Papers by Guangming Lu
Bidirectional Hierarchical Attention Networks based on Document-level Context for Emotion Cause Extraction (2021.findings-emnlp)
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| Challenge: | Emotion cause extraction (ECE) aims to extract the causes behind certain emotion in text. |
| Approach: | They propose a bidirectional hierarchical attention network corresponding to the specified candidate cause clause to capture document-level context in a structured and dynamic manner. |
| Outcome: | The proposed method achieves competitive performances on two public datasets in Chinese and English. |
UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion Recognition (2022.emnlp-main)
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| Challenge: | Existing studies study sentiment and emotion separately and do not fully exploit the complementary knowledge behind the two. |
| Approach: | They propose a multimodal sentiment knowledge-sharing framework that unifies MSA and ERC tasks from features, labels, and models. |
| Outcome: | The proposed framework achieves consistent improvements on four public benchmark datasets on MOSI, MOSEI, MELD, and IEMOCAP. |
Towards Mitigating Modality Bias in Vision-Language Models for Temporal Action Localization (2026.acl-long)
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| Challenge: | Existing vision-language models overemphasize linguistic priors, leading to modality bias. |
| Approach: | They propose a vision-language aggregation framework that mitigates modality bias in TAL by preserving vision as the dominant signal while adaptively exploiting language only when beneficial. |
| Outcome: | Experiments on THUMOS14 show that the proposed model outperforms state-of-the-art models by up to 3.2% mAP. |