collaborators

5 papers

cs.AI2026

MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs

Kevin Wang, Anna Thöni, Benjamin Kempinski +50

Large language models (LLMs) are increasingly deployed as interactive agents, yet their capacity for social and strategic reasoning over extended interaction remains poorly underst…

cs.AI2026

MindGames Arena Generalization Track: In2AI Solution with Delayed Per-Step Reward Attribution

Aliaksei Korshuk, Alexander Buyantuev, Ilya Makarov

Training language model agents for multi-agent strategic interaction presents a core difficulty: the quality of any action may depend on future events that never materialize, on mo…

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…