5 papers
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…
RS-WorldModel: a Unified Model for Remote Sensing Understanding and Future Sense Forecasting
Linrui Xu, Zhongan Wang, Fei Shen +4
Remote sensing world models aim to both explain observed changes and forecast plausible futures, two tasks that share spatiotemporal priors. Existing methods, however, typically ad…
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…
Learning on the Job: An Experience-Driven Self-Evolving Agent for Long-Horizon Tasks
Cheng Yang, Xuemeng Yang, Licheng Wen +9
Large Language Models have demonstrated remarkable capabilities across diverse domains, yet significant challenges persist when deploying them as AI agents for real-world long-hori…
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…