Elamur Research⌕
☰
home / papers / 2025 / MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs

MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs

Paper · 2025 · Zaid Alyafeai, Maged S. Al-shaibani and Bernard Ghanem

Summary

Datasets in NLP keep multiplying, but much of their descriptive information (license, size, links, domain, tasks) sits unstructured inside papers. Earlier catalogues such as Masader needed manual annotation, and older automatic extractors covered only a handful of fields. MOLE uses LLMs to read a whole paper, in LaTeX or PDF form, and fill in roughly 30 dataset attributes. A JSON schema drives the extraction. For each attribute it gives a question, the allowed options, explanations for unclear options, an output type, a validation group, and minimum and maximum answer lengths. A validation layer then repairs the model's answer by fixing types, snapping invalid options to the closest allowed one, checking length, and cleaning broken JSON. The authors also release a hand-annotated benchmark covering Arabic, English, French, Japanese, Russian and multilingual datasets. They test seven LLMs and vary context length, few-shot examples, input format and web browsing. Gemini 2.5 Pro performs best overall. The results suggest the task is largely automatable, although models still have trouble with strict constraints such as answer length.

Key points

  • The schema has 32 attributes for Arabic datasets and is adapted per language. For example, Dialect and Subset are dropped for monolingual non-Arabic sets, and Script options are language-specific.
  • The test set has 126 papers, 21 per category, plus 6 papers for validation, giving 7,518 attribute annotations in total. Agreement between the two annotators was 85.93%.
  • Every annotation also records whether the value actually appears in the paper. This separates facts that can be read from the text from facts that need browsing.
  • Scoring uses F1, with exact match or lenient set matching for lists (one mismatch tolerated). Here precision reflects how often a model hallucinates values that are not present.
  • The baselines are Random and Keyword. In the average across validation groups, Gemini 2.5 Pro reaches 76.40, GPT 4o 73.56 and Claude 3.5 Sonnet 72.18, against 48.91 for Keyword.

Interesting ideas

  • I1. Each slot is defined as a small contract: a question, a closed option list with glosses for unclear options, a type, and cardinality bounds. This turns free-form extraction into constrained filling that can be checked.
  • I2. Instead of discarding a malformed model output, a repair pass casts types, maps off-list answers to the nearest legal option, and fixes JSON with regex rules.
  • I3. Gold labels mark whether the answer is actually present in the source document. This lets evaluation separate reading ability from outside knowledge or lookup.
  • I4. Trivial baselines (random choice, keyword matching) set a floor, and precision is read as a direct measure of hallucination.
  • I5. A "Derived From" field records which seed datasets a resource was built from, which helps reveal contamination.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (frames): Frame slots from VerbNet roles could carry explicit type, allowed fillers and min/max counts, so an incomplete or overfilled frame is flagged in an explainable way.
  • I2 (learn): LLM teacher outputs could be normalized to valid UD relations or role labels before they enter silver data, with each repair logged so it stays traceable.
  • I3 (answer): QA on fables and school tests could tag each question as text-stated or requiring world knowledge, so failures are attributed to the reader or to the knowledge base.
  • I4 (learn): Each evaluation could include such a naive baseline as a negative control, and report invented content separately from missed content.
  • I5 (learn): Tracking the provenance of treebanks and silver corpora would help prevent train/test leakage when sources are mixed or converted between UD dialects.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓King Fahd University of Petroleum and MineralsDhahran · Saudi Arabia52 works · 4,666 citations

 Fields, topics and concepts

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksInformation Systems · 1,437 works

Cite

Cite as Zaid Alyafeai, Maged S. Al-shaibani and Bernard Ghanem. 2025. MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs. Findings of the Association for Computational Linguistics: EMNLP 2025.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2025.findings-emnlp.655

@inproceedings{alyafeai2025mole,
  title = {{MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs}},
  author = {Zaid Alyafeai, Maged S. Al-shaibani and Bernard Ghanem},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2025},
  year = {2025},
  doi = {10.18653/v1/2025.findings-emnlp.655},
  url = {https://doi.org/10.18653/v1/2025.findings-emnlp.655}
}

