arXiv:2401.04522
공식 코드 · Papers with Code
LUNA: A Framework for Language Understanding and Naturalness Assessment
원문 초록
The evaluation of Natural Language Generation (NLG) models has gained increased attention, urging the development of metrics that evaluate various aspects of generated text. LUNA addresses this challenge by introducing a unified interface for 20 NLG evaluation metrics. These metrics are categorized based on their reference-dependence and the type of text representation they employ, from string-based n-gram overlap to the utilization of static embeddings and pre-trained language models. The straightforward design of LUNA allows for easy extension with novel metrics, requiring just a few lines of code. LUNA offers a user-friendly tool for evaluating generated texts.
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Beyond One-Size-Fits-All: Inversion Learning for Highly Effective NLG Evaluation Prompts
DeepSeek vs. o3-mini: How Well can Reasoning LLMs Evaluate MT and Summarization?
Making Language Model a Hierarchical Classifier and Generator
Mitigating Object Hallucinations via Sentence-Level Early Intervention
The Devil behind the mask: An emergent safety vulnerability of Diffusion LLMs
Hashed Watermark as a Filter: Defeating Forging and Overwriting Attacks in Weight-based Neural Network Watermarking
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