Kai Sun, Seungwhan Moon, Paul Crook, Stephen Roller, Becka Silvert, Bing Liu, Zhiguang Wang, Honglei Liu, Eunjoon Cho, Claire Cardie
| Challenge: | Existing dialogue systems focus on functional goals, open-domain chatbots on socially engaging conversations. |
| Approach: | They propose to add chit-chat to ENhance Task-ORiented dialogues by a human-assisted data collection approach to augment task-oriented dialogues with minimal annotation effort. |
| Outcome: | The proposed models can code-switch between task and chit-chat to be more engaging, interesting, knowledgeable, and humanlike while maintaining competitive task performance. |
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KETOD: Knowledge-Enriched Task-Oriented Dialogue (2022.findings-naacl)
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| Challenge: | Existing studies treat task-oriented dialogue and chit-chat as separate domains . a new dataset is created to integrate both types of dialogue into a single system . |
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A Unifying View On Task-oriented Dialogue Annotation (2022.lrec-1)
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| Challenge: | Recent research attention in task-oriented dialogue systems focuses on end-to-end neural models. |
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| Challenge: | Recent work on end-to-end dialogue models with pre-trained dialogue corpora shows promising performance in the conversational system. |
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| Challenge: | Large language models (LLMs) are designed to handle complex task requests, but lack of specific datasets for training and evaluation of such systems . |
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Personalizing Dialogue Agents: I have a dog, do you have pets too? (P18-1)
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| Challenge: | chit-chat models lack specificity, do not display a consistent personality and are often not very captivating. |
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Grounding in social media: An approach to building a chit-chat dialogue model (2022.naacl-srw)
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| Challenge: | Existing open-domain dialogue models fail to capture and utilize external knowledge, leading to repetitive or generic responses to unseen utterances. |
| Approach: | They propose to use social media comments to improve the raw conversation ability of open-domain dialogue systems. |
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