4 papers
Learning Modal-Mixed Chain-of-Thought Reasoning with Latent Embeddings
Yifei Shao, Kun Zhou, Ziming Xu +5
We study how to extend chain-of-thought (CoT) beyond language to better handle multimodal reasoning. While CoT helps LLMs and VLMs articulate intermediate steps, its text-only form…
Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models
Zekai Zhao, Qi Liu, Kun Zhou +4
Despite the remarkable reasoning performance, eliciting the long chain-of-thought (CoT) ability in large language models (LLMs) typically requires costly reinforcement learning or…
Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models
Yanbin Yin, Kun Zhou, Zhen Wang +11
The recent explosion of large language models (LLMs), each with its own general or specialized strengths, makes scalable, reliable benchmarking more urgent than ever. Standard prac…
Towards General Continuous Memory for Vision-Language Models
Wenyi Wu, Zixuan Song, Kun Zhou +3
Language models (LMs) and their extension, vision-language models (VLMs), have achieved remarkable performance across various tasks. However, they still struggle with complex reaso…