Summary of Dynamic Demonstration Retrieval and Cognitive Understanding For Emotional Support Conversation, by Zhe Xu et al.
Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation
by Zhe Xu, Daoyuan Chen, Jiayi Kuang, Zihao Yi, Yaliang Li, Ying Shen
First submitted to arxiv on: 3 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel approach called Dynamic Demonstration Retrieval and Cognitive-Aspect Situation Understanding (ourwork) to enhance emotional support conversation systems. The system uses dynamic demonstration retrieval to select personalized and informative demonstration pairs, while also utilizing cognitive relationships from the ATOMIC knowledge source to deepen situational awareness of help-seekers’ mental states. The supportive decoder integrates information from diverse knowledge sources, enabling empathetic and cognitively aware response generation. The effectiveness of ourwork is demonstrated through automatic and human evaluations, showing substantial improvements over state-of-the-art models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps create better conversation systems that understand people’s emotions and provide support when needed. The system uses a new way to find the right examples to help with conversations, while also understanding people’s thoughts and feelings. This is done by combining information from different sources to generate responses that are both empathetic and helpful. The results show that this approach works well and can improve conversation quality. |
Keywords
* Artificial intelligence * Decoder
