https://github.com/tharindudr/multilingual-semantic-textual-similarity
https://github.com/tharindudr/multilingual-semantic-textual-similarity
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/tharindudr/multilingual-semantic-textual-similarity
- Owner: TharinduDR
- Created: 2021-11-24T15:22:08.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2025-03-31T14:51:46.000Z (about 2 months ago)
- Last Synced: 2025-04-14T11:02:26.217Z (about 1 month ago)
- Language: Jupyter Notebook
- Size: 5.94 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Multilingual Semantic Textual Similarity
Semantic textual similarity (STS) is a natural language processing (NLP) task that quantitatively assesses the semantic similarity between two text snippets. STS is a fundamental NLP task for many text-related applications, including text de-duplication, paraphrase detection, semantic searching, and question answering. Measuring STS is a machine learning (ML) problem, where an ML model predicts a value that represents the similarity of the two input texts.
This project catalogues the datasets annotated for semantic textual similarity. Then we perform a comparative evaluation of several deep learning based STS methods in these datasets. This site presents the datasets and pre-trained models evaluated in the Multilingual Semantic Textual Similarity project.
## Citation
If you use these resources, please cite (and read!) our paper:
```bash
Coming soon
```