1 citations · 1 across the 5 of their papers we have counts for
6 papers
RoboHarness: A Simple Harness Outperforms VLA and World Action Models
Bince Qu, Wei Chen, Bo Zhang
The rise of large language models (LLMs) has opened a path toward generalist embodied AI, raising the question of how LLMs can act in the physical world. One straightforward approa…
LiteResearcher: A Scalable Agentic RL Training Framework for Deep Research Agent
Bince Qu, Wanli Li, Bo Pan +5
Reinforcement Learning (RL) has emerged as a powerful training paradigm for LLM-based agents. However, scaling agentic RL for deep research remains constrained by two coupled chall…
VIS-Shepherd: Constructing Critic for LLM-based Data Visualization Generation
Bo Pan, Yixiao Fu, Ke Wang +15
Data visualization generation using Large Language Models (LLMs) has shown promising results but often produces suboptimal visualizations that require human intervention for improv…
IntuiTF: MLLM-Guided Transfer Function Optimization for Direct Volume Rendering
Yiyao Wang, Bo Pan, Ke Wang +8
Direct volume rendering (DVR) is a fundamental technique for visualizing volumetric data, where transfer functions (TFs) play a crucial role in extracting meaningful structures. Ho…
Multimodal DeepResearcher: Generating Text-Chart Interleaved Reports From Scratch with Agentic Framework
Zhaorui Yang, Bo Pan, Han Wang +8
Visualizations play a crucial part in effective communication of concepts and information. Recent advances in reasoning and retrieval augmented generation have enabled Large Langua…
R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization
Yi Yang, Xiaoxuan He, Hongkun Pan +9
Large Language Models have demonstrated remarkable reasoning capability in complex textual tasks. However, multimodal reasoning, which requires integrating visual and textual infor…