ICLR 2026, the 14th International Conference on Learning Representations, will be held in Rio de Janeiro, Brazil, from April 23 to 27, 2026.
This major global event brings together top experts to improve Learning Representations." This is a key part of AI that focuses on how computers organize and make sense of complicated information.
ICLR is famous for presenting new research that covers all areas of deep learning. it works closely with fields like natural language processing, computer vision, and reinforcement learning. The conference also shows how these tools are used in the real world, from robotics and healthcare to making large AI models work better.
At ICLR 2026, the ELLIS Institute Tübingen will share its latest research findings, showing the institute’s commitment to leading the way in machine learning.
Oral Contributions
| Saturday, Apr 25 | |
| Diffusion language models know the answer before decoding | Pengxiang Li, Yefan Zhou, Dilxat Muhtar, Lu Yin, Shilin Yan, Li Shen, Yi Liang Soroush Vosoughi, Shiwei Liu |
Poster Contributions
| Thursday, Apr 23 | |
| Adaptive Attacks on Trusted Monitors Subvert AI Control Protocols | Mikhail Terekhov, Alexander Panfilov, Daniil Dzenhaliou, Caglar Gulcehre, Maksym Andriushchenko, Ameya Prabhu, Jonas Geiping |
| Selective Rotary Position Embedding | Sajad Movahedi, Arshia Afzal, Timur Carstensen, Frank Hutter, Antonio Orvieto, Volkan Cevher |
| How does the optimizer implicitly bias the model merging loss landscape? |
Chenxiang Zhang, Alexander Theus, Damien Teney, Antonio Orvieto, Jun Pang, Sjouke Mauw |
| Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs | Xueyan Li, Guinan Su, Mrinmaya Sachan, Jonas Geiping |
|
RigidSSL: Rigidity-based Geometric Pretraining for Protein Generation |
Zhanghan (Tony) Ni, Yanjing Li, Zeju Qiu, Bernhard Schölkopf, Hongyu Guo, Weiyang Liu, Shengchao Liu |
|
Proper Velocity Neural Networks |
Ziheng Chen, Zihan Su, Bernhard Schölkopf, Nicu Sebe |
|
Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies |
Armin Kekić, Jan Schneider, Dieter Büchler, Bernhard Schölkopf, Michel Besserve |
|
Improving LLM-Based Global optimization with Search Space Partitioning |
Andrej Schwanke, Lyubomir Ivanov, David Salinas, Fabio Ferreira, Aaron Klein, Frank Hutter, Arber Zela |
| Friday, Apr 24 | |
| Capability-Based Scaling Laws for LLM Red-Teaming | Alexander Panfilov, Paul Kassianik, Maksym Andriushchenko, Jonas Geiping |
| The Curious Case of In-Training Compression of State Space Models | Makram Chahine, Philipp Nazari, Daniela Rus, T. Konstantin Rusch |
| Scaling Behavior of Discrete Diffusion Language Models |
Dimitri von Rütte, Janis Fluri, Omead Pooladzandi, Bernhard Schölkopf, Thomas Hofmann, Antonio Orvieto |
| Low-Pass Filtering Improves Behavioral Alignment of Vision Models | Max Wolff, Thomas Klein, Evgenia Rusak, Felix A. Wichmann, Wieland Brendel |
| Training Dynamics Impact Post-Training Quantization Robustness | Albert Catalan-Tatjer, Niccolò Ajroldi, Jonas Geiping |
| The Illusion of Diminishing Returns: Measuring Long Horizon Execution in LLMs | Akshit Sinha, Arvindh Arun, Shashwat Goel, Steffen Staab, Jonas Geiping |
|
MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model |
Prasanna Mayilvahanan, Ricardo Dominguez-Olmedo, Thaddäus Wiedemer, Wieland Brendel |
| Saturday, Apr 25 | |
| Neural Sum-of-Squares: Certifying the Nonnegativity of Polynomials with Transformers | Nico Pelleriti, Christoph Spiegel, Shiwei Liu, David Martinez-Rubio, Max Zimmer, Sebastian Pokutta |
| GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching | Guinan Su, Li Shen, Lu Yin, Shiwei Liu, Yanwu Yang, Jonas Geiping |
|
Pitfalls in Evaluating Language Model Forecasters |
Daniel Paleka, Shashwat Goel, Jonas Geiping, Florian Tramèr |
|
Skill learning via policy diversity yields identifiable representations for reinforcement learning |
Patrik Reizinger, Bálint Mucsányi, Siyuan Guo, Benjamin Eysenbach, Bernhard Schölkopf, Wieland Brendel |
| Strategic Dishonesty Can Undermine AI Safety Evaluations of Frontier LLMs | Alexander Panfilov, Evgenii Kortukov, Kristina Nikolić, Matthias Bethge, Sebastian Lapuschkin, Wojciech Samek, Ameya Prabhu, Maksym Andriushchenko, Jonas Geiping |
| Monitoring Decomposition Attacks in LLMs with Lightweight Sequential Monitors |
Chen Yueh-Han, Nitish Joshi, Yulin Chen, Maksym Andriushchenko, Rico Angell, He He |