# Cross-Target Stance Classification with Self-Attention Networks

arXiv: https://arxiv.org/abs/1805.06593 · HTML: https://mlsanity.com/paper/1805.06593/

## Key facts

- Cited by 41 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 May 2018.

## Built on by (most cited first, 30 of 41)

- [State-of-the-art generalisation research in NLP: A taxonomy and review](https://mlsanity.com/paper/2210.03050/) (2022)
- [How would Stance Detection Techniques Evolve after the Launch of ChatGPT?](https://mlsanity.com/paper/2212.14548/) (2022)
- [Stance Detection with Collaborative Role-Infused LLM-Based Agents](https://mlsanity.com/paper/2310.10467/) (2023)
- [Adversarial Learning for Zero-Shot Stance Detection on Social Media](https://mlsanity.com/paper/2105.06603/) (2021)
- [Investigating Chain-of-thought with ChatGPT for Stance Detection on Social Media](https://mlsanity.com/paper/2304.03087/) (2023)
- [KCD: Knowledge Walks and Textual Cues Enhanced Political Perspective Detection in News Media](https://mlsanity.com/paper/2204.04046/) (2022)
- [Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes](https://mlsanity.com/paper/2105.07571/) (2021)
- [Exploiting Sentiment and Common Sense for Zero-shot Stance Detection](https://mlsanity.com/paper/2208.08797/) (2022)
- [Zero-Shot Conversational Stance Detection: Dataset and Approaches](https://mlsanity.com/paper/2506.17693/) (2025)
- [Cross-target Stance Detection by Exploiting Target Analytical Perspectives](https://mlsanity.com/paper/2401.01761/) (2024)
- [Few-shot Learning for Cross-Target Stance Detection by Aggregating Multimodal Embeddings](https://mlsanity.com/paper/2301.04535/) (2023)
- [Opinions are Made to be Changed: Temporally Adaptive Stance Classification](https://mlsanity.com/paper/2108.12476/) (2021)
- [Contextual information integration for stance detection via cross-attention](https://mlsanity.com/paper/2211.01874/) (2022)
- [Stanceformer: Target-Aware Transformer for Stance Detection](https://mlsanity.com/paper/2410.07083/) (2024)
- [C-MTCSD: A Chinese Multi-Turn Conversational Stance Detection Dataset](https://mlsanity.com/paper/2504.09958/) (2025)
- [How to Handle Different Types of Out-of-Distribution Scenarios in Computational Argumentation? A Comprehensive and Fine-Grained Field Study](https://mlsanity.com/paper/2309.08316/) (2023)
- ["A Tale of Two Movements": Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Prediction](https://mlsanity.com/paper/2310.07155/) (2023)
- [TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings](https://mlsanity.com/paper/2310.14450/) (2023)
- [Cross-Target Stance Detection: A Survey of Techniques, Datasets, and Challenges](https://mlsanity.com/paper/2409.13594/) (2024)
- [Semi-supervised Stance Detection of Tweets Via Distant Network Supervision](https://mlsanity.com/paper/2201.00614/) (2022)
- [A Logically Consistent Chain-of-Thought Approach for Stance Detection](https://mlsanity.com/paper/2312.16054/) (2023)
- [EDDA: A Encoder-Decoder Data Augmentation Framework for Zero-Shot Stance Detection](https://mlsanity.com/paper/2403.15715/) (2024)
- [MSME: A Multi-Stage Multi-Expert Framework for Zero-Shot Stance Detection](https://mlsanity.com/paper/2512.04492/) (2025)
- [Relative Counterfactual Contrastive Learning for Mitigating Pretrained Stance Bias in Stance Detection](https://mlsanity.com/paper/2405.10991/) (2024)
- [Adversarial Learning-based Stance Classifier for COVID-19-related Health Policies](https://mlsanity.com/paper/2209.04631/) (2022)
- [Zero-shot stance detection based on cross-domain feature enhancement by contrastive learning](https://mlsanity.com/paper/2210.03380/) (2022)
- [Explaining Search Result Stances to Opinionated People](https://mlsanity.com/paper/2309.08460/) (2023)
- [SocialPET: Socially Informed Pattern Exploiting Training for Few-Shot Stance Detection in Social Media](https://mlsanity.com/paper/2403.05216/) (2024)
- [Investigating the Robustness of Modelling Decisions for Few-Shot Cross-Topic Stance Detection: A Preregistered Study](https://mlsanity.com/paper/2404.03987/) (2024)
- [Zero-shot Cross-lingual Stance Detection via Adversarial Language Adaptation](https://mlsanity.com/paper/2404.14339/) (2024)

## Abstract (arXiv)

In stance classification, the target on which the stance is made defines the boundary of the task, and a classifier is usually trained for prediction on the same target. In this work, we explore the potential for generalizing classifiers between different targets, and propose a neural model that can apply what has been learned from a source target to a destination target. We show that our model can find useful information shared between relevant targets which improves generalization in certain scenarios.