Papers with two-stream model
Dynamic Regularization in UDA for Transformers in Multimodal Classification (2023.acl-long)
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| Challenge: | Multimodal machine learning is a cutting-edge field that explores ways to combine information from multiple sources into models. |
| Approach: | They propose a multimodal BERT-ViT model that exploits weaker modality while regularizing the loss function. |
| Outcome: | The proposed model exploits weaker modality while regularizing the loss function. |
View Dialogue in 2D: A Two-stream Model in Time-speaker Perspective for Dialogue Summarization and beyond (2022.coling-1)
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| Challenge: | Existing models for dialogue summarization focus on document summarizing on time and speaker-centered points, but this approach is limited in understanding the dialogue. |
| Approach: | They propose a 2D view of dialogue based on a time-speaker perspective where the time and speaker streams of dialogue can be obtained as strengthened input. |
| Outcome: | The proposed model outperforms existing models on the QMSum dataset and improves summary faithfulness and human evaluation. |