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

arXiv: https://arxiv.org/abs/2403.03435 · HTML: https://mlsanity.com/paper/2403.03435/

## Key facts

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

## Builds on (most cited first, 4 of 4)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://mlsanity.com/paper/2111.01243/) (2021)
- [A negation detection assessment of GPTs: analysis with the xNot360 dataset](https://mlsanity.com/paper/2306.16638/) (2023)

## Built on by (most cited first, 1 of 1)

- [VLSP 2025 MLQA-TSR Challenge: Vietnamese Multimodal Legal Question Answering on Traffic Sign Regulation](https://mlsanity.com/paper/2510.20381/) (2025)

## 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.