QuangDuy/supervised_data-hn-candidates

HUIT-Embedding — hard-negative candidates (Vietnamese)

Top-200 retrieval candidates for every query of QuangDuy/supervised_data, the shared base of the mined variants (-hn-percpos, -hn-rankwindow, -hn-rerank-denoise). Generated on 2026-10-25. mMARCO is not here: its candidates come from hotchpotch/mmarco-hard-negatives-reranker-score.

How the candidates were made

• Retriever: intfloat/multilingual-e5-large (paper), chosen on our data against bge-m3, SEA-LION-E5-Embedding-600M and SEA-LION-ModernBERT-Embedding-600M; 512 tokens, query: / passage: prefixes.
• Corpus per domain (documents-<group>): every positive and provided negative of the group's sources (NLI also includes the premises; tables add the GreenNode table corpus without test-only tables), deduplicated, evaluation overlaps removed. doc_id = first 8 bytes of MD5 of the normalized text (signed).
• Exact inner-product search; known positives and the query's own text are removed from the list.

Columns

Column	Meaning
query_id	Joins queries-<source>
candidate_ids, candidate_scores	200 candidates, best first (-1 / NaN padding)
positive_ids, positive_scores	Known positives and their scores
positive_ranks, best_positive_rank	Rank of each positive among all documents (1 = first)

Usage at training time

These candidates also serve methods that act during training: SimANS samples negatives with probability ∝ exp(-a (s⁻ - s⁺ - b)²) using candidate_scores, and Qwen3-Embedding masks in-batch negatives scoring above the positive plus a margin.

from datasets import load_dataset

cand = load_dataset("QuangDuy/supervised_data-hn-candidates", "vinli", split="train")
queries = load_dataset("QuangDuy/supervised_data-hn-candidates", "queries-vinli", split="train")
docs = load_dataset("QuangDuy/supervised_data-hn-candidates", "documents-nli", split="train")

Retrieval quality

Share of queries whose best positive is ranked within k, over the full domain corpus.

Source	Queries	Positive rank 1	≤ 10	≤ 50	≤ 200
csconda	19	31.6%	73.7%	84.2%	89.5%
isedsc2024	7,944	91.0%	97.1%	98.6%	99.3%
large_vi_legal_queries	494,312	31.4%	71.4%	88.6%	95.8%
multi_wiki_qa	4,932	88.9%	96.6%	98.4%	99.4%
table_markdown_retrieval	125,830	37.5%	58.1%	71.4%	82.4%
vianli	1,606	35.7%	82.8%	91.7%	95.8%
vicov19qa	2,911	40.1%	65.2%	78.9%	88.6%
vietnamese_law_hn_mined	327,190	38.2%	79.6%	93.4%	97.6%
vifactcheck	1,595	91.5%	99.1%	99.7%	99.9%
vihealthqa	6,582	42.0%	68.0%	80.8%	88.5%
vimedaqa	31,437	61.3%	84.5%	91.9%	96.4%
vimqa	7,158	91.2%	99.7%	100.0%	100.0%
vinli	2,107	76.3%	98.4%	99.4%	99.7%
vinli_simcse_v2	268,871	39.8%	58.4%	70.5%	80.8%
vire4mrc	2,611	9.8%	25.2%	47.2%	79.1%
virhe4qa	75	90.7%	100.0%	100.0%	100.0%
viwikifc	1,802	97.6%	99.6%	99.9%	99.9%
vlogqa	3,839	24.6%	50.0%	68.6%	85.1%

Citations

@misc{wang2024multilinguale5textembeddings,
      title={Multilingual E5 Text Embeddings: A Technical Report},
      author={Liang Wang and Nan Yang and Xiaolong Huang and Linjun Yang and Rangan Majumder and Furu Wei},
      year={2024},
      eprint={2402.05672},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.05672},
}

@misc{zhou2022simanssimpleambiguousnegatives,
      title={SimANS: Simple Ambiguous Negatives Sampling for Dense Text Retrieval},
      author={Kun Zhou and Yeyun Gong and Xiao Liu and Wayne Xin Zhao and Yelong Shen and Anlei Dong and Jingwen Lu and Rangan Majumder and Ji-Rong Wen and Nan Duan and Weizhu Chen},
      year={2022},
      eprint={2210.11773},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2210.11773},
}

@misc{zhang2025qwen3embeddingadvancingtext,
      title={Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models},
      author={Yanzhao Zhang and Mingxin Li and Dingkun Long and Xin Zhang and Huan Lin and Baosong Yang and Pengjun Xie and An Yang and Dayiheng Liu and Junyang Lin and Fei Huang and Jingren Zhou},
      year={2025},
      eprint={2506.05176},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.05176},
}

@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{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"
}

@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{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},
}

@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{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{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{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{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{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"
}

@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"
}

@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}, 
}

@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{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"
}

No verified citation was found for: isedsc2024, 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: csconda, isedsc2024, multi_wiki_qa, vicov19qa, vietnamese_law_hn_mined, vihealthqa, vimedaqa, vimqa, vinli, vire4mrc, virhe4qa. 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>, …).