5 papers
LiteResearcher: A Scalable Agentic RL Training Framework for Deep Research Agent
Wanli Li, Bince Qu, 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…
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…
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…
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…
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…