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Found 5 papers, 2 papers with code
Active PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Training
To mitigate the impact of the scarcity of labelled data on fact-checking systems, we focus on few-shot claim verification.
Aggregating Pairwise Semantic Differences for Few-Shot Claim Veracity Classification
In this paper, we introduce SEED, a novel vector-based method to few-shot claim veracity classification that aggregates pairwise semantic differences for claim-evidence pairs.
Automated Fact-Checking: A Survey
As online false information continues to grow, automated fact-checking has gained an increasing amount of attention in recent years.
QMUL-SDS at SCIVER: Step-by-Step Binary Classification for Scientific Claim Verification
As a result, our team is the No.
Learning Safe Neural Network Controllers with Barrier Certificates
We provide a novel approach to synthesize controllers for nonlinear continuous dynamical systems with control against safety properties.
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