most citedEnabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs

2 citations · 3 across the 2 of their papers we have counts for

collaborators
Showing cs.CLShow all

2 papers · 1 filter

cs.CL2024★ 1 cited

Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset

Chongjian Yue, Xinrun Xu, Xiaojun Ma +5

Large Language Models (LLMs) demonstrate exceptional performance in textual understanding and tabular reasoning tasks. However, their ability to comprehend and analyze hybrid text,…

cs.CL2023★ 2 cited

Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs

Chongjian Yue, Xinrun Xu, Xiaojun Ma +6

Large Language Models (LLMs) demonstrate exceptional performance in textual understanding and tabular reasoning tasks. However, their ability to comprehend and analyze hybrid text,…