References

176 references, 51 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Muhammad Waqas Ahmad and Muhammad Tanvir Afzal. 2020. FLAG-PDFe: Features oriented metadata extraction framework for scientific publications. IEEE Access, 8:99458–99470. find
  2. Anna Aksenova, Ekaterina Gavrishina, Elisey Rykov, and Andrey Kutuzov. 2022. Rudsi: graph-based word sense induction dataset for russian. arXiv preprint arXiv: 2209.13750. ↗
  3. Rami Al-Rfou, Vivek Kulkarni, Bryan Perozzi, and Steven Skiena. 2014. Polyglot-ner: Massive multilingual named entity recognition. arXiv preprint arXiv: 1410.3791. ↗
  4. Nadège Alavoine, Gaëlle Laperriere, Christophe Servan, Sahar Ghannay, and Sophie Rosset. 2024. New semantic task for the french spoken language understanding media benchmark. arXiv preprint arXiv: 2403.19727. ↗
  5. Ahmed Ali, Peter Bell, James Glass, Yacine Messaoui, Hamdy Mubarak, Steve Renals, and Yifan Zhang. 2016. The mgb-2 challenge: Arabic multi-dialect broadcast media recognition. arXiv preprint arXiv: 1609.05625. ↗
  6. Ahmed Ali, Najim Dehak, Patrick Cardinal, Sameer Khurana, Sree Harsha Yella, James Glass, Peter Bell, and Steve Renals. 2015. Automatic dialect detection in arabic broadcast speech. arXiv preprint arXiv: 1509.06928. ↗
  7. Ahmed Ali, Stephan Vogel, and Steve Renals. 2017. Speech recognition challenge in the wild: Arabic mgb-3. arXiv preprint arXiv: 1709.07276. ↗
  8. Henk Alkemade, Steven Claeyssens, Giovanni Colavizza, Nuno Freire, Jörg Lehmann, Clemens Neudeker, Giulia Osti, and 1 others. 2023. Datasheets for digital cultural heritage datasets. Journal of open humanities data, 9(17):1–11. find
  9. Manel Aloui, Hasna Chouikhi, Ghaith Chaabane, Haithem Kchaou, and Chehir Dhaouadi. 2024. 101 billion arabic words dataset. arXiv preprint arXiv: 2405.01590. ↗
  10. Ali Alshehri, El Moatez Billah Nagoudi, and Muhammad Abdul-Mageed. 2020. Understanding and detecting dangerous speech in social media. arXiv preprint arXiv: 2005.06608. ↗
  11. Yousef Altaher, Ali Fadel, Mazen Alotaibi, Mazen Alyazidi, Mishari Al-Mutairi, Mutlaq Aldhbuiub, Abdulrahman Mosaibah, Abdelrahman Rezk, Abdulrazzaq Alhendi, Mazen Abo Shal, and 1 others. 2022. Masader plus: A new interface for exploring+ 500 arabic nlp datasets. arXiv preprint arXiv:2208.00932. ↗
  12. Sai Saketh Aluru, Binny Mathew, Punyajoy Saha, and Animesh Mukherjee. 2020. Deep learning models for multilingual hate speech detection. arXiv preprint arXiv: 2004.06465. ↗
  13. Zaid Alyafeai, Maged S. Al-shaibani, Mustafa Ghaleb, and Yousif Ahmed Al-Wajih. 2021a. Calliar: An online handwritten dataset for arabic calligraphy. arXiv preprint arXiv: 2106.10745. ↗
  14. Zaid Alyafeai, Khalid Almubarak, Ahmed Ashraf, Deema Alnuhait, Saied Alshahrani, Gubran A. Q. Abdulrahman, Gamil Ahmed, Qais Gawah, Zead Saleh, Mustafa Ghaleb, Yousef Ali, and Maged S. Al-Shaibani. 2024. Cidar: Culturally relevant instruction dataset for arabic. arXiv preprint arXiv: 2402.03177. ↗
  15. Zaid Alyafeai, Maraim Masoud, Mustafa Ghaleb, and Maged S Al-shaibani. 2021b. Masader: Metadata sourcing for arabic text and speech data resources. arXiv preprint arXiv:2110.06744. ↗
  16. Mohamed Seghir Hadj Ameur, Farid Meziane, and Ahmed Guessoum. 2019. Anetac: Arabic named entity transliteration and classification dataset. arXiv preprint arXiv: 1907.03110. ↗
  17. Dong An, Liangcai Gao, Zhuoren Jiang, Runtao Liu, and Zhi Tang. 2017. Citation metadata extraction via deep neural network-based segment sequence labeling. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, pages 1967–1970. Studying the history of the arabic language: Language technology and a large-scale historical corpus. arXiv preprint arXiv: 1809.03891. ↗
  18. Yonatan Belinkov, Alexander Magidow, Maxim Romanov, Avi Shmidman, and Moshe Koppel. 2016. Shamela: A large-scale historical arabic corpus. arXiv preprint arXiv: 1612.08989. ↗
  19. Abhyuday Bhartiya, Kartikeya Badola, and Mausam. 2021. Dis-rex: A multilingual dataset for distantly supervised relation extraction. arXiv preprint arXiv: 2104.08655. ↗
  20. Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, and Yejin Choi. 2019. Piqa: Reasoning about physical commonsense in natural language. arXiv preprint arXiv: 1911.11641. ↗
  21. Sergey Bondarkov, Victor Ledenev, and Dmitriy Skougarevskiy. 2025. Russian financial statements database: A firm-level collection of the universe of financial statements. arXiv preprint arXiv: 2501.05841. ↗
  22. Christine L Borgman. 2012. The conundrum of sharing research data. Journal of the American Society for Information Science and Technology, 63(6):1059– 1078. ↗
  23. Mikel Artetxe and Holger Schwenk. 2018. Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond. arXiv preprint arXiv: 1812.10464. ↗
  24. Zeyd Boukhers and Azeddine Bouabdallah. 2022. Vision and natural language for metadata extraction from scientific pdf documents: a multimodal approach. In Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries, pages 1–5. find
  25. Akari Asai, Jungo Kasai, Jonathan H. Clark, Kenton Lee, Eunsol Choi, and Hannaneh Hajishirzi. 2020. Xor qa: Cross-lingual open-retrieval question answering. arXiv preprint arXiv: 2010.11856. ↗
  26. Caroline Brun and Vassilina Nikoulina. 2024. French-toxicityprompts: a large benchmark for evaluating and mitigating toxicity in french texts. arXiv preprint arXiv: 2406.17566. ↗
