Meta-learning with topic-agnostic representations for zero-shot stance detection-Reference-Cited by-同舟云学术

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Meta-learning with topic-agnostic representations for zero-shot stance detection

Published:2023-07 Issue: Volume:171 Page:15-20
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Choi Kyuri,Ko Youngjoong^ORCID

Funder

NRF

IITP

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference33 articles.

1. Stance detection: concepts, approaches, resources, and outstanding issues;Küçük,2021

2. Semeval-2016 task 6: detecting stance in tweets;Mohammad,2016

3. Stance and sentiment in tweets;Mohammad;ACM Trans. Internet Technol. (TOIT),2017

4. Integrating transformers and knowledge graphs for twitter stance detection;Clark,2021

5. Zero-shot learning by convex combination of semantic embeddings;Norouzi;arXiv preprint arXiv:1312.5650,2013

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A meta-contrastive learning with data augmentation framework for zero-shot stance detection;Expert Systems with Applications;2024-09

2. Spatial-angular interaction for arbitrary scale light field reconstruction;Multimedia Tools and Applications;2024-03-11

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