2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.CL2023
CoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction Tuning
Yilun Liu, Shimin Tao, Xiaofeng Zhao +11
Instruction tuning is crucial for enabling Language Learning Models (LLMs) in responding to human instructions. The quality of instruction pairs used for tuning greatly affects the…
cs.SE2023
Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies
Yilun Liu, Shimin Tao, Weibin Meng +7
Automated log analysis is crucial in modern software-intensive systems for facilitating program comprehension throughout software maintenance and engineering life cycles. Existing…
cs.CL2023★ 2 cited
Knowledge-Prompted Estimator: A Novel Approach to Explainable Machine Translation Assessment
Hao Yang, Min Zhang, Shimin Tao +3
Cross-lingual Machine Translation (MT) quality estimation plays a crucial role in evaluating translation performance. GEMBA, the first MT quality assessment metric based on Large L…