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 | Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences. | Nikolaos Dimitriadis, Pascal Frossard, Franois Fleuret |
| 2025 | ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs. | Hao Di, Tong He, Haishan Ye, Yinghui Huang, Xiangyu Chang, Guang Dai, Ivor W. Tsang |
| 2025 | Boltzmann priors for Implicit Transfer Operators. | Juan Viguera Diez, Mathias Jacob Schreiner, Ola Engkvist, Simon Olsson |
| 2025 | On the Transfer of Object-Centric Representation Learning. | Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael Curtis Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer |
| 2025 | Efficient Imitation under Misspecification. | Nicolas A. Espinosa Dice, Sanjiban Choudhury, Wen Sun, Gokul Swamy |
| 2025 | TASAR: Transfer-based Attack on Skeletal Action Recognition. | Yunfeng Diao, Baiqi Wu, Ruixuan Zhang, Ajian Liu, Xiaoshuai Hao, Xingxing Wei, Meng Wang, He Wang |
| 2025 | A Meta-Learning Approach to Bayesian Causal Discovery. | Anish Dhir, Matthew Ashman, James Requeima, Mark van der Wilk |
| 2025 | L3Ms - Lagrange Large Language Models. | Guneet S. Dhillon, Xingjian Shi, Yee Whye Teh, Alex Smola |
| 2025 | NutriBench: A Dataset for Evaluating Large Language Models in Nutrition Estimation from Meal Descriptions. | Mehak Preet Dhaliwal, Andong Hua, Laya Pullela, Ryan Burke, Yao Qin |
| 2025 | Learning General-purpose Biomedical Volume Representations using Randomized Synthesis. | Neel Dey, Benjamin Billot, Hallee E. Wong, Clinton J. Wang, Mengwei Ren, Ellen Grant, Adrian V. Dalca, Polina Golland |
| 2025 | ADIFF: Explaining audio difference using natural language. | Soham Deshmukh, Shuo Han, Rita Singh, Bhiksha Raj |
| 2025 | Beyond Autoregression: Fast LLMs via Self-Distillation Through Time. | Justin Deschenaux, Caglar Gulcehre |
| 2025 | eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels. | Alexander C. DeRieux, Walid Saad |
| 2025 | DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models. | Wenlong Deng, Yize Zhao, Vala Vakilian, Minghui Chen, Xiaoxiao Li, Christos Thrampoulidis |
| 2025 | Everything is Editable: Extend Knowledge Editing to Unstructured Data in Large Language Models. | Jingcheng Deng, Zihao Wei, Liang Pang, Hanxing Ding, Huawei Shen, Xueqi Cheng |
| 2025 | Neuron based Personality Trait Induction in Large Language Models. | Jia Deng, Tianyi Tang, Yanbin Yin, Wenhao Yang, Xin Zhao, Ji-Rong Wen |
| 2025 | Autoregressive Video Generation without Vector Quantization. | Haoge Deng, Ting Pan, Haiwen Diao, Zhengxiong Luo, Yufeng Cui, Huchuan Lu, Shiguang Shan, Yonggang Qi, Xinlong Wang |
| 2025 | Infinite-Resolution Integral Noise Warping for Diffusion Models. | Yitong Deng, Winnie Lin, Lingxiao Li, Dmitriy Smirnov, Ryan D. Burgert, Ning Yu, Vincent Dedun, Mohammad H. Taghavi |
| 2025 | Gaussian-Based Instance-Adaptive Intensity Modeling for Point-Supervised Facial Expression Spotting. | Yicheng Deng, Hideaki Hayashi, Hajime Nagahara |
| 2025 | On the Price of Differential Privacy for Hierarchical Clustering. | Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou |
| 2025 | Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning. | Berken Utku Demirel, Christian Holz |
| 2025 | Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure. | Samet Demir, Zafer Dogan |
| 2025 | Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models. | Can Demircan, Tankred Saanum, Akshay Kumar Jagadish, Marcel Binz, Eric Schulz |
| 2025 | Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization. | Yury Demidovich, Petr Ostroukhov, Grigory Malinovsky, Samuel Horvth, Martin Takc, Peter Richtrik, Eduard Gorbunov |
| 2025 | MAST: model-agnostic sparsified training. | Yury Demidovich, Grigory Malinovsky, Egor Shulgin, Peter Richtrik |
2,926–2,950 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)