Claim Verification

63 papers with code • 1 benchmarks • 2 datasets

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Most implemented papers

FEVER: a large-scale dataset for Fact Extraction and VERification

sheffieldnlp/fever-baselines NAACL 2018

Thus we believe that FEVER is a challenging testbed that will help stimulate progress on claim verification against textual sources.

Overview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Media

sshaar/clef2020-factchecking-task1 15 Jul 2020

The first four tasks compose the full pipeline of claim verification in social media: Task 1 on check-worthiness estimation, Task 2 on retrieving previously fact-checked claims, Task 3 on evidence retrieval, and Task 4 on claim verification.

MultiVerS: Improving scientific claim verification with weak supervision and full-document context

dwadden/longchecker Findings (NAACL) 2022

Our approach outperforms two competitive baselines on three scientific claim verification datasets, with particularly strong performance in zero / few-shot domain adaptation experiments.

Combining Fact Extraction and Verification with Neural Semantic Matching Networks

easonnie/combine-FEVER-NSMN 16 Nov 2018

The increasing concern with misinformation has stimulated research efforts on automatic fact checking.

BERT for Evidence Retrieval and Claim Verification

thunlp/KernelGAT 7 Oct 2019

Motivated by the promising performance of pre-trained language models, we investigate BERT in an evidence retrieval and claim verification pipeline for the FEVER fact extraction and verification challenge.

Fact or Fiction: Verifying Scientific Claims

allenai/scifact EMNLP 2020

We introduce scientific claim verification, a new task to select abstracts from the research literature containing evidence that SUPPORTS or REFUTES a given scientific claim, and to identify rationales justifying each decision.

Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval

stanford-futuredata/ColBERT NeurIPS 2021

Multi-hop reasoning (i. e., reasoning across two or more documents) is a key ingredient for NLP models that leverage large corpora to exhibit broad knowledge.

AmbiFC: Fact-Checking Ambiguous Claims with Evidence

CambridgeNLIP/verification-real-world-info-needs 1 Apr 2021

Automated fact-checking systems verify claims against evidence to predict their veracity.

DialFact: A Benchmark for Fact-Checking in Dialogue

salesforce/dialfact ACL 2022

Fact-checking is an essential tool to mitigate the spread of misinformation and disinformation.

AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web

michschli/averitec NeurIPS 2023

Existing datasets for automated fact-checking have substantial limitations, such as relying on artificial claims, lacking annotations for evidence and intermediate reasoning, or including evidence published after the claim.