Research map / Label-efficient and robust learning / Recognition and long-tail
Structural Correspondence Learning for Cross-Lingual Sentiment Classification with One-to-Many Mappings
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use distributed representations to create one-to-many pivot mappings instead of one-to-one translations | CL-SCL · NLP&CC 2013 Books | accuracy: 0.780 -> 0.829 | Helped |
| Use distributed representations to create one-to-many pivot mappings instead of one-to-one translations | CL-SCL · NLP&CC 2013 DVD | accuracy: 0.772 -> 0.826 | Helped |
| Use distributed representations to create one-to-many pivot mappings instead of one-to-one translations | CL-SCL · NLP&CC 2013 Music | accuracy: 0.739 -> 0.787 | Helped |
| Use distributed representations to create one-to-many pivot mappings instead of one-to-one translations | CL-SCL · NLP&CC 2013 average | accuracy: 0.763 -> 0.814 | Helped |
| Tune the number of pivots and cross-lingual representation dimension (ablation) | SCL-OM · NLP&CC 2013 DVD | accuracy: 0.826 -> 0.833 | Helped |
| Increase cross-lingual representation dimension k (ablation) | SCL-OM · NLP&CC 2013 all categories | accuracy | Mixed |
| Vary the number of pivots m (ablation) | SCL-OM · NLP&CC 2013 all categories | accuracy | No clear effect |
Closest papers by meaning
- Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification (AAAI 2020 · similarity 0.88)
- Massively Multilingual Corpus of Sentiment Datasets and Multi-faceted Sentiment Classification Benchmark (NeurIPS 2023 · similarity 0.86)
- Cross-Lingual Propagation for Deep Sentiment Analysis (AAAI 2018 · similarity 0.86)
- Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities (AAAI 2019 · similarity 0.85)
- Transfer Learning for Cross-Language Text Categorization through Active Correspondences Construction (AAAI 2016 · similarity 0.85)
- Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-training (AAAI 2022 · similarity 0.84)
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