mlsanityData to 7 Oct 2026

Automatic Stance Detection Using End-to-End Memory Networks

arXiv 1804.07581 ↗First posted 20 Apr 2018cs.CLcited by 14

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Abstract (arXiv)

We present a novel end-to-end memory network for stance detection, which jointly (i) predicts whether a document agrees, disagrees, discusses or is unrelated with respect to a given target claim, and also (ii) extracts snippets of evidence for that prediction. The network operates at the paragraph level and integrates convolutional and recurrent neural networks, as well as a similarity matrix as part of the overall architecture. The experimental evaluation on the Fake News Challenge dataset shows state-of-the-art performance.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Apr 2018.

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Citing papers per year: 2021: 10; 2022: 2; 2023: 1; 2024: 1.

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