyin Zhang, Pengxiang Ding, Shangke Lyu, Ying Peng, Donglin Wang |
| 2025 | RAG-SR: Retrieval-Augmented Generation for Neural Symbolic Regression. | Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang |
| 2025 | Backtracking Improves Generation Safety. | Yiming Zhang, Jianfeng Chi, Hailey Nguyen, Kartikeya Upasani, Daniel M. Bikel, Jason E. Weston, Eric Michael Smith |
| 2025 | Adam-mini: Use Fewer Learning Rates To Gain More. | Yushun Zhang, Congliang Chen, Ziniu Li, Tian Ding, Chenwei Wu, Diederik P. Kingma, Yinyu Ye, Zhi-Quan Luo, Ruoyu Sun |
251–275 of 11,991← PreviousNext →
Comparable venues
Other A*/A conferences filed under the same field of research.
- A*ICMLInternational Conference on Machine Learning
- AAISTATSInternational Conference on Artificial Intelligence and Statistics
- A*COLTConference on Learning Theory
- APPSNParallel Problem Solving from Nature
- AECML PKDDEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008)
- A*NeurIPSAdvances in Neural Information Processing Systems (was NIPS)