  27. Christoph Auer, Maksym Lysak, Ahmed Nassar, Michele Dolfi, Nikolaos Livathinos, Panos Vagenas, Cesar Berrospi Ramis, Matteo Omenetti, Fabian Lindlbauer, Kasper Dinkla, and 1 others. 2024. Docling technical report. arXiv preprint arXiv:2408.09869. ↗
  28. Bradley Butcher, Michael O’Keefe, and James Titchener. 2025. Precise length control for large language models. Natural Language Processing Journal, page 100143. ↗
  29. Sophie Balech, Christophe Benavent, and Mihai Calciu. 2020. The first french covid19 lockdown twitter dataset. arXiv preprint arXiv: 2005.05075. ↗
  30. Lucas Bandarkar, Davis Liang, Benjamin Muller, Mikel Artetxe, Satya Narayan Shukla, Donald Husa, Naman Goyal, Abhinandan Krishnan, Luke Zettlemoyer, and Madian Khabsa. 2023. The belebele benchmark: a parallel reading comprehension dataset in 122 language variants. arXiv preprint arXiv: 2308.16884. ↗
  31. David Beauchemin, Julien Laumonier, Yvan Le Ster, and Marouane Yassine. 2022. "fijo": a french insurance soft skill detection dataset. arXiv preprint arXiv: 2204.05208. ↗
  32. Yonatan Belinkov, Alexander Magidow, Alberto Barrón-Cedeño, Avi Shmidman, and Maxim Romanov. 2018. find
  33. Mauro Cettolo. 2016. An arabic-hebrew parallel corpus of ted talks. arXiv preprint arXiv: 1610.00572. ↗
  34. Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. 2019. Boolq: Exploring the surprising difficulty of natural yes/no questions. arXiv preprint arXiv: 1905.10044. ↗
  35. Elizabeth Clark, Shruti Rijhwani, Sebastian Gehrmann, Joshua Maynez, Roee Aharoni, Vitaly Nikolaev, Thibault Sellam, Aditya Siddhant, Dipanjan Das, and Ankur P. Parikh. 2023. Seahorse: A multilingual, multifaceted dataset for summarization evaluation. arXiv preprint arXiv: 2305.13194. ↗
  36. Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021. Training verifiers to solve math word problems. arXiv preprint arXiv: 2110.14168. ↗
  37. Alexis Conneau, Guillaume Lample, Ruty Rinott, Adina Williams, Samuel R. Bowman, Holger Schwenk, and Veselin Stoyanov. 2018. Xnli: Evaluating cross-lingual sentence representations. arXiv preprint arXiv: 1809.05053. ↗
  38. Tiantian Fan, Junming Liu, Yeliang Qiu, Congfeng Jiang, Jilin Zhang, Wei Zhang, and Jian Wan. 2019. Parda: a dataset for scholarly pdf document metadata extraction evaluation. In Collaborative Computing: Networking, Applications and Worksharing: 14th EAI International Conference, CollaborateCom 2018, Shanghai, China, December 1-3, 2018, Proceedings 14, pages 417–431. Springer. find
  39. Charlotte J Connolly, Daniel M Hueholt, and Melissa A Burt. 2025. Datasheets for earth science datasets. Bulletin of the American Meteorological Society. ↗
  40. Chayma Fourati, Abir Messaoudi, and Hatem Haddad. 2020. Tunizi: a tunisian arabizi sentiment analysis dataset. arXiv preprint arXiv: 2004.14303. ↗
  41. Alexandru Constantin, Steve Pettifer, and Andrei Voronkov. 2013. PDFX: Fully-automated PDF-to-XML conversion of scientific literature. In Proceedings of the 2013 ACM symposium on Document engineering, pages 177–180. find
  42. Simon Gabay, Pedro Ortiz Suarez, Alexandre Bartz, Alix Chagué, Rachel Bawden, Philippe Gambette, and Benoît Sagot. 2022. From freem to d’alembert: a large corpus and a language model for early modern french. arXiv preprint arXiv: 2202.09452. ↗
  43. Isaac G Councill, C Lee Giles, and Min-Yen Kan. 2008. ParsCit: An open-source CRF reference string parsing package. In Proceedings of LREC, volume 8, pages 661–667. find
  44. Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford. 2021. Datasheets for datasets. Communications of the ACM, 64(12):86– 92. ↗
  45. Dorottya Demszky, Dana Movshovitz-Attias, Jeongwoo Ko, Alan Cowen, Gaurav Nemade, and Sujith Ravi. 2020. Goemotions: A dataset of fine-grained emotions. arXiv preprint arXiv: 2005.00547. ↗
  46. Martin d’Hoffschmidt, Wacim Belblidia, Tom Brendlé, Quentin Heinrich, and Maxime Vidal. 2020. Fquad: French question answering dataset. arXiv preprint arXiv: 2002.06071. ↗
  47. Shizhe Diao, Yu Yang, Yonggan Fu, Xin Dong, Dan Su, Markus Kliegl, Zijia Chen, Peter Belcak, Yoshi Suhara, Hongxu Yin, Mostofa Patwary, Yingyan, Lin, Jan Kautz, and Pavlo Molchanov. 2025. Climb: Clustering-based iterative data mixture bootstrapping for language model pre-training. arXiv preprint arXiv: 2504.13161. ↗
  48. Shahd Dibas, Christian Khairallah, Nizar Habash, Omar Fayez Sadi, Tariq Sairafy, Karmel Sarabta, and Abrar Ardah. 2022. Maknuune: A large open palestinian arabic lexicon. arXiv preprint arXiv: 2210.12985. ↗
  49. Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, and Noah A Smith. 2019. Show your work: Improved reporting of experimental results. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 2185–2194. ↗
  50. Pavel Efimov, Andrey Chertok, Leonid Boytsov, and Pavel Braslavski. 2019. Sberquad – russian reading comprehension dataset: Description and analysis. arXiv preprint arXiv: 1912.09723. ↗
  51. Ronen Eldan and Yuanzhi Li. 2023. Tinystories: How small can language models be and still speak coherent english? arXiv preprint arXiv: 2305.07759. ↗
  52. Joan Giner-Miguelez, Abel Gómez, and Jordi Cabot. 2022. Describeml: a tool for describing machine learning datasets. In Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, pages 22–26. find
