Elamur Research⌕
☰
home / authors / Timothy M. Hospedales

Timothy M. Hospedales

Timothy M. Hospedales has 2 papers in our library, in 2019–2024, most of them on Language models & pretraining, Knowledge graphs & ontologies, Bias, fairness & safety; often with Ivana Balažević, Ondrej Bohdal.

2 papers in our library · 2019–2024

OpenAlex · ORCID · Wikidata · h-index 63 · 352 works · 19,483 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 246 times in our library · 9 more in our library without a page yet · ⭐ Paper Stars ranking: #2997

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 EdinburghEdinburgh · United Kingdom2007–2026 · 177 papersEmploymentcurrent🏢SamsungChertsey · United Kingdom2021–2026 · 13 paperscurrent🏢SamsungSeoul · South Korea2020–2026 · 9 paperscurrent🎓Queen Mary University of LondonLondon · United Kingdom2009–2024 · 64 papers🎓University of SurreyGuildford · United Kingdom2019–2023 · 11 papers🎓University of LondonLondon · United Kingdom2009–2016 · 4 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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksArts and Humanities · 1 workComputational Mathematics · 1 workLanguage and Linguistics · 1 workMathematics · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Knowledge graphs & ontologies · 1 workBias, fairness & safety · 1 workLanguage models & pretraining · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Knowledge graph · 1 work

 Works by year

2020s

20241 paper

2010s

20191 paper

 Papers

The most cited first (OpenAlex and our library).

  1. TuckER: Tensor Factorization for Knowledge Graph Completion (2019 · 799 citations)
    Knowledge graphs store facts as subject–relation–object triples, but they cover only a fraction of what is true.
  2. Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models (2024 · 60 citations)
    Vision large language models (VLLMs) are usually built by fine-tuning an already safety-aligned LLM on vision-language instruction data.

All works

11 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. TuckER: Tensor Factorization for Knowledge Graph CompletionarXiv:1901.09590Ivana Balažević, Carl Allen, Timothy M. Hospedales2019 · 799 citations
  2. Episodic Training for Domain Generalization ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetDa Li et al.2019 · 442 citations
  3. Deep Domain-Adversarial Image Generation for Domain Generalisation ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetKaiyang Zhou et al.2020 · 393 citations
  4. Transferring a semantic representation for person re-identification and search ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetZhiyuan Shi, Timothy M. Hospedales, Tao Xiang2015 · 193 citations
  5. Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetShell Xu Hu et al.2022 · 190 citations
  6. Robust Person Re-Identification by Modelling Feature Uncertainty ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetTianyuan Yu et al.2019 · 143 citations
  7. Generalising Fine-Grained Sketch-Based Image Retrieval ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetKaiyue Pang et al.2019 · 110 citations
  8. ForgetMeNot: Memory-Aware Forensic Facial Sketch Matching ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetShuxin Ouyang et al.2016 · 67 citations
  9. Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language ModelsarXiv:2402.02207Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, et al.2024 · 60 citations
  10. Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations ↗arXiv:2310.01651 · no summary yetYongshuo Zong et al.2023 · 24 citations
  11. MUStReason: A Benchmark for Diagnosing Pragmatic Reasoning in VideoLMs for Multimodal Sarcasm Detection. ↗Proceedings of the Fifteenth Language Resources and Evaluation Conference · no summary yetAnisha Saha et al.2026

 Co-authors here

2 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 246 times (of the 149,439 papers whose bibliographies we read); 30 citing papers with a page here →.

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/timothy-m-hospedales/