Fact Extraction and VERification baseline published in NAACL2018
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Updated
Feb 3, 2023 - Python
Fact Extraction and VERification baseline published in NAACL2018
Symmetric evaluation set based on the FEVER (fact verification) dataset
An automated solution for fact-checking using available claims and fake-news datasets to fine-tune state-of-the-art language models published recently for NLP tasks (BERT, RoBERTa, XLNet, ConvBERT...) in order to classify unseen claims.
📄 Evidence Retrieval and Claim Verification for the FEVER shared task using Transformer Networks
FEVER<->Threat Bus connector
Fever, Python, Hexagonal Architecture, Redis
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