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Not All Metrics Are Guilty: Improving NLG Evaluation by Diversifying References
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Not All Metrics Are Guilty: Improving NLG Evaluation by Diversifying References

Tianyi Tang
Hongyuan Lu
Yuchen Eleanor Jiang
Haoyang Huang
Dongdong Zhang
Wayne Xin Zhao
Tom Kocmi
Furu Wei
ArXiv (abs)PDFHTMLGithub (3★)

Papers citing "Not All Metrics Are Guilty: Improving NLG Evaluation by Diversifying References"

3 / 3 papers shown
Title
Evaluation Should Not Ignore Variation: On the Impact of Reference Set Choice on Summarization Metrics
Evaluation Should Not Ignore Variation: On the Impact of Reference Set Choice on Summarization Metrics
Silvia Casola
Yang Liu
Siyao Peng
Oliver Kraus
Albert Gatt
Barbara Plank
23
0
0
17 Jun 2025
RevisEval: Improving LLM-as-a-Judge via Response-Adapted References
RevisEval: Improving LLM-as-a-Judge via Response-Adapted References
Qiyuan Zhang
Yufei Wang
Tiezheng YU
Yuxin Jiang
Chuhan Wu
...
Xin Jiang
Lifeng Shang
Ruiming Tang
Fuyuan Lyu
Chen Ma
131
7
0
07 Oct 2024
Chain-of-Dictionary Prompting Elicits Translation in Large Language Models
Chain-of-Dictionary Prompting Elicits Translation in Large Language Models
Hongyuan Lu
Haoran Yang
Haoyang Huang
Dongdong Zhang
Wai Lam
Furu Wei
LRMAI4CE
108
18
0
11 May 2023

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