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cs.AI2026
PREFER: From Player Experience to Personalized Game Refinement
Qi Chai, Zhang Zheng, Lu Yang +2
Understanding how large language models (LLMs) evaluate gameplay experience is important for using their feedback to guide game design. However, overall ratings alone provide limit…
cs.AI2026
Adversarial Closed-Loop Curriculum for Evolving Role-Playing Agents
Zheng Zhang, Liu Liu, Qi Chai +4
Role-playing agents based on large language models have been widely applied in areas such as personalized assistance and social simulation. Recent RL methods typically train on a f…
cs.AI2026
EvolveNav: Proactive Preflection and Self-Evolving Memory for Zero-Shot Object Goal Navigation
Qi Chai, Wenhao Shen, Nanjie Yao +5
Zero-Shot Object-Goal Navigation (ZS-OGN) requires embodied agents to explore and locate target objects without any prior training. To this end, recent methods leverage foundation…