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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
Personal Interests
Personal interests.
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Posts
Future Blog Post
Published:
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Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
QMUL-SDS at SCIVER: Step-by-Step Binary Classification for Scientific Claim Verification
Published in Proceedings of the Second Workshop on Scholarly Document Processing, 2021
In this paper, we propose an approach that performs scientific claim verification by doing binary classifications step-by-step.
Recommended citation: Zeng, X., & Zubiaga, A. (2021). QMUL-SDS at SCIVER: Step-by-step binary classification for scientific claim ver-ification. In Proceedings of the Second Workshop on Scientific Document Processing (pp. 116–123). Association for Computational Linguistics. https://aclanthology.org/2021.sdp-1.15.pdf
Automated Fact-Checking: A Survey
Published in Language and Linguistics Compass, 2021
This article reviews relevant research on automated fact-checking covering both the claim detection and claim validation components.
Recommended citation: Zeng, X., Abumansour, A. S., & Zubiaga, A. (2021). Automated fact-checking: A survey. Language & Linguistics Compass, e12438. https://doi.org/10.1111/lnc3.12438 https://onlinelibrary.wiley.com/doi/epdf/10.1111/lnc3.12438
Aggregating pairwise semantic differences for few-shot claim verification
Published in PeerJ Computer Science, 2022
This article introduces Semantic Embedding Element-wise Difference (SEED), a novel vector-based method to few-shot claim verification that aggregates pairwise semantic differences for claim-evidence pairs.
Recommended citation: Zeng X, Zubiaga A. 2022. Aggregating pairwise semantic differences for few-shot claim verification. PeerJ Computer Science 8:e1137 https://doi.org/10.7717/peerj-cs.1137 https://peerj.com/articles/cs-1137/
Active PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Training
Published in EACL Findings 2023, 2023
We propose Active PETs, a novel weighted approach that utilises an ensemble of Pattern Exploiting Training (PET) models based on various language models, to actively select unlabelled data as candidates for annotation.
Recommended citation: Xia Zeng and Arkaitz Zubiaga. 2023. Active PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Training. In Findings of the Association for Computational Linguistics: EACL 2023, pages 190–204, Dubrovnik, Croatia. Association for Computational Linguistics. https://aclanthology.org/2023.findings-eacl.14/
MAPLE: Micro Analysis of Pairwise Language Evolution for Few-Shot Claim Verification
Published in EACL Findings 2024, 2024
We propose MAPLE (Micro Analysis of Pairwise Language Evolution), a pioneering approach that explores the alignment between a claim and its evidence with a small seq2seq model and a novel semantic measure.
Recommended citation: Xia Zeng and Arkaitz Zubiaga. 2024. MAPLE: Micro Analysis of Pairwise Language Evolution for Few-Shot Claim Verification. In Findings of the Association for Computational Linguistics: EACL 2024, pages 1177–1196, St. Julian’s, Malta. Association for Computational Linguistics. https://aclanthology.org/2024.findings-eacl.79/
Combining Large Language Models and Crowdsourcing for Hybrid Human-AI Misinformation Detection
Published in SIGIR 2024, 2024
We study hybrid human-AI approaches jointly leveraging the potential of large language models and crowdsourcing.
Recommended citation: Xia Zeng, David La Barbera, Kevin Roitero, Arkaitz Zubiaga, and Stefano Mizzaro. 2024. Combining Large Language Models and Crowdsourcing for Hybrid Human-AI Misinformation Detection. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '24). Association for Computing Machinery, New York, NY, USA, 2332–2336. https://doi.org/10.1145/3626772.3657965 https://dl.acm.org/doi/pdf/10.1145/3626772.3657965
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.