Papers with end-to-end hierarchical attention network

1 papers
Sentence-Level Evidence Embedding for Claim Verification with Hierarchical Attention Networks (P19-1)

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Challenge: Claim verification is cumbersome and inefficient for human fact-checkers to find consistent pieces of evidence.
Approach: They propose an end-to-end hierarchical attention network that learns to represent coherent evidence and their semantic relatedness with the claim.
Outcome: The proposed model outperforms state-of-the-art models on three datasets . it is based on a coherence-based attention layer and entailment-based one .

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