Zero-shot stance detection based on multi-expert collaboration
Author:
Funder
Shandong Women’s University
Tibetan information processing and Machine Translation Key Laboratory
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-68870-1.pdf
Reference30 articles.
1. Augenstein, I., Rocktäschel, T., Vlachos, A. & Bontcheva, K. Stance detection with bidirectional conditional encoding. arXiv preprint arXiv:1606.05464 (2016).
2. Jang, M. & Allan, J. Explaining controversy on social media via stance summarization. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval 1221–1224 (2018).
3. Mohammad, S., Kiritchenko, S., Sobhani, P., Zhu, X. & Cherry, C. Semeval-2016 task 6: Detecting stance in tweets. In Proceedings of the 10th international workshop on semantic evaluation (SemEval-2016) 31–41 (2016).
4. Mohtarami, M. et al. Automatic stance detection using end-to-end memory networks. arXiv preprint arXiv:1804.07581 (2018).
5. Allaway, E. & McKeown, K. Zero-shot stance detection: A dataset and model using generalized topic representations. arXiv preprint arXiv:2010.03640 (2020).
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