Hierarchical Reinforcement Learning with Parameters. - Maciej Klimek; Henryk Michalewski; Piotr Milos (CoRL, 2017)

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. - Lukasz Kidzinski; Sharada Prasanna Mohanty; Carmichael F. Ong; Zhewei Huang; Shuchang Zhou 001; Anton Pechenko; Adam Stelmaszczyk; Piotr Jarosik; Mikhail Pavlov; Sergey Kolesnikov; Sergey M. Plis; Zhibo Chen 001; et al. (CoRR, 2018)

Expert-augmented actor-critic for ViZDoom and Montezumas Revenge. - Michal Garmulewicz; Henryk Michalewski; Piotr Milos (CoRR, 2018)

Model-Based Reinforcement Learning for Atari. - Lukasz Kaiser; Mohammad Babaeizadeh; Piotr Milos; Blazej Osinski; Roy H. Campbell; Konrad Czechowski; Dumitru Erhan; Chelsea Finn; Piotr Kozakowski; Sergey Levine; Ryan Sepassi; George Tucker; et al. (CoRR, 2019)

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)

Model Based Reinforcement Learning for Atari. - Lukasz Kaiser; Mohammad Babaeizadeh; Piotr Milos; Blazej Osinski; Roy H. Campbell; Konrad Czechowski; Dumitru Erhan; Chelsea Finn; Piotr Kozakowski; Sergey Levine; Afroz Mohiuddin; Ryan Sepassi; et al. (ICLR, 2020)

Simulation-Based Reinforcement Learning for Real-World Autonomous Driving. - Blazej Osinski; Adam Jakubowski; Pawel Ziecina; Piotr Milos; Christopher Galias; Silviu Homoceanu; Henryk Michalewski (ICRA, 2020)

CARLA Real Traffic Scenarios - novel training ground and benchmark for autonomous driving. - Blazej Osinski; Piotr Milos; Adam Jakubowski; Pawel Ziecina; Michal Martyniak; Christopher Galias; Antonia Breuer; Silviu Homoceanu; Henryk Michalewski (CoRR, 2020)

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)

Robust and Efficient Planning using Adaptive Entropy Tree Search. - Piotr Kozakowski; Mikolaj Pacek; Piotr Milos (CoRR, 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)

Off-Policy Correction For Multi-Agent Reinforcement Learning. - Michal Zawalski; Blazej Osinski; Henryk Michalewski; Piotr Milos (AAMAS, 2022)

Planning and Learning using Adaptive Entropy Tree Search. - Piotr Kozakowski; Mikolaj Pacek; Piotr Milos (IJCNN, 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 (NeurIPS, 2022)

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

The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning. - Samuel Kessler; Piotr Milos; Jack Parker-Holder; Stephen J. Roberts (CoRR, 2022)

The Effectiveness of World Models for Continual Reinforcement Learning. - Samuel Kessler; Mateusz Ostaszewski; Michal Pawel Bortkiewicz; Mateusz Zarski; Maciej Wolczyk; Jack Parker-Holder; Stephen J. Roberts; Piotr Milos (CoLLAs, 2023)

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)

The Tunnel Effect: Building Data Representations in Deep Neural Networks. - Wojciech Masarczyk; Mateusz Ostaszewski; Ehsan Imani; Razvan Pascanu; Piotr Milos; Tomasz Trzcinski (NeurIPS, 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)

Focused Transformer: Contrastive Training for Context Scaling. - Szymon Tworkowski; Konrad Staniszewski; Mikolaj Pacek; Yuhuai Wu; Henryk Michalewski; 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)

Exploring Continual Learning of Diffusion Models. - Michal Zajac 005; Kamil Deja; Anna Kuzina; Jakub M. Tomczak; Tomasz Trzcinski; Florian Shkurti; Piotr Milos (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)

Analysing The Impact of Sequence Composition on Language Model Pre-Training. - Yu Zhao 043; Yuanbin Qu; Konrad Staniszewski; Szymon Tworkowski; Wei Liu; Piotr Milos; Yuxiang Wu; Pasquale Minervini (ACL (1), 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 (ICLR, 2024)

Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning. - Michal Nauman; Michal Bortkiewicz; Piotr Milos; Tomasz Trzcinski; Mateusz Ostaszewski; Marek Cygan (ICML, 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)

Repurposing Language Models into Embedding Models: Finding the Compute-Optimal Recipe. - Albert Q. Jiang; Alicja Ziarko; Bartosz Piotrowski; Wenda Li; Mateja Jamnik; Piotr Milos (NeurIPS, 2024)

Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control. - Michal Nauman; Mateusz Ostaszewski; Krzysztof Jankowski; Piotr Milos; Marek Cygan (NeurIPS, 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)

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)

Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient. - Jan Ludziejewski; Maciej Pióro; Jakub Krajewski; Maciej Stefaniak; Michal Krutul; Jan Malasnicki; Marek Cygan; Piotr Sankowski; Kamil Adamczewski; Piotr Milos; Sebastian Jaszczur (CoRR, 2025)

Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery. - Mateusz Olko; Mateusz Gajewski; Joanna Wojciechowska; Mikolaj Morzy; Piotr Sankowski; Piotr Milos (CoRR, 2025)

Lightweight Latent Verifiers for Efficient Meta-Generation Strategies. - Bartosz Piotrowski; Witold Drzewakowski; Konrad Staniszewski; Piotr Milos (CoRR, 2025)

Beyond Recognition: Evaluating Visual Perspective Taking in Vision Language Models. - Gracjan Góral; Alicja Ziarko; Piotr Milos; Michal Nauman; Maciej Wolczyk; Michal Kosinski (CoRR, 2025)

Contrastive Representations for Temporal Reasoning. - Alicja Ziarko; Michal Bortkiewicz; Michal Zawalski; Benjamin Eysenbach; Piotr Milos (CoRR, 2025)