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 | MTU-Bench: A Multi-granularity Tool-Use Benchmark for Large Language Models. | Pei Wang, Yanan Wu, Noah Wang, Jiaheng Liu, Xiaoshuai Song, Z. Y. Peng, Ken Deng, Chenchen Zhang, Jiakai Wang, Junran Peng, Ge Zhang, Hangyu Guo, Zhaoxiang Zhang, Wenbo Su, Bo Zheng |
| 2025 | HeadMap: Locating and Enhancing Knowledge Circuits in LLMs. | Xuehao Wang, Liyuan Wang, Binghuai Lin, Yu Zhang |
| 2025 | LLM Unlearning via Loss Adjustment with Only Forget Data. | Yaxuan Wang, Jiaheng Wei, Chris Yuhao Liu, Jinlong Pang, Quan Liu, Ankit Shah, Yujia Bao, Yang Liu, Wei Wei |
| 2025 | DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agent. | Taiyi Wang, Zhihao Wu, Jianheng Liu, Jianye Hao, Jun Wang, Kun Shao |
| 2025 | GLOMA: Global Video Text Spotting with Morphological Association. | Han Wang, Yanjie Wang, Yang Li, Can Huang |
| 2025 | Mixture-of-Agents Enhances Large Language Model Capabilities. | Junlin Wang, Jue Wang, Ben Athiwaratkun, Ce Zhang, James Zou |
| 2025 | Agree to Disagree: Demystifying Homogeneous Deep Ensembles through Distributional Equivalence. | Yipei Wang, Xiaoqian Wang |
| 2025 | IgGM: A Generative Model for Functional Antibody and Nanobody Design. | Rubo Wang, Fandi Wu, Xingyu Gao, Jiaxiang Wu, Peilin Zhao, Jianhua Yao |
| 2025 | HiLo: A Learning Framework for Generalized Category Discovery Robust to Domain Shifts. | Hongjun Wang, Sagar Vaze, Kai Han |
| 2025 | Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design. | Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Aviv Regev, Hanchen Wang, Tommaso Biancalani |
| 2025 | Revealing and Mitigating Over-Attention in Knowledge Editing. | Pinzheng Wang, Zecheng Tang, Keyan Zhou, Juntao Li, Qiaoming Zhu, Min Zhang |
| 2025 | Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images. | Yubo Wang, Jianting Tang, Chaohu Liu, Linli Xu |
| 2025 | Diffusion Feedback Helps CLIP See Better. | Wenxuan Wang, Quan Sun, Fan Zhang, Yepeng Tang, Jing Liu, Xinlong Wang |
| 2025 | Large Language Models are Interpretable Learners. | Ruochen Wang, Si Si, Felix X. Yu, Dorothea Wiesmann Rothuizen, Cho-Jui Hsieh, Inderjit S. Dhillon |
| 2025 | Forget the Data and Fine-Tuning! Just Fold the Network to Compress. | Dong Wang, Haris Sikic, Lothar Thiele, Olga Saukh |
| 2025 | CViT: Continuous Vision Transformer for Operator Learning. | Sifan Wang, Jacob H. Seidman, Shyam Sankaran, Hanwen Wang, George J. Pappas, Paris Perdikaris |
| 2025 | Efficient Evolutionary Search Over Chemical Space with Large Language Models. | Haorui Wang, Marta Skreta, Cher Tian Ser, Wenhao Gao, Lingkai Kong, Felix Strieth-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Aln Aspuru-Guzik, Kirill Neklyudov, Chao Zhang |
| 2025 | LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior. | Hanyu Wang, Saksham Suri, Yixuan Ren, Hao Chen, Abhinav Shrivastava |
| 2025 | DynFrs: An Efficient Framework for Machine Unlearning in Random Forest. | Shurong Wang, Zhuoyang Shen, Xinbao Qiao, Tongning Zhang, Meng Zhang |
| 2025 | Diffusion-NPO: Negative Preference Optimization for Better Preference Aligned Generation of Diffusion Models. | Fu-Yun Wang, Yunhao Shui, Jingtan Piao, Keqiang Sun, Hongsheng Li |
| 2025 | On the expressiveness and spectral bias of KANs. | Yixuan Wang, Jonathan W. Siegel, Ziming Liu, Thomas Y. Hou |
| 2025 | Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets. | Yuxin Wang, Maresa Schrder, Dennis Frauen, Jonas Schweisthal, Konstantin Hess, Stefan Feuerriegel |
| 2025 | Capturing the Temporal Dependence of Training Data Influence. | Jiachen T. Wang, Dawn Song, James Zou, Prateek Mittal, Ruoxi Jia |
| 2025 | GridMix: Exploring Spatial Modulation for Neural Fields in PDE Modeling. | Honghui Wang, Shiji Song, Gao Huang |
| 2025 | High-Dynamic Radar Sequence Prediction for Weather Nowcasting Using Spatiotemporal Coherent Gaussian Representation. | Ziye Wang, Yiran Qin, Lin Zeng, Ruimao Zhang |
776–800 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)