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20242026
most citedDocument-level Claim Extraction and Decontextualisation for Fact-Checking

1 citations · 1 across the 8 of their papers we have counts for

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cs.CL2026

Multimodal Claim Extraction for Fact-Checking

Joycelyn Teo, Rui Cao, Zhenyun Deng +3

Automated Fact-Checking (AFC) relies on claim extraction as a first step, yet existing methods largely overlook the multimodal nature of today's misinformation. Social media posts…

cs.CL2026

The Automatic Verification of Image-Text Claims (AVerImaTeC) Shared Task

Rui Cao, Zhenyun Deng, Yulong Chen +2

The Automatic Verification of Image-Text Claims (AVerImaTeC) shared task aims to advance system development for retrieving evidence and verifying real-world image-text claims. Part…

cs.CL2025

Improving Zero-shot Sentence Decontextualisation with Content Selection and Planning

Zhenyun Deng, Yulong Chen, Andreas Vlachos

Extracting individual sentences from a document as evidence or reasoning steps is commonly done in many NLP tasks. However, extracted sentences often lack context necessary to make…

cs.CL2025

PledgeTracker: A System for Monitoring the Fulfilment of Pledges

Yulong Chen, Michael Sejr Schlichtkrull, Zhenyun Deng +5

Political pledges reflect candidates' policy commitments, but tracking their fulfilment requires reasoning over incremental evidence distributed across multiple, dynamically update…

cs.CL2024

The Automated Verification of Textual Claims (AVeriTeC) Shared Task

Michael Schlichtkrull, Yulong Chen, Chenxi Whitehouse +9

The Automated Verification of Textual Claims (AVeriTeC) shared task asks participants to retrieve evidence and predict veracity for real-world claims checked by fact-checkers. Evid…

cs.CL20241 cited

Document-level Claim Extraction and Decontextualisation for Fact-Checking

Zhenyun Deng, Michael Schlichtkrull, Andreas Vlachos

Selecting which claims to check is a time-consuming task for human fact-checkers, especially from documents consisting of multiple sentences and containing multiple claims. However…