  53. Taisia Glushkova, Alexey Machnev, Alena Fenogenova, Tatiana Shavrina, Ekaterina Artemova, and Dmitry I. Ignatov. 2020. Danetqa: a yes/no question answering dataset for the russian language. arXiv preprint arXiv: 2010.02605. ↗
  54. Rahul Goel, Waleed Ammar, Aditya Gupta, Siddharth Vashishtha, Motoki Sano, Faiz Surani, Max Chang, HyunJeong Choe, David Greene, Kyle He, Rattima Nitisaroj, Anna Trukhina, Shachi Paul, Pararth Shah, Rushin Shah, and Zhou Yu. 2023. Presto: A multilingual dataset for parsing realistic task-oriented dialogs. arXiv preprint arXiv: 2303.08954. ↗
  55. Naman Goyal, Cynthia Gao, Vishrav Chaudhary, Peng-Jen Chen, Guillaume Wenzek, Da Ju, Sanjana Krishnan, Marc’Aurelio Ranzato, Francisco Guzman, and Angela Fan. 2021. The flores-101 evaluation benchmark for low-resource and multilingual machine translation. arXiv preprint arXiv: 2106.03193. ↗
  56. Michael Granitzer, Maya Hristakeva, Rhiannon Knight, Kris Jack, and Roman Kern. 2012. A comparison of layout based bibliographic metadata extraction techniques. In Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, pages 1–8. find
  57. Veronika Grigoreva, Anastasiia Ivanova, Ilseyar Alimova, and Ekaterina Artemova. 2024. Rubia: A russian language bias detection dataset. arXiv preprint arXiv: 2403.17553. ↗
  58. Ilya Gusev. 2020. Dataset for automatic summarization of russian news. arXiv preprint arXiv: 2006.11063. ↗
  59. Ilya Gusev and Alexey Tikhonov. 2021. Headlinecause: A dataset of news headlines for detecting causalities. arXiv preprint arXiv: 2108.12626. ↗
  60. Julien Hauret, Malo Olivier, Thomas Joubaud, Christophe Langrenne, Sarah Poirée, Véronique Zimpfer, and Éric Bavu. 2024. Vibravox: A dataset of french speech captured with body-conduction audio sensors. arXiv preprint arXiv: 2407.11828. ↗
  61. Ahmed Heakl, Youssef Mohamed, and Ahmed B. Zaky. 2024. Araspider: Democratizing arabic-to-sql. arXiv preprint arXiv: 2402.07448. ↗
  62. Quentin Heinrich, Gautier Viaud, and Wacim Belblidia. 2021. Fquad2.0: French question answering and knowing that you know nothing. arXiv preprint arXiv: 2109.13209. ↗
  63. Ilana Heintz. 2023. Datasheets for energy datasets: An ethically-minded approach to documentation. In Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, pages 40–51. find
  64. Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020. Measuring massive multitask language understanding. arXiv preprint arXiv: 2009.03300. ↗
  65. Kushan Hewapathirana, Nisansa de Silva, and C. D. Athuraliya. 2024. M2ds: Multilingual dataset for multi-document summarisation. arXiv preprint arXiv: 2407.12336. ↗
  66. Masanori Hirano, Masahiro Suzuki, and Hiroki Sakaji. 2023. llm-japanese-dataset v0: Construction of japanese chat dataset for large language models and its methodology. arXiv preprint arXiv: 2305.12720. ↗
  67. Huang Huang, Fei Yu, Jianqing Zhu, Xuening Sun, Hao Cheng, Dingjie Song, Zhihong Chen, Abdulmohsen Alharthi, Bang An, Juncai He, Ziche Liu, Zhiyi Zhang, Junying Chen, Jianquan Li, Benyou Wang, Lian Zhang, Ruoyu Sun, Xiang Wan, Haizhou Li, and Jinchao Xu. 2023. Acegpt, localizing large language models in arabic. arXiv preprint arXiv: 2309.12053. ↗
  68. Chia-Chien Hung, Anne Lauscher, Ivan Vulić, Simone Paolo Ponzetto, and Goran Glavaš. 2022. Multi2woz: A robust multilingual dataset and conversational pretraining for task-oriented dialog. arXiv preprint arXiv: 2205.10400. ↗
  69. Julie Hunter, Jérôme Louradour, Virgile Rennard, Ismaïl Harrando, Guokan Shang, and Jean-Pierre Lorré. 2023. The claire french dialogue dataset. arXiv preprint arXiv: 2311.16840. ↗
  70. Benjamin Icard, François Maine, Morgane Casanova, Géraud Faye, Julien Chanson, Guillaume Gadek, Ghislain Atemezing, François Bancilhon, and Paul Égré. 2024. A multi-label dataset of french fake news: Human and machine insights. arXiv preprint arXiv: 2403.16099. ↗
  71. Yusuke Ide, Masato Mita, Adam Nohejl, Hiroki Ouchi, and Taro Watanabe. 2023. Japanese lexical complexity for non-native readers: A new dataset. arXiv preprint arXiv: 2306.17399. ↗
  72. Mandar Joshi, Eunsol Choi, Daniel S. Weld, and Luke Zettlemoyer. 2017. Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension. arXiv preprint arXiv: 1705.03551. ↗
  73. Fanny Jourdan, Yannick Chevalier, and Cécile Favre. 2025. Fairtranslate: An english-french dataset for gender bias evaluation in machine translation by overcoming gender binarity. arXiv preprint arXiv: 2504.15941. ↗
  74. Alexander Kapitanov, Karina Kvanchiani, Alexander Nagaev, and Elizaveta Petrova. 2023. Slovo: Russian sign language dataset. arXiv preprint arXiv: 2305.14527. ↗
  75. Nikolay Karpov, Alexander Denisenko, and Fedor Minkin. 2021. Golos: Russian dataset for speech research. arXiv preprint arXiv: 2106.10161. ↗
  76. Rachel Keraron, Guillaume Lancrenon, Mathilde Bras, Frédéric Allary, Gilles Moyse, Thomas Scialom, Edmundo-Pavel Soriano-Morales, and Jacopo Staiano. 2020. Project piaf: Building a native french question-answering dataset. arXiv preprint arXiv: 2007.00968. ↗
  77. Phillip Keung, Yichao Lu, György Szarvas, and Noah A. Smith. 2020. The multilingual amazon reviews corpus. arXiv preprint arXiv: 2010.02573. ↗
