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nlg evaluation

Evaluate the generated text by NLG (Natural Language Generation) systems, like large language models

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Showing 41–50 of 71 papers

TitleStatusHype
CLSE: Corpus of Linguistically Significant EntitiesCode0
Dialect-robust Evaluation of Generated Text—0
NLG-Metricverse: An End-to-End Library for Evaluating Natural Language Generation—0
EffEval: A Comprehensive Evaluation of Efficiency for MT Evaluation MetricsCode0
A Dynamic, Interpreted CheckList for Meaning-oriented NLG Metric Evaluation – through the Lens of Semantic Similarity Rating—0
A Dynamic, Interpreted CheckList for Meaning-oriented NLG Metric Evaluation -- through the Lens of Semantic Similarity Rating—0
The Authenticity Gap in Human Evaluation—0
Near-Negative Distinction: Giving a Second Life to Human Evaluation DatasetsCode0
Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications—0
Bridging Cross-Lingual Gaps During Leveraging the Multilingual Sequence-to-Sequence Pretraining for Text Generation and UnderstandingCode0
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