Claim Verification
63 papers with code • 1 benchmarks • 2 datasets
Most implemented papers
FEVER: a large-scale dataset for Fact Extraction and VERification
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
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
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
The increasing concern with misinformation has stimulated research efforts on automatic fact checking.
BERT for Evidence Retrieval and Claim Verification
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
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
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
Automated fact-checking systems verify claims against evidence to predict their veracity.
DialFact: A Benchmark for Fact-Checking in Dialogue
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
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.