collaborators

5 papers

cs.AI2026

Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches

Teddy Ferdinan, Bartłomiej Koptyra, Mikołaj Langner +42

While Reasoning Language Models (RLMs) are rapidly emerging as powerful tools for scientific research, their impact is primarily concentrated in "hard science" fields. The slow --…

cs.AI2026

PRAIB: Peer Review AI Benchmark of Behaviour of LLM-Assisted Reviewing

Krzysztof Żurawicki, Julia Farganus, Arkadiusz Gaweł +2

The growing number of submitted papers has motivated the exploration of Large Language Models (LLMs) as a means to support and augment the peer review process, particularly in term…

cs.AI2026

Geometry of Knowledge Allows Extending Diversity Boundaries of Large Language Models

Mateusz Bystroński, Doheon Han, Nitesh V. Chawla +1

Starting from the hypothesis that knowledge in semantic space is organized along structured manifolds, we argue that this geometric structure renders the space explorable. By trave…

cs.CL2025

LatentPrompt: Optimizing Promts in Latent Space

Mateusz Bystroński, Grzegorz Piotrowski, Nitesh V. Chawla +1

Recent advances have shown that optimizing prompts for Large Language Models (LLMs) can significantly improve task performance, yet many optimization techniques rely on heuristics…

cs.CL2025

SMOTExT: SMOTE meets Large Language Models

Mateusz Bystroński, Mikołaj Hołysz, Grzegorz Piotrowski +2

Data scarcity and class imbalance are persistent challenges in training robust NLP models, especially in specialized domains or low-resource settings. We propose a novel technique,…