natural-language-processing-11

Few-Shot Stance Detection

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Infusing Knowledge from Wikipedia to Enhance Stance Detection

Zihao He, Negar Mokhberian, Kristina Lerman•Thu Apr 07 2022

This work introduces Wikipedia Stance Detection BERT (WS-BERT) that infuses the knowledge from Wikipedia into stance encoding and significantly outperforms the state-of-the-art methods on target-specific stance detection, cross-target stance detection and zero/few-shot stance detection.

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Investigating the Robustness of Modelling Decisions for Few-Shot Cross-Topic Stance Detection: A Preregistered Study

Myrthe Reuver, Suzan Verberne, Antske Fokkens•Thu Apr 04 2024

The robustness of operationalization choices for few-shot stance detection is investigated, with special attention to modelling stance across different topics, and cross-encoding out-performs bi-encoding and adding NLI training to models gives considerable improvement.

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Stance Reasoner: Zero-Shot Stance Detection on Social Media with Explicit Reasoning

E. Milios, Maksym Taranukhin, Vered Shwartz•Thu Mar 21 2024

An approach to zero-shot stance detection on social media that leverages explicit reasoning over background knowledge to guide the model’s inference about the document’s stance on a target, and uses a pre-trained language model as a source of world knowledge to generate intermediate reasoning steps.

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