40 citations · 45 across the 13 of their papers we have counts for
13 papers
Learning Continuous Regional Temperature Fields with Lead-Time and Resolution Queries
Chunlei Shi, Jiong Wang, Yi-Lin Wei +4
Accurate regional near-surface temperature forecasting is fundamental to short-range weather services and downstream risk assessment. Existing deep learning-based regional forecast…
Obshazard-bench: Benchmarking Multimodal Foundation Models for Real-Time Disaster Intelligence from Raw Earth Observation Streams
Fengxiang Wang, Qiuyang Yu, Yueying Li +14
Multimodal Large Language Models (MLLMs) are increasingly used to interpret Earth observation data, yet their capability to support real-world disaster emergency response remains i…
AutoSupervision: Closing the Feedback Loop in Scientific Workflows with Grounded Revision Verification
Haobo Li, Eunseo Jung, Wenxiao Zhao +8
Recent advances in large language models (LLMs) have enabled AI systems to assist scientific research and peer review. However, an essential capability for reliable AI-assisted sci…
Agents-K1: Towards Agent-native Knowledge Orchestration
Zongsheng Cao, Bihao Zhan, Jinxin Shi +25
Current LLM-based research agents have advanced through agent orchestration, yet largely overlook scientific knowledge orchestration. Existing works often reduce papers to abstract…
LangRetrieval: Language-Guided Self-Evolving Satellite-to-Radar Retrieval via CSI-Driven Reward
Chunlei Shi, Junming Hou, Yi-Lin Wei +5
Satellite-to-radar (S2R) retrieval estimates ground radar precipitation from geostationary satellite observations, providing a critical solution for precipitation monitoring in rad…
TRACE: A Multi-Agent System for Autonomous Physical Reasoning for Seismology
Feng Liu, Jian Xu, Xin Cui +11
Modern seismic networks resolve earthquake sequences in unprecedented detail, yet explaining how large earthquakes emerge from evolving fault systems remains difficult. We introduc…
InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery
Shiyang Feng, Runmin Ma, Xiangchao Yan +53
We introduce InternAgent-1.5, a unified system designed for end-to-end scientific discovery across computational and empirical domains. The system is built on a structured architec…
EWE: An Agentic Framework for Extreme Weather Analysis
Zhe Jiang, Jiong Wang, Xiaoyu Yue +5
Extreme weather events pose escalating risks to global society, underscoring the urgent need to unravel their underlying physical mechanisms. Yet the prevailing expert-driven, labo…
A Self-Evolving AI Agent System for Climate Science
Zijie Guo, Jiong Wang, Fenghua Ling +19
Scientific progress in Earth science depends on integrating data across the planet's interconnected spheres. However, the accelerating volume and fragmentation of multi-sphere know…
OmniEarth-Bench: Towards Holistic Evaluation of Earth's Six Spheres and Cross-Spheres Interactions with Multimodal Observational Earth Data
Fengxiang Wang, Mingshuo Chen, Xuming He +15
Existing benchmarks for multimodal learning in Earth science offer limited, siloed coverage of Earth's spheres and their cross-sphere interactions, typically restricting evaluation…
Molly: Making Large Language Model Agents Solve Python Problem More Logically
Rui Xiao, Jiong Wang, Lu Han +2
Applying large language models (LLMs) as teaching assists has attracted much attention as an integral part of intelligent education, particularly in computing courses. To reduce th…
QACP: An Annotated Question Answering Dataset for Assisting Chinese Python Programming Learners
Rui Xiao, Lu Han, Xiaoying Zhou +3
In online learning platforms, particularly in rapidly growing computer programming courses, addressing the thousands of students' learning queries requires considerable human cost.…
LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark
Zhenfei Yin, Jiong Wang, Jianjian Cao +9
Large language models have emerged as a promising approach towards achieving general-purpose AI agents. The thriving open-source LLM community has greatly accelerated the developme…