6 papers
LandslideAgent with Multimodal LandslideBench: A Domain-Rule-Augmented Agent for Autonomous Landslide Identification and Analysis
Chengfu Liu, Dongyang Hou, Junwu Xiang +5
Intelligent landslide hazard interpretation is critical for disaster prevention, yet current paradigms struggle to simultaneously extract visual features and high-level geoscientif…
RS-Claw: Progressive Active Tool Exploration via Hierarchical Skill Trees for Remote Sensing Agents
Liangtian Liu, Zeyuan Wang, Ziyu Li +8
The rise of multi-modal large language models (MLLMs) is shifting remote sensing (RS) intelligence from "see" to "action", as OpenClaw-style frameworks enable agents to autonomousl…
What Will Happen Next: Large Models-Driven Deduction for Emergency Instances
Zhengqing Hu, Dong Chen, Junkun Yuan +6
Traditional simulation methods reproduce occurred emergency instances through presetting to assist people in risk assessment and emergency decision-making. However, due to the lack…
Bidirectional Semantic Complementary Tool Retrieval for Remote Sensing Agents
Zeyuan Wang, Dongyang Hou, Cheng Yang +10
Large language model (LLM)-based agents provide a novel paradigm for the automated processing of remote sensing(RS) data. Their success in complex RS tasks rely on extensive specia…
MAS-Bench: A Unified Benchmark for Shortcut-Augmented Hybrid Mobile GUI Agents
Pengxiang Zhao, Guangyi Liu, YaoZhen Liang +11
Shortcuts such as APIs and deep-links have emerged as efficient complements to flexible GUI operations, fostering a promising hybrid paradigm for MLLM-based mobile automation. Howe…
CogDDN: A Cognitive Demand-Driven Navigation with Decision Optimization and Dual-Process Thinking
Yuehao Huang, Liang Liu, Shuangming Lei +7
Mobile robots are increasingly required to navigate and interact within unknown and unstructured environments to meet human demands. Demand-driven navigation (DDN) enables robots t…