QuangDuy/supervised_data

HUIT-Embedding — supervised data (Vietnamese)

(query, positive, negatives[]) rows for fine-tuning Vietnamese embedding models: 19 non-empty sources, 1,827,077 rows. Processed on 2026-10-21. Only negatives that ship with the source are included; mined hard negatives are in separate repositories (see Hard-negative variants). Rows that overlap evaluation data are removed.

Usage

from datasets import load_dataset

ds = load_dataset("QuangDuy/supervised_data", "vinli", split="train")

Schema

Column	Type	Meaning
query	string	Question, claim or premise
positive	string	Relevant document or entailed sentence
negatives	list[string]	Negatives provided by the source
negative_type	list[string]	contradiction, refuted_evidence, distractor or provided
source	string	Config name
label_origin	string	human_paper, competition, translated or synthetic
translated	bool	Machine-translated text
group_id	string	Rows sharing a query or document
license	string	Source license

Sources

Config	Source	Paper	License	Label origin	Translated	Rows in	Rows out	Kept	Queries	Avg negatives	Query p50/p95	Positive p50/p95
vinli	presencesw/vinli_4_label	paper	unknown	human_paper	False	6,094	4,228	69.4%	2,107	2.013	32/61	21/37
vianli	uitnlp/ViANLI	paper	mit	human_paper	False	2,615	1,657	63.4%	1,606	0.916	32/59	16/31
vinli_simcse_v2	anti-ai/ViNLI-SimCSE-supervised_v2	paper	mit	translated	True	275,601	269,934	97.9%	268,952	0.992	18/54	10/23
mmarco_vi	unicamp-dl/mmarco, GreenNode/msmarco-vn	paper	apache-2.0 (repo); passages from GreenNode/msmarco-vn cc-by-sa-4.0; MS MARCO terms (non-commercial)	translated	True	532,743	509,371	95.6%	470,747	0.0	8/15	78/152
viquad2	taidng/UIT-ViQuAD2.0	paper	unknown	human_paper	False	19,238	0	0.0%	0	0.0	0/0	0/0
vimqa	nguyenlab/vimqa	paper	cc-by-nc-sa-4.0	human_paper	False	14,588	13,050	89.5%	7,159	8.057	19/31	132/350
vlogqa	uitnlp/vlogqa	paper	cc-by-sa-4.0	human_paper	False	8,386	3,846	45.9%	3,839	0.0	12/18	3428/7889
vire4mrc	https://github.com/DoPhamPhucTinh/ViRe4MRC/raw/main/ViRe4MRC.zip	paper	unknown (README: research purposes only, not for commercial use)	human_paper	False	5,297	2,667	50.3%	2,612	0.0	12/17	93/171
virhe4qa	TaiDoan123/UIT-R2GQA (config triplet)	paper	unknown	human_paper	False	7,806	75	1.0%	75	0.013	15/25	264/613
multi_wiki_qa	alexandrainst/multi-wiki-qa (config vi)	paper	cc-by-nc-sa-4.0	synthetic	False	5,000	4,932	98.6%	4,932	0.0	16/27	684/4917
vimedaqa	tmnam20/ViMedAQA	paper	unknown	human_paper	False	39,881	31,486	78.9%	31,437	0.0	15/25	111/312
vihealthqa	tarudesu/ViHealthQA	paper	unknown	human_paper	False	7,009	6,586	94.0%	6,583	0.0	16/80	96/295
vicov19qa	https://raw.githubusercontent.com/triet2397/UIT-ViCoV19QA/main/dataset/4_ans/UIT-ViCoV19QA_train.csv	paper	unknown (README: research purposes only)	human_paper	False	5,704	4,632	81.2%	2,911	0.0	30/98	84/377
csconda	ura-hcmut/Vietnamese-Customer-Support-QA	paper	cc-by-nc-4.0	human_paper	False	8,349	20	0.2%	19	0.0	13/29	43/127
vifactcheck	tranthaihoa/vifactcheck	paper	mit	human_paper	False	1,751	1,596	91.1%	1,595	2.482	37/65	50/111
viwikifc	High-Will/ViWikiFC	paper	cc-by-4.0	human_paper	False	5,594	1,802	32.2%	1,802	0.698	25/53	36/83
isedsc2024	MiuN2k3/isedsc.train.dataset	–	unknown	competition	False	8,519	7,951	93.3%	7,946	0.0	22/53	28/58
zalo_legal_triplets	batmangiaicuuthegioi/zalo-legal-triplets	–	unknown	competition	False	37,059	0	0.0%	0	0.0	0/0	0/0
zalo_legal	GreenNode/zalo-ai-legal-text-retrieval-vn	–	mit	competition	False	2,505	0	0.0%	0	0.0	0/0	0/0
vietnamese_law_hn_mined	GreenNode/Vietnamese-Law-hn-mined-v2	–	unknown	competition	False	354,123	338,193	95.5%	328,102	6.868	29/45	222/1106
large_vi_legal_queries	phamson02/large-vi-legal-queries	paper	cc-by-4.0	synthetic	False	507,152	498,454	98.3%	494,476	0.0	27/40	208/266
table_markdown_retrieval	GreenNode/GreenNode-Table-Markdown-Retrieval-VN	–	mit	synthetic	False	143,106	126,597	88.5%	125,842	0.0	22/33	325/507

