Dr Michael Schlichtkrull
Lecturer
School of Electronic Engineering and Computer Science
Queen Mary University of London
Research
Natural language processing, fact verification, question answering, graph neural networks
Interests
Michael works on automated reasoning over retrieved evidence, focusing especially on automated fact-checking where he has published both models and datasets. He is also interested in interpretability for NLP, as well as techniques for modelling and incorporating structured data such as tables or knowledge bases into NLP applications.
Publications
Publications of specific relevance to the Centre for Human-Centred Computing
2024
Generating Media Background Checks for Automated Source Critical ReasoningSchlichtkrull M Findings of the 2024 Conference on Empirical Methods in Natural Language Processing Miami, Florida 12 Nov 2024 - 16 Nov 2024.
12-11-2024The Automated Verification of Textual Claims (AVeriTeC) Shared TaskSchlichtkrull M, Chen Y, Whitehouse C, Deng Z, Akhtar M, Aly R, Guo Z, Christodoulopoulos C, Cocarascu O, Mittal A, Thorne J and Vlachos A
The Seventh Workshop on Fact Extraction and Verification (FEVER).
01-11-2024 Document-level Claim Extraction and Decontextualisation for Fact-CheckingDeng Z,
Schlichtkrull M and Vlachos A
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics.
11-08-2024 Automated Focused Feedback Generation for Scientific Writing AssistanceChamoun E,
Schlichtkrull M and Vlachos A
Findings of the Association for Computational Linguistics ACL 2024.
11-08-2024 2023
AVeriTeC: A dataset for real-world claim verification with evidence from the webSchlichtkrull M, Guo Z and Vlachos A
Advances in Neural Information Processing Systems 36.
10-12-2023 Are Embedded Potatoes Still Vegetables? On the Limitations of WordNet Embeddings for Lexical SemanticsCheng X,
Schlichtkrull M and Emerson G
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing.
06-12-2023 Multimodal Automated Fact-Checking: A SurveyAkhtar M,
Schlichtkrull M, Guo Z, Cocarascu O, Simperl E and Vlachos A
Findings of the Association for Computational Linguistics: EMNLP 2023., 5430-5448.
01-01-2023 The Intended Uses of Automated Fact-Checking Artefacts: Why, How and WhoSchlichtkrull M, Ousidhoum N and Vlachos A
Findings of the Association for Computational Linguistics: EMNLP 2023., 8618-8642.
01-01-2023 2022
A Survey on Automated Fact-CheckingGuo Z,
Schlichtkrull M and Vlachos A
Transactions of The Association For Computational Linguistics,
Mit Press vol. 10, 178-206.
09-02-2022 2021
The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared TaskAly R, Guo Z,
Schlichtkrull MS, Thorne J, Vlachos A, Christodoulopoulos C, Cocarascu O and Mittal A
Proceedings of the Fourth Workshop on Fact Extraction and VERification (FEVER)., 1-13.
01-01-2021 Joint Verification and Reranking for Open Fact Checking Over TablesSchlichtkrull MS, Karpukhin V, Oguz B, Lewis M, Yih W-T and Riedel S
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)., 6787-6799.
01-01-2021 2020
Interpreting graph neural networks for NLP with differentiable edge maskingSchlichtkrull M, De Cao N and Titov I
The Ninth International Conference on Learning Representations.
01-10-2020 How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable MaskingDe Cao N,
Schlichtkrull MS, Aziz W and Titov I
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)., 3243-3255.
01-01-2020 2018
Modeling Relational Data with Graph Convolutional NetworksSchlichtkrull M, Kipf TN, Bloem P, van den Berg R, Titov I and Welling M
European Semantic Web Conference 2018.
03-06-2018
Grants
Grants of specific relevance to the Centre for Human-Centred Computing
