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Dimitar Iliyanov Dimitrov

Dimitar Iliyanov Dimitrov has 5 papers in our library, in 2021–2026, most of them on Bias, fairness & safety, Vision & language, Language models & pretraining; often with Preslav Nakov, Md. Shad Akhtar, Shivam Sharma.

5 papers in our library · 2021–2026

OpenAlex · ORCID · h-index 7 · 39 works · 528 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 265 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4021

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

🎓Sofia University "St. Kliment Ohridski"Sofia · Bulgaria2018–2026 · 31 papersEducation 2018–2020 · Master'sEducation 2021–2026 · PhDcurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 11The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksArtificial Intelligence · 5 worksSocial Sciences · 4 worksSociology and Political Science · 2 worksPsychology · 1 workSocial Psychology · 1 workArts and Humanities · 2 worksLanguage and Linguistics · 2 worksPhilosophy · 2 worksGeneral Social Sciences · 1 workSafety Research · 1 work

🧭 Topics 3Research subjects and languages the work is about.Bias, fairness & safety · 3 worksVision & language · 2 worksLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers20213 papers

 Papers

The most cited first (OpenAlex and our library).

  1. MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets (2021 · 212 citations)
    The paper addresses automatic recognition of harmful memes, where an image and its overlaid text together can damage a person, organization, community or society, even when neither part looks offensive alone.
  2. Detecting Harmful Memes and Their Targets (2021 · 171 citations)
    The paper argues that harmful memes are a broader category than hateful or offensive ones. A meme can damage a person's or group's reputation without using insulting language. The authors also note that the victim of a harmful meme deserves attention of its own. They define two tasks. The first rates a meme's…
  3. SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images (2021 · 75 citations)
    This shared task addresses the automatic identification of propaganda and persuasion devices in memes. Memes carry their message through both overlaid text and the picture, so studying text alone misses part of the signal. Building on SemEval-2020 task 11, which covered news text only, the organisers created a…
  4. A Corpus of Persuasion Techniques in Slavic Languages (2026)
    Resources for detecting persuasion techniques in Slavic languages are scarce, especially outside news media.
  5. Schützen: Evaluating LLM Safety in Bulgarian and German Contexts (2026)
    Most LLM safety benchmarks are built for English or Chinese and usually test other languages one at a time.

All works

7 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

  1. MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their TargetsFindings of the Association for Computational LinguisticsShraman Pramanick, Shivam Sharma, Dimitar Dimitrov, et al.2021 · 212 citations
  2. Detecting Harmful Memes and Their TargetsFindings of the Association for Computational LinguisticsShraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee, et al.2021 · 171 citations
  3. Detecting Propaganda Techniques in Memes ↗Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yetDimitar Dimitrov et al.2021 · 136 citations
  4. SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and ImagesInternational Workshop on Semantic Evaluation (SemEval)Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar, et al.2021 · 75 citations
  5. A Corpus of Persuasion Techniques in Slavic LanguagesLanguage Resources and Evaluation Conference (LREC)Jakub Piskorski, Dimitar Iliyanov Dimitrov, Marina Ernst, et al.2026
  6. Schützen: Evaluating LLM Safety in Bulgarian and German ContextsarXiv:2606.11316Kiril Georgiev, Yuxia Wang, Dimitar Iliyanov Dimitrov, et al.2026
  7. FMISUYotkovaKastreva at SemEval-2026 Task 13: Lightweight Detection of LLM-Generated Code via Stylometric Signals ↗Proceedings of the 20th International Workshop on Semantic Evaluation (2026) · no summary yetElitsa Yotkova et al.2026

 Co-authors here

12 of 16 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 265 times (of the 149,439 papers whose bibliographies we read); 36 citing papers with a page here →.

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