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Meng Fang

Meng Fang has 2 papers in our library, in 2026, most of them on Bias, fairness & safety; often with Ling Chen, Biao Wu, Haozhe Wang.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 26 · 131 works · 2,736 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 284 times in our library · 12 more in our library without a page yet · ⭐ Paper Stars ranking: #10730

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of LiverpoolLiverpool · United Kingdom2022–2026 · 79 paperscurrent🎓Eindhoven University of TechnologyEindhoven · Netherlands2021–2026 · 29 papers🏢TencentShenzhen · China2018–2025 · 26 papers🎓University of Technology SydneySydney · Australia2012–2023 · 22 papers🎓The University of MelbourneMelbourne · Australia2016–2018 · 10 papers🏛️Commonwealth Scientific and Industrial Research OrganisationCanberra · Australia2013–2016 · 4 papers🏛️National Research and Innovation AgencyJakarta · Indonesia2023–2026 · 2 papers🎓Monash UniversityMelbourne · Australia2022–2023 · 2 papers🎓University of CambridgeCambridge · United Kingdom2022–2023 · 2 papers🎓Wuhan UniversityWuhan · China2010–2011 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArts and Humanities · 1 workArtificial Intelligence · 2 worksInformation Systems · 2 worksComputer Vision and Pattern Recognition · 1 workLanguage and Linguistics · 1 work

🧭 Topics 1Research subjects and languages the work is about.Bias, fairness & safety · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Infinity-Parser: Layout-Aware Reinforcement Learning with High-quality Document Parsing Dataset (2026 · 4 citations)
    Converting scanned pages into structured Markdown is difficult. Pages mix paragraphs, tables, formulas and figures, and a parser must recover both the content and its layout and reading order. The authors identify two obstacles: there is little training data with precise, layout-aware annotation, and supervised…
  2. Benchmarking Web Agent Safety under E-commerce Deceptive Interfaces (2026)
    Autonomous multimodal web agents increasingly act on users' behalf online, yet safety evaluations have mostly targeted malicious instructions or prompt injection.

All works

14 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Learning how to Active Learn: A Deep Reinforcement Learning Approach ↗Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · no summary yetMeng Fang, Yuan Li, Trevor Cohn2017 · 301 citations
  2. Learning Granularity-Unified Representations for Text-to-Image Person Re-identification ↗ACM International Conference on Multimedia (ACM MM) · no summary yetZhiyin Shao et al.2022 · 197 citations
  3. Saliency propagation from simple to difficult ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetChen Gong et al.2015 · 151 citations
  4. Dual Adversarial Neural Transfer for Low-Resource Named Entity Recognition ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetJoey Tianyi Zhou et al.2019 · 134 citations
  5. Model Transfer for Tagging Low-resource Languages using a Bilingual Dictionary ↗Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yetMeng Fang, Trevor Cohn2017 · 112 citations
  6. Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for Topics ↗Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetZihan Zhang et al.2022 · 87 citations
  7. OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models ↗arXiv:2410.09671 · no summary yetJun Wang et al.2024 · 50 citations
  8. MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data ↗arXiv:2406.18321 · no summary yetMeng Fang et al.2024 · 46 citations
  9. Large Language Models Are Neurosymbolic Reasoners ↗arXiv:2401.09334 · no summary yetMeng Fang et al.2024 · 34 citations
  10. Infinity-Parser: Layout-Aware Reinforcement Learning with High-quality Document Parsing DatasetFindings of the Association for Computational LinguisticsBaode Wang, Biao Wu, Weizhen Li, et al.2026 · 4 citations
  11. VaseVQA: Multimodal Agent and Benchmark for Ancient Greek Pottery ↗Findings of the Association for Computational Linguistics: EACL 2026 · no summary yetJinchao Ge et al.2026 · 1 citation
  12. Benchmarking Web Agent Safety under E-commerce Deceptive InterfacesAnnual Meeting of the Association for Computational Linguistics (ACL)Zijing Shi, Meng Fang, Ling Chen2026
  13. DOSE: Data Selection for Multi-Modal LLMs via Off-the-Shelf Models ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetBiao Wu et al.2026
  14. MATH-IDN: A Multilingual Mathematical Problem Solving Dataset Featuring Local Languages in Indonesia ↗Findings of the Association for Computational Linguistics: EACL 2026 · no summary yetXiao Xiao et al.2026

 Co-authors here

6 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 284 times (of the 149,439 papers whose bibliographies we read); 53 citing papers with a page here →.

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