10 papers
World Reasoning Arena
PAN Team, Qiyue Gao, Kun Zhou +15
World models (WMs) are intended to serve as internal simulators of the real world that enable agents to understand, anticipate, and act upon complex environments. Existing WM bench…
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…
PAN: A World Model for General, Interactable, and Long-Horizon World Simulation
PAN Team, Jiannan Xiang, Yi Gu +31
A world model enables an intelligent agent to imagine, predict, and reason about how the world evolves in response to its actions, and accordingly to plan and strategize. While rec…
Auto-scaling Continuous Memory for GUI Agent
Wenyi Wu, Kun Zhou, Ruoxin Yuan +4
We study how to endow GUI agents with scalable memory that help generalize across unfamiliar interfaces and long-horizon tasks. Prior GUI agents compress past trajectories into tex…
Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation
Yuheng Zha, Kun Zhou, Yujia Wu +7
Despite their success, current training pipelines for reasoning VLMs focus on a limited range of tasks, such as mathematical and logical reasoning. As a result, these models face d…
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…