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Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models

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arxiv 2403.01616 v2 pith:FTCXFOQC submitted 2024-03-03 cs.CL

Nguyen Quang Duc , Le Hai Son , Nguyen Duc Nhan , Nguyen Dich Nhat Minh , Le Thanh Huong , Dinh Viet Sang This is my paper · ORCID
classification cs.CL
keywords generationlanguagemodelsvietnameselargeretrieval-augmentedtowardsadvancing
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This paper presents our contributions towards advancing the state of Vietnamese language understanding and generation through the development and dissemination of open datasets and pre-trained models for Vietnamese Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs).

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. VN-MTEB: Vietnamese Massive Text Embedding Benchmark

    cs.CL 2025-07 conditional novelty 6.0 of 10

    VN-MTEB is a new 41-dataset Vietnamese benchmark for text embeddings, built by machine-translating MTEB datasets with embedding-based and LLM-based quality filters.

  2. Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining

    cs.IR 2025-07 conditional novelty 4.0 of 10

    A lightweight Bi-Encoder plus Cross-Encoder pipeline with random top-candidate negative sampling achieves 79.1% MRR@10 on Vietnamese legal retrieval.

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