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cs.LG2026
Recursive Offline Distillation via Entropy Gain Sampling and Answer Mixing
Andrey Goncharov, Daniil Vyazhev, Simon Epanov +1
Distillation of reasoning chains from Large Language Models (LLMs) into their smaller siblings is a standard training approach. Frequently, researchers do not have full access to a…
cs.LG2026
Enhancing the Reliability of Medical AI through Expert-guided Uncertainty Modeling
Aleksei Khalin, Ekaterina Zaychenkova, Aleksandr Yugay +4
Artificial intelligence (AI) systems accelerate medical workflows and improve diagnostic accuracy in healthcare, serving as second-opinion systems. However, the unpredictability of…
cs.LG2025
Complexity-aware fine-tuning
Andrey Goncharov, Daniil Vyazhev, Petr Sychev +2
General-purpose Large Language Models (LLMs) are frequently fine-tuned through supervised fine-tuning (SFT) to enhance performance in specific domains. Better results can be achiev…