Michael Sejr Schlichtkrull
Cited by
Cited by
Modeling relational data with graph convolutional networks
MS Schlichtkrull, TN Kipf, P Bloem, R van den Berg, I Titov, M Welling
European Semantic Web Conference, 593-607, 2018
A survey on automated fact-checking
Z Guo, M Schlichtkrull, A Vlachos
Transactions of the Association for Computational Linguistics 10, 178-206, 2022
Interpreting graph neural networks for NLP with differentiable edge masking
MS Schlichtkrull, N De Cao, I Titov
arXiv preprint arXiv:2010.00577, 2020
Feverous: Fact extraction and verification over unstructured and structured information
R Aly, Z Guo, M Schlichtkrull, J Thorne, A Vlachos, C Christodoulopoulos, ...
arXiv preprint arXiv:2106.05707, 2021
Unik-qa: Unified representations of structured and unstructured knowledge for open-domain question answering
B Oguz, X Chen, V Karpukhin, S Peshterliev, D Okhonko, M Schlichtkrull, ...
arXiv preprint arXiv:2012.14610, 2020
How do decisions emerge across layers in neural models? interpretation with differentiable masking
N De Cao, M Schlichtkrull, W Aziz, I Titov
arXiv preprint arXiv:2004.14992, 2020
Neurips 2020 efficientqa competition: Systems, analyses and lessons learned
S Min, J Boyd-Graber, C Alberti, D Chen, E Choi, M Collins, K Guu, ...
NeurIPS 2020 Competition and Demonstration Track, 86-111, 2021
Unified open-domain question answering with structured and unstructured knowledge
B Oguz, X Chen, V Karpukhin, S Peshterliev, D Okhonko, M Schlichtkrull, ...
arXiv preprint arXiv:2012.14610, 2020
Joint verification and reranking for open fact checking over tables
M Schlichtkrull, V Karpukhin, B Oğuz, M Lewis, W Yih, S Riedel
arXiv preprint arXiv:2012.15115, 2020
Cross-lingual dependency parsing with late decoding for truly low-resource languages
MS Schlichtkrull, A Søgaard
arXiv preprint arXiv:1701.01623, 2017
Msejrku at semeval-2016 task 14: Taxonomy enrichment by evidence ranking
M Schlichtkrull, HM Alonso
Proceedings of the 10th international workshop on semantic evaluation …, 2016
Learning affective projections for emoticons on Twitter
MS Schlichtkrull
2015 6th IEEE International Conference on Cognitive Infocommunications …, 2015
Averitec: A dataset for real-world claim verification with evidence from the web
M Schlichtkrull, Z Guo, A Vlachos
Advances in Neural Information Processing Systems 36, 2024
Multimodal automated fact-checking: A survey
M Akhtar, M Schlichtkrull, Z Guo, O Cocarascu, E Simperl, A Vlachos
arXiv preprint arXiv:2305.13507, 2023
Modeling relational data with graph convolutional networks
I Titov, M Welling, M Schlichtkrull, P Bloem, R Berg, TN Kipf
Proceedings of the European Semantic Web Conference. Heraklion, 593-607, 2018
The intended uses of automated fact-checking artefacts: Why, how and who
M Schlichtkrull, N Ousidhoum, A Vlachos
arXiv preprint arXiv:2304.14238, 2023
Evaluating for diversity in question generation over text
MS Schlichtkrull, W Cheng
arXiv preprint arXiv:2008.07291, 2020
Incorporating structure into neural models for language processing
MS Schlichtkrull
University of Amsterdam, 2021
Document-level Claim Extraction and Decontextualisation for Fact-Checking
Z Deng, M Schlichtkrull, A Vlachos
arXiv e-prints, arXiv: 2406.03239, 2024
Are Embedded Potatoes Still Vegetables? On the Limitations of WordNet Embeddings for Lexical Semantics
X Cheng, M Schlichtkrull, G Emerson
Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023
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