Notes:

• viquad2: almost all rows removed by ViRE decontamination
• csconda: almost all rows removed by ViRE decontamination
• zalo_legal_triplets: almost all rows removed by ViRE decontamination
• zalo_legal: almost all rows removed by ViRE decontamination
• table_markdown_retrieval: Label origin is not documented; questions look model-generated.
• Not published (no rows left after decontamination): viquad2, zalo_legal_triplets, zalo_legal

Rows removed and decontamination

Cleaning, language and statistical filters as for the unsupervised data, dedup on (query, positive), and removal of every row overlapping the evaluation blocklist (all of ViRE, VN-MTEB test data and the test splits of the training sources).

Config	Rows dropped (reason: count)	Eval overlap by set (top 5)	Negative types
vinli	eval_overlap: 1,857, lang: 6, duplicate: 3	viqpc_test: 1,835, vianli_test: 12, vinli_test: 10	contradiction: 8,512
vianli	eval_overlap: 952, lang: 6	vianli_test: 932, viqpc_test: 12, vinli_test: 8	contradiction: 1,518
vinli_simcse_v2	lang: 2,665, query_equals_positive: 2,047, stat_repeat: 344, eval_overlap: 289, too_short: 255, duplicate: 42, stat_upper: 12, stat_special: 12, empty: 1	vnmteb_sickr-sts-vn: 279, vnmteb_stsbenchmark-sts-vn: 10	contradiction: 267,677
mmarco_vi	lang: 21,023, too_short: 1,465, duplicate: 412, eval_overlap: 265, stat_upper: 95, stat_special: 89, stat_repeat: 22, empty: 1	vnmteb_msmarco-vn: 125, vnmteb_dbpedia-vn: 47, vimqa_test: 22, vnmteb_quora-vn: 22, vnmteb_hotpotqa-vn: 16	–
viquad2	eval_overlap: 19,162, lang: 74, too_short: 2	vire_uit-viquad2: 19,162	–
vimqa	eval_overlap: 1,516, lang: 21, stat_upper: 1	vimqa_test: 1,405, viqpc_test: 60, vinli_test: 31, viwikifc_test: 20	distractor: 105,142
vlogqa	eval_overlap: 4,491, lang: 46, duplicate: 3	vire_vlogqa_2: 4,433, vlogqa_test: 58	–
vire4mrc	eval_overlap: 2,599, lang: 24, duplicate: 4, stat_special: 3	vire_vire4mrc_v2: 2,522, vire4mrc_test: 77	–
virhe4qa	eval_overlap: 7,629, duplicate: 84, stat_upper: 17, lang: 1	vire_virhe4qa_v2: 7,427, virhe4qa_test: 202	provided: 1
multi_wiki_qa	lang: 37, eval_overlap: 25, stat_repeat: 6	viqpc_test: 25	–
vimedaqa	eval_overlap: 8,114, lang: 174, empty: 76, stat_repeat: 18, too_short: 10, duplicate: 2, stat_upper: 1	vimedaqa_test: 5,884, vire_vimedaqa_v2: 2,205, vire_vinewsqa: 19, isedsc_dev: 3, viqpc_test: 2	–
vihealthqa	eval_overlap: 399, lang: 19, duplicate: 5	vicov19qa_test: 333, vihealthqa_test: 64, vire_vinewsqa: 1, viqpc_test: 1	–
vicov19qa	eval_overlap: 1,019, lang: 38, duplicate: 9, stat_upper: 3, too_short: 2, empty: 1	vihealthqa_test: 939, vicov19qa_test: 77, vire_alqac: 2, vianli_test: 1	–
csconda	eval_overlap: 7,612, lang: 559, too_short: 140, duplicate: 12, stat_upper: 3, stat_special: 1, empty: 1, stat_repeat: 1	vire_csconda: 7,612	–
vifactcheck	query_equals_positive: 118, eval_overlap: 37	vifactcheck_test: 36, isedsc_dev: 1	refuted_evidence: 3,962
viwikifc	eval_overlap: 3,776, query_equals_positive: 13, duplicate: 2, lang: 1	viwikifc_test: 3,731, viqpc_test: 43, vire_uit-viquad2: 2	refuted_evidence: 1,257
isedsc2024	duplicate: 216, too_short: 188, eval_overlap: 138, lang: 14, query_equals_positive: 10, stat_repeat: 2	isedsc_test: 73, isedsc_dev: 62, vifactcheck_test: 3	refuted_evidence: 1
zalo_legal_triplets	eval_overlap: 36,992, duplicate: 65, stat_repeat: 2	vire_zalolegalqa: 36,992	–
zalo_legal	eval_overlap: 2,505	vire_zalolegalqa: 2,505	–
vietnamese_law_hn_mined	eval_overlap: 11,918, duplicate: 820, stat_upper: 25, stat_repeat: 4, lang: 3, too_short: 1	vnmteb_TVPL-Retrieval-VN: 7,197, hoidap_tvpl_test: 1,530, viqpc_test: 1,355, hoidap_tvpl200k_test: 756, vire_zalolegalqa: 548	provided: 2,322,749
large_vi_legal_queries	eval_overlap: 8,328, stat_upper: 187, stat_special: 98, stat_repeat: 69, lang: 12, duplicate: 4	vnmteb_TVPL-Retrieval-VN: 2,560, viqpc_test: 2,444, vire_zalolegalqa: 1,842, hoidap_tvpl_test: 716, hoidap_tvpl200k_test: 371	–
table_markdown_retrieval	stat_repeat: 12,753, eval_overlap: 1,814, lang: 977, stat_special: 892, stat_upper: 60, empty: 9, too_short: 4	vnmteb_GreenNode-Table-Markdown-Retrieval-VN: 1,814	–

