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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
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Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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other_papers
Explainable Machine Learning at Microsoft MLADS
Published:
Internal Microsoft MLADS presentation on explainable machine learning work during a Microsoft Ireland internship.
Recommended citation: Tyrolski, M. (2022). Explainable machine learning at Microsoft MLADS (Internal Microsoft MLADS Conference presentation).
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Enhancing Antigenic Peptide Discovery
Published:
Study of evaluation pitfalls in MHC-I presentation prediction, with a unified methodology and model for peptide-MHC-I binding.
Recommended citation: Giziński, S., Preibisch, G., Kucharski, P., Tyrolski, M., Rembalski, M., Grzegorczyk, P., & Gambin, A. (2024). Enhancing antigenic peptide discovery: Improved MHC-I binding prediction and methodology. Methods, 224, 1–9. https://doi.org/10.1016/j.ymeth.2024.01.016
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publications
Hierarchical Transformers Are More Efficient Language Models
Published in NAACL 2022, 2022
Hourglass adds downsampling and upsampling to Transformers for more efficient long-sequence modeling; evaluated on ImageNet32 and enwik8.
Recommended citation: Nawrot, P., Tworkowski, S., Tyrolski, M., Kaiser, Ł., Wu, Y., Szegedy, C., & Michalewski, H. (2022). Hierarchical transformers are more efficient language models. Findings of the Association for Computational Linguistics: NAACL 2022, 1559-1571.
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Adjusting Planning Horizon with Adaptive Subgoal Search
Published in ICLR 2023 (Top-5%, Oral), 2023
AdaSubS adjusts planning horizon using generated subgoals and reachability filtering; evaluated on Sokoban, Rubik’s Cube, and INT.
Recommended citation: Zawalski, M., Tyrolski, M., Czechowski, K., Odrzygóźdź, T., Stachura, D., Piękos, P., Wu, Y., Kuciński, Ł., & Miłoś, P. (2022). Fast and precise: Adjusting planning horizon with adaptive subgoal search. arXiv preprint arXiv:2206.00702.
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What Matters in Hierarchical Search for Combinatorial Reasoning Problems?
Published in ICLR 2024 (Generative Models for Decision Making), 2024
Empirical study of when hierarchical search helps in combinatorial reasoning, with evaluation guidelines for comparing methods.
Recommended citation: Zawalski, M., Góral, G., Tyrolski, M., Wiśnios, E., Budrowski, F., Cygan, M., Kuciński, Ł., & Miłoś, P. (2024). What matters in hierarchical search for combinatorial reasoning problems? arXiv preprint arXiv:2406.03361.
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OpenGVL: Benchmarking Visual Temporal Progress for Data Curation
Published in CoRL 2025 workshop, 2025
Benchmark, toolkit, and live leaderboard for evaluating VLM temporal progress estimation in robotics videos; supports automated dataset curation.
Recommended citation: Budzianowski, P., Wiśnios, E., Tyrolski, M., Góral, G., Kulakov, I., Petrenko, V., & Walas, K. (2025). OpenGVL--Benchmarking Visual Temporal Progress for Data Curation. arXiv preprint arXiv:2509.17321.
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Resolution of Recursive Data Corruption to Transform T-cell Epitope Discovery
Published in bioRxiv 2026, 2026
bioRxiv preprint on data contamination in T-cell epitope discovery; reframes MHC-I prediction as protein-centric learning to rank.
Recommended citation: Preibisch, G., Tyrolski, M., Kucharski, P., Giziński, S., Grzegorczyk, P., Moon, S., Kim, S., Zaro, B., & Gambin, A. (2026). Resolution of recursive data corruption to transform T-cell epitope discovery. bioRxiv, 2026.03.30.710191. https://doi.org/10.64898/2026.03.30.710191
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