May 11, 2022 · In this paper, we introduce SEED, a novel vector-based method to few-shot claim veracity classification that aggregates pairwise semantic differences for claim ...
Missing: verification. | Show results with:verification.
Oct 25, 2022 · As part of an automated fact-checking pipeline, the claim verification task consists in determining if a claim is supported by an associated ...
SEED is introduced, a novel vector-based method to few-shot claim veracity classification that aggregates pairwise semantic differences for claim-evidence ...
Sep 8, 2024 · We build on the hypothesis that we can simulate class representative vectors that capture average semantic differences for claim-evidence pairs ...
Experiments conducted on the FEVER and SCIFACT datasets show consistent improvements over competitive baselines in few-shot settings. Our code is available.
Semantic Embedding Element-wise Difference (SEED), a novel vector-based method to few-shot claim verification that aggregates pairwise semantic differences ...
In this article, we introduce Semantic Embedding Element-wise Difference (SEED), a novel vector-based method to few-shot claim verification that aggregates ...
Aggregating pairwise semantic differences for few-shot claim verification ; Volume. 8 ; DOI. 10.7717/peerj-cs.1137 ; Journal. PEERJ COMPUTER SCIENCE ; Metadata.
We build on the hypothesis that we can simulate class representative vectors that capture average semantic differences for claim-evidence pairs in a class, ...
It provides sufficient field background and context on fact verification and corresponding few-shot setting. The article structure, figures, and data can ...