Composition

By label origin: translated: 42.7%, synthetic: 34.5%, competition: 18.9%, human_paper: 3.9%

Hard-negative variants

Mined hard negatives for these rows are published separately, one repository per method, so each can be compared in ablations. All use intfloat/multilingual-e5-large as retriever and BAAI/bge-reranker-v2-m3 as teacher, and ship each config twice (texts included, or ids with a documents table).

Repository	Method	Paper
QuangDuy/supervised_data-hn-candidates	Top-200 retrieval candidates with scores (base of the others; also for SimANS or false-negative masking at training time)	Multilingual E5
QuangDuy/supervised_data-hn-percpos	TopK-PercPos, p = 0.90 / 0.95 / 0.99 and an F2LLM variant	NV-Retriever, F2LLM
QuangDuy/supervised_data-hn-rankwindow	Consistency filter (positive in top 50) and negatives from ranks 30–100 or 50–100	KaLM-Embedding
QuangDuy/supervised_data-hn-rerank-denoise	Teacher-scored candidates: near-copy extra positives, flagged false negatives, negatives and all scores for KL distillation	RocketQA, RLHN

vire4mrc and vlogqa have no mined negatives: their questions depend on the passage, so top candidates usually answer them too.

Citations

@inproceedings{huynh-etal-2022-vinli,
    title = "{V}i{NLI}: A {V}ietnamese Corpus for Studies on Open-Domain Natural Language Inference",
    author = "Huynh, Tin Van  and
      Nguyen, Kiet Van  and
      Nguyen, Ngan Luu-Thuy",
    editor = "Calzolari, Nicoletta  and
      Huang, Chu-Ren  and
      Kim, Hansaem  and
      Pustejovsky, James  and
      Wanner, Leo  and
      Choi, Key-Sun  and
      Ryu, Pum-Mo  and
      Chen, Hsin-Hsi  and
      Donatelli, Lucia  and
      Ji, Heng  and
      Kurohashi, Sadao  and
      Paggio, Patrizia  and
      Xue, Nianwen  and
      Kim, Seokhwan  and
      Hahm, Younggyun  and
      He, Zhong  and
      Lee, Tony Kyungil  and
      Santus, Enrico  and
      Bond, Francis  and
      Na, Seung-Hoon",
    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2022.coling-1.339/",
    pages = "3858--3872"
}