  78. Mohammed Khalil and Mohammed Sabry. 2024. Athar: A high-quality and diverse dataset for classical arabic to english translation. arXiv preprint arXiv: 2407.19835. ↗
  79. Ali Can Kocabiyikoglu, François Portet, Prudence Gibert, Hervé Blanchon, Jean-Marc Babouchkine, and Gaëtan Gavazzi. 2022. A spoken drug prescription dataset in french for spoken language understanding. arXiv preprint arXiv: 2207.08292. ↗
  80. Hyesoo Kong, Hwamook Yoon, Jaewook Seol, Mihwan Hyun, Hyejin Lee, Soonyoung Kim, and Wonjun Choi. 2022. Annotated open corpus construction and bert-based approach for automatic metadata extraction from korean academic papers. IEEE Access, 11:825–838. ↗
  81. Vladislav Korablinov and Pavel Braslavski. 2020. Rubq: A russian dataset for question answering over wikidata. arXiv preprint arXiv: 2005.10659. ↗
  82. Fajri Koto, Haonan Li, Sara Shatnawi, Jad Doughman, Abdelrahman Boda Sadallah, Aisha Alraeesi, Khalid Almubarak, Zaid Alyafeai, Neha Sengupta, Shady Shehata, Nizar Habash, Preslav Nakov, and Timothy Baldwin. 2024. Arabicmmlu: Assessing massive multitask language understanding in arabic. arXiv preprint arXiv: 2402.12840. ↗
  83. Abdullatif Köksal and Arzucan Özgür. 2020. The relx dataset and matching the multilingual blanks for cross-lingual relation classification. arXiv preprint arXiv: 2010.09381. ↗
  84. Yanis Labrak, Adrien Bazoge, Richard Dufour, Mickael Rouvier, Emmanuel Morin, Béatrice Daille, and Pierre-Antoine Gourraud. 2023. Frenchmedmcqa: A french multiple-choice question answering dataset for medical domain. arXiv preprint arXiv: 2304.04280. ↗
  85. Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy. 2017. Race: Large-scale reading comprehension dataset from examinations. arXiv preprint arXiv: 1704.04683. ↗
  86. Antoine Lefebvre-Brossard, Stephane Gazaille, and Michel C. Desmarais. 2023. Alloprof: a new french question-answer education dataset and its use in an information retrieval case study. arXiv preprint arXiv: 2302.07738. ↗
  87. Thibaud Leteno, Irina Proskurina, Antoine Gourru, Julien Velcin, Charlotte Laclau, Guillaume Metzler, and Christophe Gravier. 2025. Histoires morales: A french dataset for assessing moral alignment. arXiv preprint arXiv: 2501.17117. ↗
  88. Dalian, China, November 8–12, 2017, Proceedings 6, pages 305–317. Springer. find
  89. Antoine Louis and Gerasimos Spanakis. 2021. A statutory article retrieval dataset in french. arXiv preprint arXiv: 2108.11792. ↗
  90. Natalia Loukachevitch, Ekaterina Artemova, Tatiana Batura, Pavel Braslavski, Ilia Denisov, Vladimir Ivanov, Suresh Manandhar, Alexander Pugachev, and Elena Tutubalina. 2021. Nerel: A russian dataset with nested named entities, relations and events. arXiv preprint arXiv: 2108.13112. ↗
  91. Michael J. Lyons. 2021. "excavating ai" re-excavated: Debunking a fallacious account of the jaffe dataset. arXiv preprint arXiv: 2107.13998. ↗
  92. Supriya V Mahadevkar, Shruti Patil, Ketan Kotecha, Lim Way Soong, and Tanupriya Choudhury. 2024. Exploring ai-driven approaches for unstructured document analysis and future horizons. Journal of Big Data, 11(1):92. ↗
  93. Igor Markov, Sergey Nesteruk, Andrey Kuznetsov, and Denis Dimitrov. 2023. Rustitw: Russian language text dataset for visual text in-the-wild recognition. arXiv preprint arXiv: 2303.16531. ↗
  94. Patrick Lewis, Barlas Oğuz, Ruty Rinott, Sebastian Riedel, and Holger Schwenk. 2019. Mlqa: Evaluating cross-lingual extractive question answering. arXiv preprint arXiv: 1910.07475. ↗
  95. Norman Meuschke, Apurva Jagdale, Timo Spinde, Jelena Mitrović, and Bela Gipp. 2023. A benchmark of pdf information extraction tools using a multi-task and multi-domain evaluation framework for academic documents. In International Conference on Information, pages 383–405. Springer. find
  96. Haoran Li, Abhinav Arora, Shuohui Chen, Anchit Gupta, Sonal Gupta, and Yashar Mehdad. 2020a. Mtop: A comprehensive multilingual task-oriented semantic parsing benchmark. arXiv preprint arXiv: 2008.09335. ↗
  97. Paul Michel and Graham Neubig. 2018. Mtnt: A testbed for machine translation of noisy text. arXiv preprint arXiv: 1809.00388. ↗
  98. Minghao Li, Yiheng Xu, Lei Cui, Shaohan Huang, Furu Wei, Zhoujun Li, and Ming Zhou. 2020b. Docbank: A benchmark dataset for document layout analysis. arXiv preprint arXiv:2006.01038. ↗
  99. Yinghao Li, Rampi Ramprasad, and Chao Zhang. 2024. A simple but effective approach to improve structured language model output for information extraction. arXiv preprint arXiv:2402.13364. ↗
  100. Michael Xieyang Liu, Frederick Liu, Alexander J Fiannaca, Terry Koo, Lucas Dixon, Michael Terry, and Carrie J Cai. 2024. " we need structured output": Towards user-centered constraints on large language model output. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, pages 1–9. find
  101. Runtao Liu, Liangcai Gao, Dong An, Zhuoren Jiang, and Zhi Tang. 2018. Automatic document metadata extraction based on deep networks. In Natural Language Processing and Chinese Computing: 6th CCF International Conference, NLPCC 2017, Vladislav Mikhailov, Tatiana Shamardina, Max Ryabinin, Alena Pestova, Ivan Smurov, and Ekaterina Artemova. 2022. Rucola: Russian corpus of linguistic acceptability. arXiv preprint arXiv: 2210.12814. ↗
  102. Elena Mikhalkova. 2021. A russian jeopardy! data set for question-answering systems. arXiv preprint arXiv: 2112.02325. ↗
