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20222026
most citedHuman-like Summarization Evaluation with ChatGPT

38 citations · 90 across the 18 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CL2024

Analyzing and Evaluating Correlation Measures in NLG Meta-Evaluation

Mingqi Gao, Xinyu Hu, Li Lin +1

The correlation between NLG automatic evaluation metrics and human evaluation is often regarded as a critical criterion for assessing the capability of an evaluation metric. Howeve…

cs.CL2024

Better than Random: Reliable NLG Human Evaluation with Constrained Active Sampling

Jie Ruan, Xiao Pu, Mingqi Gao +2

Human evaluation is viewed as a reliable evaluation method for NLG which is expensive and time-consuming. To save labor and costs, researchers usually perform human evaluation on a…

cs.CL2024★ 1 cited

Themis: A Reference-free NLG Evaluation Language Model with Flexibility and Interpretability

Xinyu Hu, Li Lin, Mingqi Gao +2

The evaluation of natural language generation (NLG) tasks is a significant and longstanding research area. With the recent emergence of powerful large language models (LLMs), some…

cs.CL2024

Are LLM-based Evaluators Confusing NLG Quality Criteria?

Xinyu Hu, Mingqi Gao, Sen Hu +4

Some prior work has shown that LLMs perform well in NLG evaluation for different tasks. However, we discover that LLMs seem to confuse different evaluation criteria, which reduces…

cs.CL2024★ 15 cited

LLM-based NLG Evaluation: Current Status and Challenges

Mingqi Gao, Xinyu Hu, Jie Ruan +2

Evaluating natural language generation (NLG) is a vital but challenging problem in natural language processing. Traditional evaluation metrics mainly capturing content (e.g. n-gram…