Szymon Tworkowski

According to our database, Szymon Tworkowski authored at least 8 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Magnushammer: A Transformer-Based Approach to Premise Selection.

Maciej Mikula, Szymon Tworkowski, Szymon Antoniak, Bartosz Piotrowski, Albert Q. Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Analysing The Impact of Sequence Composition on Language Model Pre-Training.

Yu Zhao, Yuanbin Qu, Konrad Staniszewski, Szymon Tworkowski, Wei Liu, Piotr Milos, Yuxiang Wu, Pasquale Minervini

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Structured Packing in LLM Training Improves Long Context Utilization.

Konrad Staniszewski, Szymon Tworkowski, Sebastian Jaszczur, Henryk Michalewski, Lukasz Kucinski, Piotr Milos

CoRR, 2023

Explaining Competitive-Level Programming Solutions using LLMs.

Jierui Li, Szymon Tworkowski, Yingying Wu, Raymond J. Mooney

CoRR, 2023

Magnushammer: A Transformer-based Approach to Premise Selection.

Maciej Mikula, Szymon Antoniak, Szymon Tworkowski, Albert Qiaochu Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu

CoRR, 2023

Focused Transformer: Contrastive Training for Context Scaling.

Szymon Tworkowski, Konrad Staniszewski, Mikolaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Milos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers.

Albert Qiaochu Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygózdz, Piotr Milos, Yuhuai Wu, Mateja Jamnik

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Hierarchical Transformers Are More Efficient Language Models.

Piotr Nawrot, Szymon Tworkowski, Michal Tyrolski, Lukasz Kaiser, Yuhuai Wu, Christian Szegedy, Henryk Michalewski

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022