3 papers
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.AI2025
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
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,…