1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2025
Counterfactual LLM-based Framework for Measuring Rhetorical Style
Jingyi Qiu, Hong Chen, Zongyi Li
The rise of AI has fueled growing concerns about ``hype'' in machine learning papers, yet a reliable way to quantify rhetorical style independently of substantive content has remai…
cs.CL2024★ 1 cited
Sample Design Engineering: An Empirical Study of What Makes Good Downstream Fine-Tuning Samples for LLMs
Biyang Guo, He Wang, Wenyilin Xiao +4
In the burgeoning field of Large Language Models (LLMs) like ChatGPT and LLaMA, Prompt Engineering (PE) is renowned for boosting zero-shot or in-context learning (ICL) through prom…