SophiaVL-R1: Reinforcing MLLMs Reasoning with Thinking Reward
Kaixuan Fan · Kaituo Feng · Haoming Lyu · Dongzhan Zhou · Xiangyu Yue
首次获取该候选人的完整档案及 StartLux 评估共 20 积分;每位用户单独解锁,之后查看免费。主动刷新 20 积分。
实时查找电子邮箱,费用不超过20积分;未找到邮箱不扣费。
Kaixuan Fan · Kaituo Feng · Haoming Lyu · Dongzhan Zhou · Xiangyu Yue
Kaituo Feng · Manyuan Zhang · Hongyu Li · Kaixuan Fan · Shuang Chen · Yilei Jiang · Dian Zheng · Peiwen Sun · Yiyuan Zhang · Haoze Sun · Yan Feng · Peng Pei · Xunliang Cai · Xiangyu Yue
Kaixiong Gong · Kaituo Feng · Bohao Li · Yibing Wang · Mofan Cheng · Shijia Yang · Jiaming Han · Benyou Wang · Yutong Bai · Zhuoran Yang · Xiangyu Yue
Recent multimodal large language models (MLLMs), such as GPT-4o, Gemini 1.5/2.5 Pro, and Reka Core, have advanced audio-visual reasoning capabilities, achieving strong performance in tasks like cross-modal understanding and generation. However, our DeafTest uncovers unanticipated failures: most o...
Kaixuan Fan · Kaituo Feng · Manyuan Zhang · Tianshuo Peng · Zhixun Li · Yilei Jiang · Shuang Chen · Xiangyu Yue
Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use. However, most methods still relies on sparse outcome-based reward for training. Such feedback fails to differentiate intermediate reasoning quality, leading to su...
Chaoyang Wang · Kaituo Feng · Dongyang Chen · Zhongyu Wang · Zhixun Li · Sicheng Gao · Meng Meng · Xu Zhou · Manyuan Zhang · Yuzhang Shang · Xiangyu Yue
Recent advances have shown that multimodal large language models (MLLMs) benefit from multimodal interleaved chain-of-thought (CoT) with vision tool interactions. However, existing open-source models often exhibit blind tool-use reasoning patterns, invoking vision tools even when they are unneces...