LG-CoTrain, an LLM-guided co-training method, outperforms classical semi-supervised baselines for crisis tweet classification in low-resource settings with 5-25 labeled examples per class.
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3 Pith papers cite this work, alongside 5,604 external citations. Polarity classification is still indexing.
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representative citing papers
DeluluNet enables continued prediction under modality substitution, addition, or subsets by training a multi-modal model from a unimodal teacher and unlabeled multimodal data via modality hallucination.
Multimodal training with attention and contrastive multi-view learning improves both combined and acoustic-only emotion recognition on IEMOCAP over prior acoustic baselines.
citing papers explorer
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LLM-guided Semi-Supervised Approaches for Social Media Crisis Data Classification
LG-CoTrain, an LLM-guided co-training method, outperforms classical semi-supervised baselines for crisis tweet classification in low-resource settings with 5-25 labeled examples per class.
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Changing Modalities: Adapting Remote Sensing Models to New Satellites and Sensors
DeluluNet enables continued prediction under modality substitution, addition, or subsets by training a multi-modal model from a unimodal teacher and unlabeled multimodal data via modality hallucination.
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Multimodal and Multi-view Models for Emotion Recognition
Multimodal training with attention and contrastive multi-view learning improves both combined and acoustic-only emotion recognition on IEMOCAP over prior acoustic baselines.