Csordas, Robert

19 publications

NeurIPS 2025 Do Language Models Use Their Depth Efficiently? Róbert Csordás, Christopher D Manning, Christopher Potts

ICML 2025 Measuring In-Context Computation Complexity via Hidden State Prediction Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber

ICLRW 2025 Measuring In-Context Computation Complexity via Hidden State Prediction Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber

TMLR 2025 Metalearning Continual Learning Algorithms Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber

ICLR 2025 MrT5: Dynamic Token Merging for Efficient Byte-Level Language Models Julie Kallini, Shikhar Murty, Christopher D Manning, Christopher Potts, Róbert Csordás

NeurIPS 2024 MoEUT: Mixture-of-Experts Universal Transformers Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber, Christopher Potts, Christopher D. Manning

NeurIPS 2024 SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention Róbert Csordás, Piotr Piękos, Kazuki Irie, Jürgen Schmidhuber

NeurIPSW 2023 Mindstorms in Natural Language-Based Societies of Mind Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piękos, Aditya Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanić, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber

ICMLW 2023 Topological Neural Discrete Representation Learning À La Kohonen Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber

LoG 2022 A Generalist Neural Algorithmic Learner Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Joseph Dudzik, Matko Bošnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Veličković

ICML 2022 A Modern Self-Referential Weight Matrix That Learns to Modify Itself Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber

ICML 2022 The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of Attention Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber

ICLR 2022 The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber

NeurIPSW 2021 A Modern Self-Referential Weight Matrix That Learns to Modify Itself Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber

ICLR 2021 Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks Róbert Csordás, Sjoerd van Steenkiste, Jürgen Schmidhuber

NeurIPS 2021 Going Beyond Linear Transformers with Recurrent Fast Weight Programmers Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber

NeurIPSW 2021 Improving Baselines in the Wild Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber

NeurIPSW 2021 Learning Adaptive Control Flow in Transformers for Improved Systematic Generalization Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber

ICLR 2019 Improving Differentiable Neural Computers Through Memory Masking, De-Allocation, and Link Distribution Sharpness Control Robert Csordas, Juergen Schmidhuber