collaborators

5 papers

cs.AI2026

DocTrace: Towards Traceable Long Document VQA via Hierarchical Evidence Graph Reasoning

Le Xiang, Zhicheng Guan, Hong Chen +5

Long Document Visual Question Answering (LongDocVQA) requires Multimodal Large Language Models (MLLMs) to locate, integrate, and reason over heterogeneous document elements distrib…

cs.CL2026

Graph-Based Chain-of-Thought Pruning for Reducing Redundant Reflections in Reasoning LLMs

Hongyuan Yuan, Xinran He, Run Shao +6

Extending CoT through RL has been widely used to enhance the reasoning capabilities of LLMs. However, due to the sparsity of reward signals, it can also induce undesirable thinking…

cs.CV2026

Asking like Socrates: Socrates helps VLMs understand remote sensing images

Run Shao, Ziyu Li, Zhaoyang Zhang +9

Recent multimodal reasoning models, inspired by DeepSeek-R1, have significantly advanced vision-language systems. However, in remote sensing (RS) tasks, we observe widespread pseud…

cs.CL2025

Select to Know: An Internal-External Knowledge Self-Selection Framework for Domain-Specific Question Answering

Bolei He, Xinran He, Run Shao +5

Large Language Models (LLMs) perform well in general QA but often struggle in domain-specific scenarios. Retrieval-Augmented Generation (RAG) introduces external knowledge but suff…

cs.CL2025

RISE: Reasoning Enhancement via Iterative Self-Exploration in Multi-hop Question Answering

Bolei He, Xinran He, Mengke Chen +3

Large Language Models (LLMs) excel in many areas but continue to face challenges with complex reasoning tasks, such as Multi-Hop Question Answering (MHQA). MHQA requires integratin…