Papers with Attention visualization
Infusing Context and Knowledge Awareness in Multi-turn Dialog Understanding (2023.findings-eacl)
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| Challenge: | Existing work on multi-turn dialog understanding does not model multi-turned dynamics, instead leaving them for updating dialog states only. |
| Approach: | They propose to equip a BERT-based framework with knowledge and context awareness to model multi-turn dialog dynamics by detecting intents and slots within each user utterance. |
| Outcome: | The proposed framework can detect intents and slots within a dialog and extract key slot information as 'semantic frames' however, humans usually associate relevant background knowledge with the current dialog contexts to better illustrate slot semantics revealed from word connotations . |
CogBERT: Cognition-Guided Pre-trained Language Models (2022.coling-1)
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| Challenge: | Existing methods fine-tune pre-trained models on cognitive data, ignoring the semantic gap between texts and cognitive signals. |
| Approach: | They propose a framework that can induce fine-grained cognitive features from cognitive data and incorporate them into pre-trained language models by adaptively adjusting the weight of cognitive features for different NLP tasks. |
| Outcome: | The proposed framework can induce fine-grained cognitive features from cognitive data and incorporate them into BERT by adaptively adjusting weight of cognitive features for different NLP tasks. |