127 citations · 128 across the 9 of their papers we have counts for
4 papers · 1 filter
DeepEyesV2: Toward Agentic Multimodal Model
Jack Hong, Chenxiao Zhao, ChengLin Zhu +3
Agentic multimodal models should not only comprehend text and images, but also actively invoke external tools, such as code execution environments and web search, and integrate the…
Decoupling Understanding from Reasoning via Problem Space Mapping for Small-Scale Model Reasoning
Li Wang, Changhao Zhang, Zengqi Xiu +4
Despite recent advances in the reasoning capabilities of Large Language Models (LLMs), improving the reasoning ability of Small Language Models (SLMs, e.g., up to 1.5B parameters)…
Think When You Need: Self-Adaptive Chain-of-Thought Learning
Junjie Yang, Ke Lin, Xing Yu
Chain of Thought (CoT) reasoning enhances language models' performance but often leads to inefficient "overthinking" on simple problems. We identify that existing approaches direct…
DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning
Ziwei Zheng, Michael Yang, Jack Hong +5
Large Vision-Language Models excel at multimodal understanding but struggle to deeply integrate visual information into their predominantly text-based reasoning processes, a key ch…