Machine Translation is one of the essential tasks in Natural Language Processing (NLP), which has massive applications in real life as well as contributing to other tasks in the NLP research community.
In addition, to prove the generalization of our proposed model, we also conduct extensive experiments on three translation datasets IWLST14 German-English, IWSLT15 Vietnamese-English, WMT14 English-German, and show significant improvement.
Ranked #1 on Semantic Parsing on ATIS
We introduce efficient deep learning-based methods for legal document processing including Legal Document Retrieval and Legal Question Answering tasks in the Automated Legal Question Answering Competition (ALQAC 2022).
Ambiguity is a characteristic of natural language, which makes expression ideas flexible.
COLIEE is an annual competition in automatic computerized legal text processing.
Semantic parsing is a challenging task whose purpose is to convert a natural language utterance to machine-understandable information representation.
We propose deep learning based methods for automatic systems of legal retrieval and legal question-answering in COLIEE 2020.