How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
BLEURT is an evaluation metric for Natural Language Generation. It takes a pair of sentences as input, a reference and a candidate, and it returns a score that indicates to what extent the candidate is fluent and conveys the meaning of the reference. It is comparable to sentence-BLEU, BERTscore,…
The main features of google-research/bleurt are: Evaluation.
Open-source alternatives to google-research/bleurt include: facebookresearch/vizseq — VizSeq is a Python toolkit for visual analysis on text generation tasks like machine translation, summarization, image… maluuba/nlg-eval — Evaluation code for various unsupervised automated metrics for NLG (Natural Language Generation). It takes as input a… neulab/compare-mt — by NeuLab @ CMU LTI, and other contributors.
VizSeq is a Python toolkit for visual analysis on text generation tasks like machine translation, summarization, image captioning, speech translation and video description. It takes multi-modal sources, text references as well as text predictions as inputs, and analyzes them visually in Jupyter…
Evaluation code for various unsupervised automated metrics for NLG (Natural Language Generation). It takes as input a hypothesis file, and one or more references files and outputs values of metrics. Rows across these files should correspond to the same example.