@article{vianli,
title = {A New Benchmark Dataset and Mixture-of-Experts Language Models for Adversarial Natural Language Inference in Vietnamese},
journal = {Expert Systems with Applications},
pages = {130109},
year = {2025},
issn = {0957-4174},
doi = {https://doi.org/10.1016/j.eswa.2025.130109},
url = {https://www.sciencedirect.com/science/article/pii/S095741742503725X},
author = {Tin Van Huynh, Kiet Van Nguyen and Ngan Luu-Thuy Nguyen},
}

@inproceedings{williams-etal-2018-broad,
    title = "A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference",
    author = "Williams, Adina  and
      Nangia, Nikita  and
      Bowman, Samuel R.",
    editor = "Walker, Marilyn  and
      Ji, Heng  and
      Stent, Amanda",
    booktitle = "Proceedings of the 2018 Conference of the {N}orth {A}merican Chapter of the {A}ssociation for {C}omputational {L}inguistics: Human Language Technologies, Volume 1 (Long Papers)",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N18-1101/",
    doi = "10.18653/v1/N18-1101",
    pages = "1112--1122"
}

@misc{bonifacio2022mmarcomultilingualversionms,
      title={mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset}, 
      author={Luiz Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and Roberto Lotufo and Rodrigo Nogueira},
      year={2022},
      eprint={2108.13897},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2108.13897}, 
}

@misc{bajaj2018msmarcohumangenerated,
      title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset}, 
      author={Payal Bajaj and Daniel Campos and Nick Craswell and Li Deng and Jianfeng Gao and Xiaodong Liu and Rangan Majumder and Andrew McNamara and Bhaskar Mitra and Tri Nguyen and Mir Rosenberg and Xia Song and Alina Stoica and Saurabh Tiwary and Tong Wang},
      year={2018},
      eprint={1611.09268},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/1611.09268}, 
}

@article{vlsp2021-vimrc,
   title={VLSP 2021-ViMRC Challenge: Vietnamese Machine Reading Comprehension},
   volume={38},
   ISSN={2615-9260},
   url={http://dx.doi.org/10.25073/2588-1086/vnucsce.340},
   DOI={10.25073/2588-1086/vnucsce.340},
   number={2},
   journal={VNU Journal of Science: Computer Science and Communication Engineering},
   publisher={Vietnam National University Journal of Science},
   author={Nguyen, Kiet and Tran, Son Quoc and Nguyen, Luan Thanh and Huynh, Tin Van and Luu, Son Thanh and Nguyen, Ngan Luu-Thuy},
   year={2022},
   month=dec}

% source: https://huggingface.co/datasets/tarudesu/ViHealthQA (dataset card citation block)
@InProceedings{nguyen2022viheathqa,
  author="Nguyen, Nhung Thi-Hong
  and Ha, Phuong Phan-Dieu
  and Nguyen, Luan Thanh
  and Van Nguyen, Kiet
  and Nguyen, Ngan Luu-Thuy",
  title="SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts",
  booktitle="Knowledge Science, Engineering and Management",
  year="2022",
  publisher="Springer International Publishing",
  address="Cham",
  pages="371--382",
  isbn="978-3-031-10986-7"
}

@inproceedings{nguyen-etal-2020-vietnamese,
    title = "A {V}ietnamese Dataset for Evaluating Machine Reading Comprehension",
    author = "Van Nguyen, Kiet  and
      Nguyen, Duc-Vu  and
      Gia-Tuan Nguyen, Anh  and
      Nguyen, Ngan Luu-Thuy",
    editor = "Scott, Donia  and
      Bel, Nuria  and
      Zong, Chengqing",
    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2020.coling-main.233/",
    doi = "10.18653/v1/2020.coling-main.233",
    pages = "2595--2605"
}

@inproceedings{le-etal-2022-vimqa,
    title = "{VIMQA}: A {V}ietnamese Dataset for Advanced Reasoning and Explainable Multi-hop Question Answering",
    author = "Le, Nguyen-Khang  and
      Nguyen, Dieu-Hien  and
      Le, Tung  and
      Nguyen, Minh",
    editor = "Calzolari, Nicoletta  and
      B{\'e}chet, Fr{\'e}d{\'e}ric  and
      Blache, Philippe  and
      Choukri, Khalid  and
      Cieri, Christopher  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Isahara, Hitoshi  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, H{\'e}l{\`e}ne  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.lrec-1.700/",
    pages = "6521--6529"
}

