3 papers
cs.CL2026
ReDAct: Uncertainty-Aware Deferral for LLM Agents
Dzianis Piatrashyn, Nikita Kotelevskii, Kirill Grishchenkov +7
Recently, LLM-based agents have become increasingly popular across many applications, including complex sequential decision-making problems. However, they inherit the tendency of L…
cs.LG2026
SuS: Strategy-aware Surprise for Intrinsic Exploration
Mark Kashirskiy, Ilya Makarov
We propose Strategy-aware Surprise (SuS), a novel intrinsic motivation framework that uses pre-post prediction mismatch as a novelty signal for exploration in reinforcement learnin…
cs.CL2025
AraToken: Optimizing Arabic Tokenization with Normalization Pipeline and Language Extension for Qwen3
Mark Kashirskiy, Artiom Lipinski, Ilya Makarov
Tokenization is a critical preprocessing step for large language models (LLMs), directly impacting training efficiency and downstream performance. General-purpose tokenizers traine…