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Jonathan Tonglet

Jonathan Tonglet has 2 papers in our library, in 2026, most of them on Language models & pretraining, Vision & language; often with Iryna Gurevych, Tinne Tuytelaars, Marie-Francine Moens.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 4 · 20 works · 57 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 4 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #10712

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

🎓KU LeuvenLeuven · Belgium2022–2026 · 9 paperscurrent🎓Technische Universität DarmstadtDarmstadt · Germany2023–2026 · 7 paperscurrent🔬Hessian Center for Artificial IntelligenceDarmstadt · Germany2023–2024 · 3 papers

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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksComputer Vision and Pattern Recognition · 2 worksArtificial Intelligence · 1 workMathematics · 1 workSocial Sciences · 1 workSociology and Political Science · 1 workStatistics and Probability · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workVision & language · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Protecting multimodal large language models against misleading visualizations (2026 · 3 citations)
    Charts can distort their underlying data through design flaws called misleaders, such as truncated or inverted axes, dual axes, or 3D effects.
  2. Is this chart lying to me? Automating the detection of misleading visualizations (2026 · 1 citation)
    Charts that break design conventions, for example through truncated axes or misleading 3D effects, can distort data and spread misinformation online.

All works

4 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. Protecting multimodal large language models against misleading visualizationsAnnual Meeting of the Association for Computational Linguistics (ACL)Jonathan Tonglet, Tinne Tuytelaars, Marie-Francine Moens, et al.2026 · 3 citations
  2. Is this chart lying to me? Automating the detection of misleading visualizationsAnnual Meeting of the Association for Computational Linguistics (ACL)Jonathan Tonglet, Jan Zimny, Tinne Tuytelaars, et al.2026 · 1 citation
  3. ChartAttack: Testing the Vulnerability of LLMs to Malicious Prompting in Chart Generation ↗arXiv:2601.12983 · no summary yetJesus-German Ortiz-Barajas et al.2026
  4. Last Translation Benchmark ↗arXiv:2609.04173 · no summary yetVilem Zouhar et al.2026

 Co-authors here

3 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 4 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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