  103. Mehrad Moradshahi, Tianhao Shen, Kalika Bali, Monojit Choudhury, Gaël de Chalendar, Anmol Goel, Sungkyun Kim, Prashant Kodali, Ponnurangam Kumaraguru, Nasredine Semmar, Sina J. Semnani, Jiwon Seo, Vivek Seshadri, Manish Shrivastava, Michael Sun, Aditya Yadavalli, Chaobin You, Deyi Xiong, and Monica S. Lam. 2023. X-risawoz: High-quality end-to-end multilingual dialogue datasets and few-shot agents. arXiv preprint arXiv: 2306.17674. ↗
  104. Makoto Morishita, Jun Suzuki, and Masaaki Nagata. 2019. Jparacrawl: A large scale web-based english-japanese parallel corpus. arXiv preprint arXiv: 1911.10668. ↗
  105. Hamdy Mubarak, Sabit Hassan, and Shammur Absar Chowdhury. 2022. Emojis as anchors to detect arabic offensive language and hate speech. arXiv preprint arXiv: 2201.06723. ↗
  106. Bowen Peng, Sami Xie, Hao Yao, Karthik Gu, Skyler Reynolds, Tri Shen, and Denny Zhou. 2023. Yarn: Efficient context window extension of large language models. arXiv preprint arXiv:2309.00071. ↗
  107. Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel Candès, and Tatsunori Hashimoto. 2025. s1: Simple test-time scaling. arXiv preprint arXiv:2501.19393. ↗
  108. Long Phan, Alice Gatti, Ziwen Han, Nathaniel Li, Josephina Hu, Hugh Zhang, Chen Bo Calvin Zhang, Mohamed Shaaban, John Ling, Sean Shi, Michael Choi, Anish Agrawal, Arnav Chopra, Adam Khoja, Ryan Kim, Richard Ren, Jason Hausenloy, Oliver Zhang, Mantas Mazeika, and 1090 others. 2025. Humanity’s last exam. arXiv preprint arXiv: 2501.14249. — Humanity's Last Exam ↗
  109. Taichi Murayama, Shohei Hisada, Makoto Uehara, Shoko Wakamiya, and Eiji Aramaki. 2022. Annotation-scheme reconstruction for "fake news" and japanese fake news dataset. arXiv preprint arXiv: 2204.02718. ↗
  110. Mahmoud Nabil, Mohamed Aly, and Amir Atiya. 2014. Labr: A large scale arabic sentiment analysis benchmark. arXiv preprint arXiv: 1411.6718. ↗
  111. Atsumoto Ohashi, Ryu Hirai, Shinya Iizuka, and Ryuichiro Higashinaka. 2024. Jmultiwoz: A large-scale japanese multi-domain task-oriented dialogue dataset. arXiv preprint arXiv: 2403.17319. ↗
  112. Naoaki Okazaki, Kakeru Hattori, Hirai Shota, Hiroki Iida, Masanari Ohi, Kazuki Fujii, Taishi Nakamura, Mengsay Loem, Rio Yokota, and Sakae Mizuki. 2024. Building a large japanese web corpus for large language models. arXiv preprint arXiv: 2404.17733. ↗
  113. Eri Onami, Shuhei Kurita, Taiki Miyanishi, and Taro Watanabe. 2024. Jdocqa: Japanese document question answering dataset for generative language models. arXiv preprint arXiv: 2403.19454. ↗
  114. Dina Pisarevskaya and Tatiana Shavrina. 2022. Wikiomnia: generative qa corpus on the whole russian wikipedia. arXiv preprint arXiv: 2204.08009. ↗
  115. Raffaele Pizzolante, Arcangelo Castiglione, and Francesco Palmieri. 2024. Unlocking insights: An extensible framework for automated metadata extraction from online documents. In 2024 IEEE 23rd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pages 1512–1521. IEEE. find
  116. Edoardo Maria Ponti, Goran Glavaš, Olga Majewska, Qianchu Liu, Ivan Vulić, and Anna Korhonen. 2020. Xcopa: A multilingual dataset for causal commonsense reasoning. arXiv preprint arXiv: 2005.00333. ↗
  117. Reid Pryzant, Yongjoo Chung, Dan Jurafsky, and Denny Britz. 2017. Jesc: Japanese-english subtitle corpus. arXiv preprint arXiv: 1710.10639. report. ↗
  118. Alexander Pugachev, Alena Fenogenova, Vladislav Mikhailov, and Ekaterina Artemova. 2025. Repa: Russian error types annotation for evaluating text generation and judgment capabilities. arXiv preprint arXiv: 2503.13102. ↗
  119. Hiroki Ouchi, Hiroyuki Shindo, Shoko Wakamiya, Yuki Matsuda, Naoya Inoue, Shohei Higashiyama, Satoshi Nakamura, and Taro Watanabe. 2023. Arukikata travelogue dataset. arXiv preprint arXiv: 2305.11444. ↗
  120. Mohadese Rahnama, Seyed Mohammad Hossein Hasheminejad, and Jalal A Nasiri. 2020. Automatic metadata extraction from iranian theses and dissertations. In 2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), pages 1–5. IEEE. find
  121. Aissam Outchakoucht and Hamza Es-Samaali. 2021. Moroccan dialect -darija- open dataset. arXiv preprint arXiv: 2103.09687. ↗
  122. Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018. Know what you don’t know: Unanswerable questions for squad. arXiv preprint arXiv: 1806.03822. ↗
  123. Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Quan Ngoc Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, and Raquel Fernández. 2016. The lambada dataset: Word prediction requiring a broad discourse context. arXiv preprint arXiv: 1606.06031. ↗
  124. Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016. Squad: 100,000+ questions for machine comprehension of text. arXiv preprint arXiv: 1606.05250. ↗
  125. OpenAI. 2023. arXiv:2303.08774. GPT-4 technical Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Alessandro Cappelli, Hamza Alobeidli, Baptiste Pannier, Ebtesam Almazrouei, and Julien Launay. 2023. The refinedweb dataset for falcon llm: Outperforming curated corpora with web data, and web data only. arXiv preprint arXiv: 2306.01116. ↗
  126. David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R. Bowman. 2023. Gpqa: A graduate-level google-proof q&a benchmark. arXiv preprint arXiv: 2311.12022. ↗
