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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.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…