Papers with task-oriented systems

3 papers
Adding Chit-Chat to Enhance Task-Oriented Dialogues (2021.naacl-main)

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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.
Combining Discourse Coherence with Large Language Models for More Inclusive, Equitable, and Robust Task-Oriented Dialogue (2024.lrec-main)

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Challenge: Large language models (LLMs) are capable of generating well-formed responses, but they struggle in goal-oriented settings.
Approach: They propose a discourse-aware multimodal task-oriented dialogue system that combines discourse theories with offline LLM generation.
Outcome: The proposed system reduces misunderstandings in the dialect of African-American Vernacular English from 93% to 57%.
Japanese Dialogue Corpus of Information Navigation and Attentive Listening Annotated with Extended ISO-24617-2 Dialogue Act Tags (L18-1)

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Challenge: Large-scale conventional dialogue corpora are mainly built for specified tasks with specially designed dialogue states.
Approach: They propose to annotate large-scale dialogue data with an extended ISO-24617-2 dialogue act tag-set to model a natural conversation with machines.
Outcome: The proposed corpus covers a wider range of dialogue tasks than existing task-oriented systems or text-chat systems.

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