| Thor: Wielding hammers to integrate language models and automated theorem provers AQ Jiang, W Li, S Tworkowski, K Czechowski, T Odrzygóźdź, P Miłoś, ... Advances in Neural Information Processing Systems 35, 8360-8373, 2022 | 91 | 2022 |
| Subgoal search for complex reasoning tasks K Czechowski, T Odrzygóźdź, M Zbysiński, M Zawalski, K Olejnik, Y Wu, ... Advances in Neural Information Processing Systems 34, 624-638, 2021 | 29 | 2021 |
| Scaling laws for fine-grained mixture of experts J Krajewski, J Ludziejewski, K Adamczewski, M Pióro, M Krutul, ... arXiv preprint arXiv:2402.07871, 2024 | 27 | 2024 |
| A half-page derivation of the Thomas precession A Dragan, T Odrzygóźdź American Journal of Physics 81 (8), 631-632, 2013 | 23 | 2013 |
| The square model for random groups T Odrzygóźdź arXiv preprint arXiv:1405.2773, 2014 | 12 | 2014 |
| Fast and precise: Adjusting planning horizon with adaptive subgoal search M Zawalski, M Tyrolski, K Czechowski, T Odrzygóźdź, D Stachura, ... arXiv preprint arXiv:2206.00702, 2022 | 9 | 2022 |
| Scaling Laws for Fine-Grained Mixture of Experts J Ludziejewski, J Krajewski, K Adamczewski, M Pióro, M Krutul, ... Forty-first International Conference on Machine Learning, 0 | 9 | |
| Cubulating random groups in the square model T Odrzygóźdź Israel Journal of Mathematics 227 (2), 623-661, 2018 | 8 | 2018 |
| Bent walls for random groups in the square and hexagonal model T Odrzygóźdź arXiv preprint arXiv:1906.05417, 2019 | 4 | 2019 |
| Mixture of Tokens: Continuous MoE through Cross-Example Aggregation S Antoniak, M Krutul, M Pióro, J Krajewski, J Ludziejewski, K Ciebiera, ... Advances in Neural Information Processing Systems 37, 103873-103896, 2025 | 2 | 2025 |
| Mixture of Tokens: Efficient LLMs through Cross-Example Aggregation S Antoniak, S Jaszczur, M Krutul, M Pióro, J Krajewski, J Ludziejewski, ... arXiv preprint arXiv:2310.15961, 2023 | 2 | 2023 |
| Nonplanar isoperimetric inequality for random groups T Odrzygóźdź arXiv preprint arXiv:2104.13903, 2021 | 2 | 2021 |
| Trust, but Verify: Alleviating Pessimistic Errors in Model-Based Exploration K Czechowski, T Odrzygóźdź, M Izworski, M Zbysiński, Ł Kuciński, P Miłoś 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | | 2021 |
| Trust, but Verify: Alleviating Pessimistic Errors in Model-Based Exploration Ł Kuciński, M Izworski, K Czechowski, M Zbysiński, P Miłoś, T Odrzygóźdź | | 2021 |
| Trust, but verify: model-based exploration in sparse reward environments K Czechowski, T Odrzygóźdź, M Izworski, M Zbysiński, Ł Kuciński, P Miłoś | | |
Piotr MiłośUniversity of Warsaw, Polish Academy of Sciences and IDEAS NCBR在 mimuw.edu.pl 的电子邮件经过验证