7 papers
The Wittgensteinian Representation Hypothesis: Is Language the Attractor of Multimodal Convergence?
Zhaoyang Zhang, Run Shao, Dongyue Wu +4
Understanding why independently trained neural networks from different modalities converge toward shared representations, and where this convergence leads, remains an open question…
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…
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…
Don't Act Blindly: Robust GUI Automation via Action-Effect Verification and Self-Correction
Yuzhe Zhang, Xianwei Xue, Xingyong Wu +8
Autonomous GUI agents based on vision-language models (VLMs) often assume deterministic environment responses, generating actions without verifying whether previous operations succ…
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…
AllSpark: A Multimodal Spatio-Temporal General Intelligence Model with Ten Modalities via Language as a Reference Framework
Run Shao, Cheng Yang, Qiujun Li +8
Leveraging multimodal data is an inherent requirement for comprehending geographic objects. However, due to the high heterogeneity in structure and semantics among various spatio-t…