Developmentally motivated emergence of compositional communication via template transfer. - Tomasz Korbak; Julian Zubek; Lukasz Kucinski; Piotr Milos; Joanna Raczaszek-Leonardi (CoRR, 2019)

Uncertainty-sensitive Learning and Planning with Ensembles. - Piotr Milos; Lukasz Kucinski; Konrad Czechowski; Piotr Kozakowski; Maciej Klimek (CoRR, 2019)

Structure and Randomness in Planning and Reinforcement Learning. - Konrad Czechowski; Piotr Januszewski; Piotr Kozakowski; Lukasz Kucinski; Piotr Milos (IJCNN, 2021)

Trust, but Verify: Alleviating Pessimistic Errors in Model-Based Exploration. - Konrad Czechowski; Tomasz Odrzygózdz; Michal Izworski; Marek Zbysinski; Lukasz Kucinski; Piotr Milos (IJCNN, 2021)

Subgoal Search For Complex Reasoning Tasks. - Konrad Czechowski; Tomasz Odrzygózdz; Marek Zbysinski; Michal Zawalski; Krzysztof Olejnik; Yuhuai Wu; Lukasz Kucinski; Piotr Milos (NeurIPS, 2021)

Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication. - Lukasz Kucinski; Tomasz Korbak; Pawel Kolodziej; Piotr Milos (NeurIPS, 2021)

Continual World: A Robotic Benchmark For Continual Reinforcement Learning. - Maciej Wolczyk; Michal Zajac 005; Razvan Pascanu; Lukasz Kucinski; Piotr Milos (NeurIPS, 2021)

Continuous Control With Ensemble Deep Deterministic Policy Gradients. - Piotr Januszewski; Mateusz Olko; Michal Królikowski; Jakub Swiatkowski; Marcin Andrychowicz; Lukasz Kucinski; Piotr Milos (CoRR, 2021)

Disentangling Transfer in Continual Reinforcement Learning. - Maciej Wolczyk; Michal Zajac 005; Razvan Pascanu; Lukasz Kucinski; Piotr Milos (NeurIPS, 2022)

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search. - Michal Zawalski; Michal Tyrolski; Konrad Czechowski; Tomasz Odrzygózdz; Damian Stachura; Piotr Piekos; Yuhuai Wu; Lukasz Kucinski; Piotr Milos (ICLR, 2023)

Trust Your 𝛁: Gradient-based Intervention Targeting for Causal Discovery. - Mateusz Olko; Michal Zajac 005; Aleksandra Nowak 001; Nino Scherrer; Yashas Annadani; Stefan Bauer; Lukasz Kucinski; Piotr Milos (NeurIPS, 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)

Structured Packing in LLM Training Improves Long Context Utilization. - Konrad Staniszewski; Szymon Tworkowski; Sebastian Jaszczur; Henryk Michalewski; Lukasz Kucinski; Piotr Milos (CoRR, 2023)

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 (ICLR, 2024)

Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem. - Maciej Wolczyk; Bartlomiej Cupial; Mateusz Ostaszewski; Michal Bortkiewicz; Michal Zajac 005; Razvan Pascanu; Lukasz Kucinski; Piotr Milos (ICML, 2024)

GUIDE: Guidance-based Incremental Learning with Diffusion Models. - Bartosz Cywinski; Kamil Deja; Tomasz Trzcinski; Bartlomiej Twardowski; Lukasz Kucinski (CoRR, 2024)

tsGT: Stochastic Time Series Modeling With Transformer. - Lukasz Kucinski; Witold Drzewakowski; Mateusz Olko; Piotr Kozakowski; Lukasz Maziarka; Marta Emilia Nowakowska; Lukasz Kaiser; Piotr Milos (CoRR, 2024)

What Matters in Hierarchical Search for Combinatorial Reasoning Problems? - Michal Zawalski; Gracjan Góral; Michal Tyrolski; Emilia Wisnios; Franciszek Budrowski; Lukasz Kucinski; Piotr Milos (CoRR, 2024)

RoboMorph: Evolving Robot Morphology using Large Language Models. - Kevin Qiu; Krzysztof Ciebiera; Pawel Fijalkowski; Marek Cygan; Lukasz Kucinski (CoRR, 2024)

Accelerating Goal-Conditioned RL Algorithms and Research. - Michal Bortkiewicz; Wladek Palucki; Vivek Myers; Tadeusz Dziarmaga; Tomasz Arczewski; Lukasz Kucinski; Benjamin Eysenbach (CoRR, 2024)

There and Back Again: On the relation between noises, images, and their inversions in diffusion models. - Lukasz Staniszewski; Lukasz Kucinski; Kamil Deja (CoRR, 2024)

RapidDock: Unlocking Proteome-scale Molecular Docking. - Rafal Powalski; Bazyli Klockiewicz; Maciej Jaskowski; Bartosz Topolski; Pawel Dabrowski-Tumanski; Maciej Wisniewski; Lukasz Kucinski; Piotr Milos; Dariusz Plewczynski (CoRR, 2024)

Structured Packing in LLM Training Improves Long Context Utilization. - Konrad Staniszewski; Szymon Tworkowski; Sebastian Jaszczur; Yu Zhao 043; Henryk Michalewski; Lukasz Kucinski; Piotr Milos (AAAI, 2025)

Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research. - Michal Bortkiewicz; Wladyslaw Palucki; Vivek Myers; Tadeusz Dziarmaga; Tomasz Arczewski; Lukasz Kucinski; Benjamin Eysenbach (ICLR, 2025)

BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games. - Davide Paglieri; Bartlomiej Cupial; Samuel Coward; Ulyana Piterbarg; Maciej Wolczyk; Akbir Khan; Eduardo Pignatelli; Lukasz Kucinski; Lerrel Pinto; Rob Fergus; Jakob Nicolaus Foerster; Jack Parker-Holder; et al. (ICLR, 2025)