x-stance Data and code accompanying the paper "X-Stance: A Multilingual Multi-Target Dataset for Stance Detection". A high-level description can be found in the blog post, and a more detailed description in the
In: Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: Human language technologies. ACL, pp 1163–1168 Sobhani P, Inkpen D, Zhu X (2017) A dataset for multi-target stance detection. In: 15th conference of the European chapter of ...
(2017). A dataset for multi-target stance detection. In Proceedings of the 15th conference of the european chapter of the association for computational linguistics: volume 2, short papers. (pp. 551–557). Google Scholar Somasundaran and Wiebe, 2009 Somasundaran, S., & Wiebe, J. (2009). ...
Then connect it to a Bidirectional Long Short-Term Memory networks with target-specific attention mechanism. The experimental results show that our proposed model outperforms other baseline models in the SemEval-2016 stance detection dataset and achieves state-of-the-art performance....
In the same dataset, we estimated multi-unit spike rates in each of the 96 channels by summing up the multi-unit spikes with a 150-ms history every 0.5 ms. We used these multi-unit rates and the hotspot initiation events to calibrate a multi-class rLDA decoder23,33,35,36. Based ...
Among the target genes of these miRNAs, we found five upregulated genes in our snRNA-seq dataset are associated with neurodegenerative diseases, including Atcb, Elavl2, and Fgf1, which are associated with ALS. In addition, analysis of the intercellular communication between cell types also ...
The algorithm learns patterns within the dataset(s) and uses these patterns to make a maximum likelihood prediction about the outcome [32]. Some common ML algorithms include random forests [33], decision trees [34], support vector machines [35], k-means clustering [36], Multi Layer ...
Cheema GS, Hakimov S, Sittar A, et al (2022) Mm-claims: a dataset for multimodal claim detection in social media. arXiv preprint arXiv:2205.01989 Clark K, Luong MT, Le QV, et al (2020) Electra: Pre-training text encoders as discriminators rather than generators. arXiv preprint arXiv...
To address this, we introduce a new multimodal multi-turn conversational stance detection dataset (called MmMtCSD). To derive stances from this challenging dataset, we propose a novel multimodal large language model stance detection framework (MLLM-SD), that learns joint stance representations from ...
Paper tables with annotated results for ExaASC: A General Target-Based Stance Detection Corpus in Arabic Language