@inproceedings{ngo-etal-2024-vlogqa,
    title = "{V}log{QA}: Task, Dataset, and Baseline Models for {V}ietnamese Spoken-Based Machine Reading Comprehension",
    author = "Ngo, Thinh  and
      Dang, Khoa  and
      Luu, Son  and
      Nguyen, Kiet  and
      Nguyen, Ngan Luu-Thuy",
    editor = "Graham, Yvette  and
      Purver, Matthew",
    booktitle = "Proceedings of the 18th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = mar,
    year = "2024",
    address = "St. Julian{'}s, Malta",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.eacl-long.79/",
    doi = "10.18653/v1/2024.eacl-long.79",
    pages = "1310--1324"
}

@inproceedings{do-etal-2023-machine,
    title = "Machine Reading Comprehension for {V}ietnamese Customer Reviews: Task, Corpus and Baseline Models",
    author = "Do, Tinh Pham Phuc  and
      Cao, Ngoc Dinh Duy  and
      Nguyen, Nhan Thanh  and
      Huynh, Tin Van  and
      Nguyen, Kiet Van",
    editor = "Huang, Chu-Ren  and
      Harada, Yasunari  and
      Kim, Jong-Bok  and
      Chen, Si  and
      Hsu, Yu-Yin  and
      Chersoni, Emmanuele  and
      A, Pranav  and
      Zeng, Winnie Huiheng  and
      Peng, Bo  and
      Li, Yuxi  and
      Li, Junlin",
    booktitle = "Proceedings of the 37th Pacific {A}sia Conference on Language, Information and Computation",
    month = dec,
    year = "2023",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.paclic-1.3/",
    pages = "24--35"
}

@misc{do2024r2gqaretrieverreadergeneratorquestionanswering,
      title={R2GQA: Retriever-Reader-Generator Question Answering System to Support Students Understanding Legal Regulations in Higher Education}, 
      author={Phuc-Tinh Pham Do and Duy-Ngoc Dinh Cao and Khanh Quoc Tran and Kiet Van Nguyen},
      year={2024},
      eprint={2409.02840},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2409.02840}, 
}

@misc{smart2026multiwikiqareadingcomprehensionbenchmark,
      title={MultiWikiQA: A Reading Comprehension Benchmark in 300+ Languages}, 
      author={Dan Saattrup Smart},
      year={2026},
      eprint={2509.04111},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2509.04111}, 
}

@inproceedings{tran-etal-2024-vimedaqa,
    title = "{V}i{M}ed{AQA}: A {V}ietnamese Medical Abstractive Question-Answering Dataset and Findings of Large Language Model",
    author = "Tran, Minh-Nam  and
      Nguyen, Phu-Vinh  and
      Nguyen, Long  and
      Dinh, Dien",
    editor = "Fu, Xiyan  and
      Fleisig, Eve",
    booktitle = "Proceedings of the 62nd Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 4: Student Research Workshop)",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.acl-srw.31/",
    doi = "10.18653/v1/2024.acl-srw.31",
    pages = "252--260",
    ISBN = "979-8-89176-097-4"
}

@inproceedings{thai-etal-2022-uit,
    title = "{UIT}-{V}i{C}o{V}19{QA}: A Dataset for {COVID}-19 Community-based Question Answering on {V}ietnamese Language",
    author = "Thai, Triet  and
      Thao-Ha, Ngan Chu  and
      Vo, Anh  and
      Luu, Son",
    editor = "Dita, Shirley  and
      Trillanes, Arlene  and
      Lucas, Rochelle Irene",
    booktitle = "Proceedings of the 36th Pacific {A}sia Conference on Language, Information and Computation",
    month = oct,
    year = "2022",
    address = "Manila, Philippines",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.paclic-1.88/",
    pages = "801--810"
}

@inproceedings{csconda,
  title     = {A Benchmark Dataset and Evaluation Framework for Vietnamese Large Language Models in Customer Support},
  author    = {Nguyen, Long S. T. and Hua, Truong P. and Nguyen, Thanh M. and Pham, Toan Q. and Ngo, Nam K. and Nguyen, An X. and Pham, Nghi D. M. and Nguyen, Nghia H. and Quan, Tho T.},
  editor    = {Nguyen, Ngoc Thanh and Dinh Duc Anh, Vu and Kozierkiewicz, Adrianna and Nguyen Van, Sinh and Nunez, Manuel and Treur, Jan and Vossen, Gottfried},
  booktitle = {Advances in Computational Collective Intelligence},
  year      = {2026},
  publisher = {Springer Nature Switzerland},
  address   = {Cham},
  pages     = {481--496},
  isbn      = {978-3-032-10202-7}
}

