5 citations · 14 across the 8 of their papers we have counts for
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cs.CL2023★ 2 cited
DocMath-Eval: Evaluating Math Reasoning Capabilities of LLMs in Understanding Long and Specialized Documents
Yilun Zhao, Yitao Long, Hongjun Liu +7
Recent LLMs have demonstrated remarkable performance in solving exam-like math word problems. However, the degree to which these numerical reasoning skills are effective in real-wo…
cs.CL2023★ 5 cited
Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data?
Xiangru Tang, Yiming Zong, Jason Phang +4
Despite the remarkable capabilities of Large Language Models (LLMs) like GPT-4, producing complex, structured tabular data remains challenging. Our study assesses LLMs' proficiency…