Papers Few-Shot Stance Detection

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

For a viewpoint-diverse news recommender, identifying whether two news articles express the same viewpoint is essential. One way to determine "same or different" viewpoint is stance detection. In this paper, we investiga…

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

Social media platforms are rich sources of opinionated content. Stance detection allows the automatic extraction of users' opinions on various topics from such content. We focus on zero-shot stance detection, where the m…

SocialPET: Socially Informed Pattern Exploiting Training for Few-Shot Stance Detection in Social Media

Stance detection, as the task of determining the viewpoint of a social media post towards a target as 'favor' or 'against', has been understudied in the challenging yet realistic scenario where there is limited labeled d…

Target Really Matters: Target-aware Contrastive Learning and Consistency Regularization for Few-shot Stance Detection

Stance detection aims to identify the attitude from an opinion towards a certain target. Despite the significant progress on this task, it is extremely time-consuming and budget-unfriendly to collect sufficient high-qual…

Few-Shot Stance Detection via Target-Aware Prompt Distillation

Stance detection aims to identify whether the author of a text is in favor of, against, or neutral to a given target. The main challenge of this task comes two-fold: few-shot learning resulting from the varying targets a…

Infusing Knowledge from Wikipedia to Enhance Stance Detection

Stance detection infers a text author's attitude towards a target. This is challenging when the model lacks background knowledge about the target. Here, we show how background knowledge from Wikipedia can help enhance th…

Enhancing Zero-shot and Few-shot Stance Detection with Commonsense Knowledge Graph