5 papers
TQA-Bench: Evaluating LLMs for Multi-Table Question Answering
Zipeng Qiu, Chenyue Li, You Peng +3
The advance of large language models (LLMs) has unlocked great opportunities in complex multi-modal data management tasks, particularly in question answering (QA) over complicated…
S2SServiceBench: A Multimodal Benchmark for Last-Mile S2S Climate Services
Chenyue Li, Wen Deng, Zhuotao Sun +9
Subseasonal-to-seasonal (S2S) forecasts play an essential role in providing a decision-critical weeks-to-months planning window for climate resilience and sustainability, yet a gro…
CLIMATEAGENT: Multi-Agent Orchestration for Complex Climate Data Science Workflows
Hyeonjae Kim, Chenyue Li, Wen Deng +4
Climate science demands automated workflows to transform comprehensive questions into data-driven statements across massive, heterogeneous datasets. However, generic LLM agents and…
AtmosSci-Bench: Evaluating the Recent Advance of Large Language Model for Atmospheric Science
Chenyue Li, Wen Deng, Mengqian Lu +1
The rapid advancements in large language models (LLMs), particularly in their reasoning capabilities, hold transformative potential for addressing complex challenges and boosting s…
Zero-Indexing Internet Search Augmented Generation for Large Language Models
Guangxin He, Zonghong Dai, Jiangcheng Zhu +6
Retrieval augmented generation has emerged as an effective method to enhance large language model performance. This approach typically relies on an internal retrieval module that u…