  127. Virgile Rennard, Guokan Shang, Damien Grari, Julie Hunter, and Michalis Vazirgiannis. 2023. Fredsum: A dialogue summarization corpus for french political debates. arXiv preprint arXiv: 2312.04843. ↗
  128. Syed Toufeeq Ahmad Rizvi. 2020. A hybrid approach for information extraction from biomedical text. Ph.D. thesis, University of Bedfordshire. find
  129. Taiga Someya, Yushi Sugimoto, and Yohei Oseki. 2023. Jcola: Japanese corpus of linguistic acceptability. arXiv preprint arXiv: 2309.12676. ↗
  130. Julia Rodina and Andrey Kutuzov. 2020. Rusemshift: a dataset of historical lexical semantic change in russian. arXiv preprint arXiv: 2010.06436. ↗
  131. Ryosuke Sonobe, Shinnosuke Takamichi, and Hiroshi Saruwatari. 2017. Jsut corpus: free large-scale japanese speech corpus for end-to-end speech synthesis. arXiv preprint arXiv: 1711.00354. ↗
  132. Sergio J Rodríguez Méndez, Pouya G Omran, Armin Haller, and Kerry Taylor. 2021. MEL: Metadata extractor & loader. In European Semantic Web Conference, pages 159–163. Springer. find
  133. Mihaela Rosca and Thomas Breuel. 2016. Sequence-to-sequence neural network models for transliteration. arXiv preprint arXiv: 1610.09565. ↗
  134. Negar Rostamzadeh, Diana Mincu, Subhrajit Roy, Andrew Smart, Lauren Wilcox, Mahima Pushkarna, Jessica Schrouff, Razvan Amironesei, Nyalleng Moorosi, and Katherine Heller. 2022. Healthsheet: development of a transparency artifact for health datasets. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, pages 1943–1961. find
  135. Tarek Saier and Michael Färber. 2020. unarxive: a large scholarly data set with publications’ full-text, annotated in-text citations, and links to metadata. Scientometrics, 125(3):3085–3108. ↗
  136. Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2019. Winogrande: An adversarial winograd schema challenge at scale. arXiv preprint arXiv: 1907.10641. ↗
  137. Yuya Sakaizawa and Mamoru Komachi. 2017. Construction of a japanese word similarity dataset. arXiv preprint arXiv: 1703.05916. ↗
  138. Björn Schembera. 2021. Like a rainbow in the dark: metadata annotation for hpc applications in the age of dark data. The Journal of Supercomputing, 77(8):8946–8966. ↗
  139. Marcel Schilling-Wilhelmi, Melissa Ríos-García, Sameena Shabih, Marcos V. Gil, Santiago Miret, Christoph T. Koch, José A. Márquez, and Kevin Maik Jablonka. 2024. From text to insight: large language models for materials science data extraction. arXiv preprint arXiv:2407.16867. ↗
  140. Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, and Jacopo Staiano. 2020. Mlsum: The multilingual summarization corpus. arXiv preprint arXiv: 2004.14900. ↗
  141. Priyanka Sen, Alham Fikri Aji, and Amir Saffari. 2022. Mintaka: A complex, natural, and multilingual dataset for end-to-end question answering. arXiv preprint arXiv: 2210.01613. ↗
  142. ByungHoon So, Kyuhong Byun, Kyungwon Kang, and Seongjin Cho. 2022. Jaquad: Japanese question answering dataset for machine reading comprehension. arXiv preprint arXiv: 2202.01764. ↗
  143. Ramya Srinivasan, Emily Denton, Jordan Famularo, Negar Rostamzadeh, Fernando Diaz, and Beth Coleman. 2021. Artsheets for art datasets. In Thirty-fifth conference on neural information processing systems datasets and benchmarks track (round 2). find
  144. Gabriel Stanovsky, Noah A. Smith, and Luke Zettlemoyer. 2019. Evaluating gender bias in machine translation. arXiv preprint arXiv: 1906.00591. ↗
  145. Hongjin Su, Howard Yen, Mengzhou Xia, Weijia Shi, Niklas Muennighoff, Han yu Wang, Haisu Liu, Quan Shi, Zachary S. Siegel, Michael Tang, Ruoxi Sun, Jinsung Yoon, Sercan O. Arik, Danqi Chen, and Tao Yu. 2024. Bright: A realistic and challenging benchmark for reasoning-intensive retrieval. arXiv preprint arXiv: 2407.12883. ↗
  146. Tomoki Sugimoto, Yasumasa Onoe, and Hitomi Yanaka. 2023. Jamp: Controlled japanese temporal inference dataset for evaluating generalization capacity of language models. arXiv preprint arXiv: 2306.10727. ↗
  147. Daisuke Suzuki, Yujin Takahashi, Ikumi Yamashita, Taichi Aida, Tosho Hirasawa, Michitaka Nakatsuji, Masato Mita, and Mamoru Komachi. 2022. Construction of a quality estimation dataset for automatic evaluation of japanese grammatical error correction. arXiv preprint arXiv: 2201.08038. ↗
  148. Shinnosuke Takamichi, Ludwig Kürzinger, Takaaki Saeki, Sayaka Shiota, and Shinji Watanabe. 2021. Jtubespeech: corpus of japanese speech collected from youtube for speech recognition and speaker verification. arXiv preprint arXiv: 2112.09323. ↗
  149. Ekaterina Taktasheva, Maxim Bazhukov, Kirill Koncha, Alena Fenogenova, Ekaterina Artemova, and Vladislav Mikhailov. 2024. Rublimp: Russian benchmark of linguistic minimal pairs. arXiv preprint arXiv: 2406.19232. ↗
  150. Zhi Rui Tam, Cheng-Kuang Wu, Yi-Lin Tsai, Chieh-Yen Lin, Hung-yi Lee, and Yun-Nung Chen. 2024. Let me speak freely? a study on the impact of format restrictions on performance of large language models. arXiv preprint arXiv:2408.02442. ↗
  151. Kota Tanabe, Masahiro Suzuki, Hiroki Sakaji, and Itsuki Noda. 2024. Jafin: Japanese financial instruction dataset. arXiv preprint arXiv: 2404.09260. ↗
  152. Gemini Team, Rohan Anil, Sebastian Borgeaud, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, Katie Millican, and 1 others. 2023. Gemini: a family of highly capable multimodal models. arXiv preprint arXiv:2312.11805. ↗
