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Documents authored by Tuytelaars, Tinne

Document
DOI: 10.4230/DagRep.15.10.119
Deep Continual Learning in the Foundation Model Era (Dagstuhl Seminar 25432)

Authors: Christopher Kanan, Martin Mundt, Tinne Tuytelaars, Joost van de Weijer, and Timm Felix Hess

Published in: Dagstuhl Reports, Volume 15, Issue 10 (2026)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 25432 "Deep Continual Learning in the Foundation Model Era". This seminar brought together 23 researchers to discuss research at the intersection of continual learning and foundation models. The discussion centered on the major challenges arising from continual training of foundation models, including the need for new benchmarks, new opportunities for memory-based continual learning, emerging application domains, and the development of efficient metrics to quantify forgetting of foundation model knowledge. In addition, the report contains a summery of the talks of the partipants.
Cite as

Christopher Kanan, Martin Mundt, Tinne Tuytelaars, Joost van de Weijer, and Timm Felix Hess. Deep Continual Learning in the Foundation Model Era (Dagstuhl Seminar 25432). In Dagstuhl Reports, Volume 15, Issue 10, pp. 119-134, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{kanan_et_al:DagRep.15.10.119,
  author =	{Kanan, Christopher and Mundt, Martin and Tuytelaars, Tinne and van de Weijer, Joost and Hess, Timm Felix},
  title =	{{Deep Continual Learning in the Foundation Model Era (Dagstuhl Seminar 25432)}},
  pages =	{119--134},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2026},
  volume =	{15},
  number =	{10},
  editor =	{Kanan, Christopher and Mundt, Martin and Tuytelaars, Tinne and van de Weijer, Joost and Hess, Timm Felix},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.10.119},
  URN =		{urn:nbn:de:0030-drops-254123},
  doi =		{10.4230/DagRep.15.10.119},
  annote =	{Keywords: continual learning, deep learning, foundation models}
}
Document
DOI: 10.4230/DagRep.13.3.74
Deep Continual Learning (Dagstuhl Seminar 23122)

Authors: Tinne Tuytelaars, Bing Liu, Vincenzo Lomonaco, Gido van de Ven, and Andrea Cossu

Published in: Dagstuhl Reports, Volume 13, Issue 3 (2023)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23122 "Deep Continual Learning". This seminar brought together 26 researchers to discuss open problems and future directions of Continual Learning. The discussion revolved around key properties and the definition of Continual Learning itself, on the way Continual Learning should be evaluated, and on its real-world applications beyond academic research.
Cite as

Tinne Tuytelaars, Bing Liu, Vincenzo Lomonaco, Gido van de Ven, and Andrea Cossu. Deep Continual Learning (Dagstuhl Seminar 23122). In Dagstuhl Reports, Volume 13, Issue 3, pp. 74-91, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{tuytelaars_et_al:DagRep.13.3.74,
  author =	{Tuytelaars, Tinne and Liu, Bing and Lomonaco, Vincenzo and van de Ven, Gido and Cossu, Andrea},
  title =	{{Deep Continual Learning (Dagstuhl Seminar 23122)}},
  pages =	{74--91},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{3},
  editor =	{Tuytelaars, Tinne and Liu, Bing and Lomonaco, Vincenzo and van de Ven, Gido and Cossu, Andrea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.3.74},
  URN =		{urn:nbn:de:0030-drops-192298},
  doi =		{10.4230/DagRep.13.3.74},
  annote =	{Keywords: continual learning, incremental learning}
}
Document
DOI: 10.4230/DagRep.9.1.1
Joint Processing of Language and Visual Data for Better Automated Understanding (Dagstuhl Seminar 19021)

Authors: Marie-Francine Moens, Lucia Specia, and Tinne Tuytelaars

Published in: Dagstuhl Reports, Volume 9, Issue 1 (2019)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19021 "Joint Processing of Language and Visual Data for Better Automated Understanding". It includes a discussion of the motivation and overall organization, the abstracts of the talks, and a report of each working group.
Cite as

Marie-Francine Moens, Lucia Specia, and Tinne Tuytelaars. Joint Processing of Language and Visual Data for Better Automated Understanding (Dagstuhl Seminar 19021). In Dagstuhl Reports, Volume 9, Issue 1, pp. 1-27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@Article{moens_et_al:DagRep.9.1.1,
  author =	{Moens, Marie-Francine and Specia, Lucia and Tuytelaars, Tinne},
  title =	{{Joint Processing of Language and Visual Data for Better Automated Understanding (Dagstuhl Seminar 19021)}},
  pages =	{1--27},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{1},
  editor =	{Moens, Marie-Francine and Specia, Lucia and Tuytelaars, Tinne},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.1.1},
  URN =		{urn:nbn:de:0030-drops-105673},
  doi =		{10.4230/DagRep.9.1.1},
  annote =	{Keywords: multimodal learning, representation learning, computer vision, natural language processing, machine learning}
}
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