mlsanityData to 7 Oct 2026

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models

arXiv 2512.14554 ↗First posted 16 Dec 2025cs.CL cs.AIcited by 1

On the map: LLM reasoning → Reasoning for agents, planning and code

Abstract (arXiv)

The rapid advancement of large language models (LLMs) has enabled new possibilities for applying artificial intelligence within the legal domain. Nonetheless, the complexity, hierarchical organization, and frequent revisions of Vietnamese legislation pose considerable challenges for evaluating how well these models interpret and utilize legal knowledge. To address this gap, the Vietnamese Legal Benchmark (VLegal-Bench) is introduced, the first comprehensive benchmark designed to systematically assess LLMs on Vietnamese legal tasks. Informed by Bloom's cognitive taxonomy, VLegal-Bench encompasses multiple levels of legal understanding through tasks designed to reflect practical usage scenarios. The benchmark comprises 10,450 samples generated through a rigorous annotation pipeline, where legal experts label and cross-validate each instance using our annotation system to ensure every sample is grounded in authoritative legal documents and mirrors real-world legal assistant workflows, including general legal questions and answers, retrieval-augmented generation, multi-step reasoning, and scenario-based problem solving tailored to Vietnamese law. By providing a standardized, transparent, and cognitively informed evaluation framework, VLegal-Bench establishes a solid foundation for assessing LLM performance in Vietnamese legal contexts and supports the development of more reliable, interpretable, and ethically aligned AI-assisted legal systems. To facilitate access and reproducibility, we provide a public landing page for this benchmark at https://vilegalbench.cmcai.vn/.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 5 of its 22 references that are in the map. First posted on arXiv 16 Dec 2025.

Builds on

5 of 22 references.

References · 5

  1. 2025Agentic Retrieval-Augmented Generation: A Survey on Agentic RAGcited by 242
  2. 2023Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecturecited by 119
  3. 2023DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Servicescited by 117
  4. 2023A Short Survey of Viewing Large Language Models in Legal Aspectcited by 51
  5. 2024Vietnamese Legal Information Retrieval in Question-Answering Systemcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

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  1. 2023LawBench: Benchmarking Legal Knowledge of Large Language Models
  2. 2026From Benchmarking to Reasoning: A Dual-Aspect, Large-Scale Evaluation of LLMs on Vietnamese Legal Text
  3. 2025Evaluating Test-Time Scaling LLMs for Legal Reasoning: OpenAI o1, DeepSeek-R1, and Beyond
  4. 2023LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
  5. 2023One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support
  6. 2024LegalAgentBench: Evaluating LLM Agents in Legal Domain
  7. 2025Benchmarking Multi-Step Legal Reasoning and Analyzing Chain-of-Thought Effects in Large Language Models
  8. 2026Evaluation of Large Language Models in Legal Applications: Challenges, Methods, and Future Directions