arXiv:1805.11474
공식 코드 · Papers with Code
Human vs Automatic Metrics: on the Importance of Correlation Design
원문 초록
This paper discusses two existing approaches to the correlation analysis between automatic evaluation metrics and human scores in the area of natural language generation. Our experiments show that depending on the usage of a system- or sentence-level correlation analysis, correlation results between automatic scores and human judgments are inconsistent.
함께 살펴볼 논문
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Mitigating Object Hallucinations via Sentence-Level Early Intervention
The Reader is the Metric: How Textual Features and Reader Profiles Explain Conflicting Evaluations of AI Creative Writing
Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal Transport
A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations
EEG2TEXT-CN: An Exploratory Study of Open-Vocabulary Chinese Text-EEG Alignment via Large Language Model and Contrastive Learning on ChineseEEG
Exploring Naive Approaches to Tell Apart LLMs Productions from Human-written Text
토론
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