  153. Yingtao Tian, Chikahiko Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, and Asanobu Kitamoto. 2020. Kaokore: A pre-modern japanese art facial expression dataset. arXiv preprint arXiv: 2002.08595. ↗
  154. Michelle Wastl, Jannis Vamvas, Selena Calleri, and Rico Sennrich. 2025. 20min-xd: A comparable corpus of swiss news articles. arXiv preprint arXiv: 2504.21677. ↗
  155. Dominika Tkaczyk, Paweł Szostek, Mateusz Fedo-ryszak, Piotr Jan Dendek, and Łukasz Bolikowski. 2015. CERMINE: automatic extraction of structured metadata from scientific literature. International Journal on Document Analysis and Recognition (IJ-DAR), 18(4):317–335. ↗
  156. Yu Watanabe, Koichiro Ito, and Shigeki Matsubara. 2024. Capabilities and challenges of llms in metadata extraction from scholarly papers. In International Conference on Asian Digital Libraries, pages 280– 287. Springer. find
  157. Alena Tsanda and Elena Bruches. 2024. Russian-language multimodal dataset for automatic summarization of scientific papers. arXiv preprint arXiv: 2405.07886. ↗
  158. Nobuhiro Ueda, Hideko Habe, Yoko Matsui, Akishige Yuguchi, Seiya Kawano, Yasutomo Kawanishi, Sadao Kurohashi, and Koichiro Yoshino. 2024. J-cre3: A japanese conversation dataset for real-world reference resolution. arXiv preprint arXiv: 2403.19259. ↗
  159. Jannis Vamvas and Rico Sennrich. 2020. X-stance: A multilingual multi-target dataset for stance detection. arXiv preprint arXiv: 2003.08385. ↗
  160. Viacheslav Vasilev, Julia Agafonova, Nikolai Gerasimenko, Alexander Kapitanov, Polina Mikhailova, Evelina Mironova, and Denis Dimitrov. 2025a. Rus-code: Russian cultural code benchmark for text-to-image generation. arXiv preprint arXiv: 2502.07455. ↗
  161. Viacheslav Vasilev, Vladimir Arkhipkin, Julia Agafonova, Tatiana Nikulina, Evelina Mironova, Alisa Shichanina, Nikolai Gerasimenko, Mikhail Shoytov, and Denis Dimitrov. 2025b. Craft: Cultural russian-oriented dataset adaptation for focused text-to-image generation. arXiv preprint arXiv: 2505.04851. ↗
  162. Amir Pouran Ben Veyseh, Javid Ebrahimi, Franck Dernoncourt, and Thien Huu Nguyen. 2022a. Mee: A novel multilingual event extraction dataset. arXiv preprint arXiv: 2211.05955. ↗
  163. Amir Pouran Ben Veyseh, Minh Van Nguyen, Franck Dernoncourt, and Thien Huu Nguyen. 2022b. Minion: a large-scale and diverse dataset for multilingual event detection. arXiv preprint arXiv: 2211.05958. ↗
  164. Josiah Wang, Pranava Madhyastha, Josiel Figueiredo, Chiraag Lala, and Lucia Specia. 2021. Multisubs: A large-scale multimodal and multilingual dataset. arXiv preprint arXiv: 2103.01910. ↗
  165. Yubo Wang, Xueguang Ma, Ge Zhang, Yuansheng Ni, Abhranil Chandra, Shiguang Guo, Weiming Ren, Aaran Arulraj, Xuan He, Ziyan Jiang, Tianle Li, Max Ku, Kai Wang, Alex Zhuang, Rongqi Fan, Xiang Yue, and Wenhu Chen. 2024. Mmlu-pro: A more robust and challenging multi-task language understanding benchmark. arXiv preprint arXiv: 2406.01574. ↗
  166. Johannes Welbl, Nelson F. Liu, and Matt Gardner. 2017. Crowdsourcing multiple choice science questions. arXiv preprint arXiv: 1707.06209. ↗
  167. Mark D Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, Jan-Willem Boiten, Luiz Bonino da Silva Santos, Philip E Bourne, and 1 others. 2016. The fair guiding principles for scientific data management and stewardship. Scientific data, 3(1):1–9. find
  168. Ankit Yadav, Shubham Chandel, Sushant Chatufale, and Anil Bandhakavi. 2023. Lahm : Large annotated dataset for multi-domain and multilingual hate speech identification. arXiv preprint arXiv: 2304.00913. ↗
  169. Wenli Yang, Rui Fu, Muhammad Bilal Amin, and Byeong Kang. 2025. Impact and influence of modern ai in metadata management. arXiv preprint arXiv:2501.16605. ↗
  170. Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018. Hotpotqa: A dataset for diverse, explainable multi-hop question answering. arXiv preprint arXiv: 1809.09600. ↗
  171. Yuya Yoshikawa, Yutaro Shigeto, and Akikazu Takeuchi. 2017. Stair captions: Constructing a large-scale japanese image caption dataset. arXiv preprint arXiv: 1705.00823. ↗
  172. Jamil Zaghir, Mina Bjelogrlic, Jean-Philippe Goldman, Soukaïna Aananou, Christophe Gaudet-Blavignac, and Christian Lovis. 2023. Frasimed: a clinical french annotated resource produced through crosslingual bert-based annotation projection. arXiv preprint arXiv: 2309.10770. ↗
  173. Wajdi Zaghouani and Anis Charfi. 2018. Arap-tweet: A large multi-dialect twitter corpus for gender, age and language variety identification. arXiv preprint arXiv: 1808.07674. ↗
  174. Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019. Hellaswag: Can a machine really finish your sentence? arXiv preprint arXiv: 1905.07830. ↗
  175. Shouyuan Zhang, Xiaohan Ding, and Alexander M Rush. 2023. Extending context window of large language models via positional interpolation. arXiv preprint arXiv:2306.15595. ↗
  176. Miao Zhu and Jacqueline M Cole. 2022. Pdfdataextrac-tor: A tool for reading scientific text and interpreting metadata from the typeset literature in the portable document format. Journal of Chemical Information and Modeling, 62(7):1633–1643. find

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/alyafeai-2025-mole-metadata-extraction-validation-scientific/