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cs.CL2026
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…
cs.CL2026
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…
cs.CL2024
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…