THUNLP-MT/TRICE

Code for our paper "Transfer Learning for Sequence Generation: from Single-source to Multi-source" in ACL 2021.

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Experimental

This project offers a framework to improve the accuracy of machine translation and document summarization systems. It takes text from one or more source languages (or multiple documents) and produces more accurate translated text or a summary, especially when dealing with complex, multi-source information. Researchers and developers working on advanced natural language processing tasks will find this useful.

No commits in the last 6 months.

Use this if you are a researcher or NLP developer looking to improve state-of-the-art results in tasks like automatic post-editing, multi-source machine translation, or multi-document summarization.

Not ideal if you are looking for a ready-to-use, off-the-shelf translation or summarization application without technical implementation.

natural-language-processing machine-translation document-summarization computational-linguistics sequence-generation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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Language

Python

License

BSD-3-Clause

Last pushed

Jun 01, 2021

Commits (30d)

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