5 papers
Hybrid Open-Ended Tri-Evolution Makes Better Deep Researcher
Hongming Piao, Chi Liu, Mengzhuo Chen +5
Deep research and agent evolution serve as de-facto tasks for AI agents in real-world applications toward artificial general intelligence. The former enables autonomous retrieval a…
Towards Solving the Gilbert-Pollak Conjecture via Large Language Models
Yisi Ke, Tianyu Huang, Yankai Shu +3
The Gilbert-Pollak Conjecture \citep{gilbert1968steiner}, also known as the Steiner Ratio Conjecture, states that for any finite point set in the Euclidean plane, the Steiner minim…
Investigating Advanced Reasoning of Large Language Models via Black-Box Environment Interaction
Congchi Yin, Tianyi Wu, Yankai Shu +5
Existing tasks fall short in evaluating reasoning ability of Large Language Models (LLMs) in an interactive, unknown environment. This deficiency leads to the isolated assessment o…
Fleming-VL: Towards Universal Medical Visual Reasoning with Multimodal LLMs
Yan Shu, Chi Liu, Robin Chen +2
Multimodal Large Language Models (MLLMs) have demonstrated remarkable effectiveness in various general-domain scenarios, such as visual question answering and image captioning. Rec…
Fleming-R1: Toward Expert-Level Medical Reasoning via Reinforcement Learning
Chi Liu, Derek Li, Yan Shu +4
While large language models show promise in medical applications, achieving expert-level clinical reasoning remains challenging due to the need for both accurate answers and transp…