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cs.CV2025
Counteracting Matthew Effect in Self-Improvement of LVLMs through Head-Tail Re-balancing
Xin Guo, Zhiheng Xi, Yiwen Ding +6
Self-improvement has emerged as a mainstream paradigm for advancing the reasoning capabilities of large vision-language models (LVLMs), where models explore and learn from successf…
cs.AI2025
MUA-RL: Multi-turn User-interacting Agent Reinforcement Learning for agentic tool use
Weikang Zhao, Xili Wang, Chengdi Ma +6
With the recent rapid advancement of Agentic Intelligence, agentic tool use in LLMs has become increasingly important. During multi-turn interactions between agents and users, the…