4 papers
From Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms
Zhaokun Jiang, Ziyin Zhang
Recent advancements in machine learning have spurred growing interests in automated interpreting quality assessment. Nevertheless, existing research suffers from insufficient exami…
Convergences and Divergences between Automatic Assessment and Human Evaluation: Insights from Comparing ChatGPT-Generated Translation and Neural Machine Translation
Zhaokun Jiang, Qianxi Lv, Ziyin Zhang +1
Large language models have demonstrated parallel and even superior translation performance compared to neural machine translation (NMT) systems. However, existing comparative studi…
Distinguishing Translations by Human, NMT, and ChatGPT: A Linguistic and Statistical Approach
Zhaokun Jiang, Qianxi Lv, Ziyin Zhang +1
The growing popularity of neural machine translation (NMT) and LLMs represented by ChatGPT underscores the need for a deeper understanding of their distinct characteristics and rel…
Multiple-Choice Questions are Efficient and Robust LLM Evaluators
Ziyin Zhang, Zhaokun Jiang, Lizhen Xu +2
We present GSM-MC, a multiple-choice (MC) dataset constructed by collecting answers and incorrect predictions on GSM8K from 60 open-source models. Through extensive experiments, we…