ViLegalExpert: A Large-Scale Benchmark for Vietnamese Legal Retrieval and Question Answering from Real-World Consultations

Dat Tien Nguyen, Nghia Hieu Nguyen, Anh Thi-Hoang Nguyen, Dung Ha Nguyen, Kiet Van Nguyen +1 more
9/30/2026
cs.CL

No confident code implementation found for this paper.

Abstract

Trustworthy Legal AI requires systems that can answer legal questions while grounding their responses in authoritative sources. However, existing Vietnamese legal benchmarks provide limited coverage of real-world legal consultations. We introduce \textbf{ViLegalExpert}, a large-scale benchmark constructed from authentic citizen--lawyer consultations, containing over \textbf{172K} questions across \textbf{34 legal domains}, together with professional answers and expert-verified legal evidence. ViLegalExpert supports legal information retrieval, extractive QA, and abstractive QA. Experiments with representative retrieval methods and language models reveal substantial challenges in evidence retrieval and grounded answer generation. While pretrained models perform strongly on QA, hybrid retrieval achieves the best retrieval performance. These results demonstrate the difficulty of mapping naturally expressed legal questions to authoritative provisions and establish ViLegalExpert as a challenging benchmark for reliable Vietnamese Legal AI.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{nguyen2026vilegalexpert,
  title  = {ViLegalExpert: A Large-Scale Benchmark for Vietnamese Legal Retrieval and Question Answering from Real-World Consultations},
  author = {Dat Tien Nguyen and Nghia Hieu Nguyen and Anh Thi-Hoang Nguyen and Dung Ha Nguyen and Kiet Van Nguyen and Ngan Luu-Thuy Nguyen},
  year   = {2026},
  eprint = {2609.39189},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2609.39189v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2609.39189.svg)](https://codeofpaper.com/paper/2609.39189)

Discussion