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VLSP 2023 -- LTER: A Summary of the Challenge on Legal Textual Entailment Recognition

arXiv 2403.03435 ↗First posted 6 Mar 2024cs.CLcited by 1

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Abstract (arXiv)

In this new era of rapid AI development, especially in language processing, the demand for AI in the legal domain is increasingly critical. In the context where research in other languages such as English, Japanese, and Chinese has been well-established, we introduce the first fundamental research for the Vietnamese language in the legal domain: legal textual entailment recognition through the Vietnamese Language and Speech Processing workshop. In analyzing participants' results, we discuss certain linguistic aspects critical in the legal domain that pose challenges that need to be addressed.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 14 references that are in the map. First posted on arXiv 6 Mar 2024.

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4 of 14 references.

References · 4

  1. 2017Attention Is All You Needcited by 59,932
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  3. 2021Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Surveycited by 457
  4. 2023A negation detection assessment of GPTs: analysis with the xNot360 datasetcited by 10

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