Papers with Dual Attention
End-to-end Spoken Conversational Question Answering: Task, Dataset and Model (2022.findings-naacl)
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| Challenge: | Existing methods for conversational question answering significantly degrade on datasets . a new task aims to enable systems to model complex dialogues flow given the speech documents . |
| Approach: | They propose a new Spoken Conversational Question Answering task to model human conversations . they propose DDNet, which ingests cross-modal information to achieve fine-grained representations of speech and language modalities. |
| Outcome: | The proposed method achieves superior performance in spoken conversational question answering. |
DABERT: Dual Attention Enhanced BERT for Semantic Matching (2022.coling-1)
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| Challenge: | Existing models for semantic sentence matching lack the ability to capture subtle differences. |
| Approach: | They propose to use a Transformer-based pre-trained language model to capture fine-grained differences in sentence pairs by introducing a dual attention module and a fusion module to learn the aggregation of difference and affinity features. |
| Outcome: | The proposed method is able to capture fine-grained differences in sentence pairs. |