14 citations · 23 across the 10 of their papers we have counts for
4 papers · 1 filter
SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
Sihang Li, Jin Huang, Jiaxi Zhuang +7
Scientific literature understanding is crucial for extracting targeted information and garnering insights, thereby significantly advancing scientific discovery. Despite the remarka…
MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows
Xingjian Zhang, Yutong Xie, Jin Huang +8
Scientific innovation relies on detailed workflows, which include critical steps such as analyzing literature, generating ideas, validating these ideas, interpreting results, and i…
DCA-Bench: A Benchmark for Dataset Curation Agents
Benhao Huang, Yingzhuo Yu, Jin Huang +2
The quality of datasets plays an increasingly crucial role in the research and development of modern artificial intelligence (AI). Despite the proliferation of open dataset platfor…
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
Hengxing Cai, Xiaochen Cai, Junhan Chang +20
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis. However, existing benchmarks fail to adequately evaluate the proficiency of…