3 papers
cs.LG2024
What Matters in Hierarchical Search for Combinatorial Reasoning Problems?
Michał Zawalski, Gracjan Góral, Michał Tyrolski +5
Efficiently tackling combinatorial reasoning problems, particularly the notorious NP-hard tasks, remains a significant challenge for AI research. Recent efforts have sought to enha…
cs.AI2022
Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
Michał Zawalski, Michał Tyrolski, Konrad Czechowski +6
Complex reasoning problems contain states that vary in the computational cost required to determine a good action plan. Taking advantage of this property, we propose Adaptive Subgo…
cs.LG2021
Hierarchical Transformers Are More Efficient Language Models
Piotr Nawrot, Szymon Tworkowski, Michał Tyrolski +4
Transformer models yield impressive results on many NLP and sequence modeling tasks. Remarkably, Transformers can handle long sequences which allows them to produce long coherent o…