@inproceedings{vire,
    title = "Which Works Best for {V}ietnamese? {A} Practical Study of Information Retrieval Methods across Domains",
    author = "Nguyen, Long S. T.  and
      Quan, Tho T.",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EACL} 2026",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.findings-eacl.110/",
    doi = "10.18653/v1/2026.findings-eacl.110",
    pages = "2098--2119",
    ISBN = "979-8-89176-386-9"
}

@inproceedings{tran2025vifactcheck,
  title     = {ViFactCheck: A New Benchmark Dataset and Methods for Multi-Domain News Fact-Checking in Vietnamese},
  author    = {Tran, Thai Hoa and Tran, Quang Duy and Tran, Khanh Quoc and Nguyen, Kiet Van},
  booktitle = {Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25)},
  pages     = {308--316},
  year      = {2025},
  publisher = {AAAI Press}
}

@inproceedings{le-etal-2026-viwikifc,
    title = "{V}i{W}iki{FC}: Fact-Checking for {V}ietnamese {W}ikipedia-Based Textual Knowledge Source",
    author = "Le, Hung Tuan  and
      To, Long Truong  and
      Nguyen, Manh Trong  and
      Nguyen, Kiet Van",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://aclanthology.org/2026.lrec-1.869/",
    doi = "10.63317/5ew98tfds6jc",
    pages = "11125--11140"
}

@InProceedings{large-vi-legal-queries,
author="Son, Pham Tien and Hieu, Nguyen Doan and An, Nguyen Dai and Sang, Dinh Viet",
editor="Buntine, Wray and Fjeld, Morten and Tran, Truyen and Tran, Minh-Triet and Huynh Thi Thanh, Binh and Miyoshi, Takumi",
title="Improving Vietnamese Legal Document Retrieval Using Synthetic Data",
booktitle="Information and Communication Technology",
year="2025",
publisher="Springer Nature Singapore",
address="Singapore",
pages="378--393",
isbn="978-981-96-4291-5"
}

@inproceedings{gn-trvn,
  abstract = {Information retrieval often comes in plain text, lacking semi-structured text such as HTML and markdown, retrieving data that contains rich format such as table became non-trivial. In this paper, we tackle this challenge by introducing a new dataset, GreenNode Table Retrieval VN (GN-TRVN), which is collected from a massive corpus, a wide range of topics, and a longer context compared to ViQuAD2.0. To evaluate the effectiveness of our proposed dataset, we introduce two versions, M3-GN-VN and M3-GN-VN-Mixed, by fine-tuning the M3-Embedding model on this dataset. Experimental results show that our models consistently outperform the baselines, including the base model, across most evaluation criteria on various datasets such as VieQuADRetrieval, ZacLegalTextRetrieval, and GN-TRVN. In general, we release a more comprehensive dataset and two model versions that improve response performance for Vietnamese Markdown Table Retrieval.},
  address = {Singapore},
  author = {Pham, Bao Loc
and Hoang, Quoc Viet
and Luu, Quy Tung
and Vo, Trong Thu},
  booktitle = {Proceedings of the Fifth International Conference on Intelligent Systems and Networks},
  isbn = {978-981-95-1746-6},
  pages = {153--163},
  publisher = {Springer Nature Singapore},
  title = {GN-TRVN: A Benchmark for Vietnamese Table Markdown Retrieval Task},
  year = {2026},
}

@misc{vnmteb,
      title={VN-MTEB: Vietnamese Massive Text Embedding Benchmark}, 
      author={Loc Pham and Tung Luu and Thu Vo and Minh Nguyen and Viet Hoang},
      year={2025},
      eprint={2507.21500},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2507.21500}, 
}

No verified citation was found for: isedsc2024, zalo_legal_triplets, zalo_legal, vietnamese_law_hn_mined.

Limitations and licenses

Each source keeps its own license (column above); this collection is license: other. Sources that are non-commercial or have no stated license: vinli, viquad2, vimqa, vire4mrc, virhe4qa, multi_wiki_qa, vimedaqa, vihealthqa, vicov19qa, csconda, isedsc2024, zalo_legal_triplets, vietnamese_law_hn_mined. Check the original license before any use beyond research. Q&A sources crawled from the web had person names masked with a Vietnamese NER model and phone/ID/account numbers masked by regex (<name>, <phone>, …).