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LLM and Natural Language Interaction / Dialogue System Management and Error Handling

When users are dissatisfied with dialogue system responses, the system cannot flexibly adjust response strategies.

lightbulbPractical problemDialogue System Management and Error Handling

When users are dissatisfied with dialogue system responses, the system cannot flexibly adjust response strategies.

UbiComp '21Adaptor: A Real-time Module for a Conversational Agent to Adapt Policy Based on Negative User Behavior

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lightbulbPractical problemDialogue System Management and Error Handling

Older adults struggle to find suitable opportunities and partners for reminiscence conversations.

CHI '25Chorus of the Past: Toward Designing a Multi-agent Conversational Reminiscence System with Digital Artifacts for Older Adults

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Voice ordering systems in the restaurant industry often cause poor customer experience due to recognition errors.

CHI '25Diagnosing and Prioritizing Issues in Automated Order-Taking Systems: A Machine-Assisted Error Discovery Approach

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In multitask dialogue, listeners missing content can cause misunderstandings or communication breakdowns.

IUI '24SCAINs Presenter: Preventing Miscommunication by Detecting Context-Dependent Utterances in Spoken Dialogue

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Lay users cannot efficiently extract and utilize information from online tabular data.

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Users feel frustrated when AI refuses requests and struggle to understand the reasons for refusal.

CHI '24“As an AI language model, I cannot”: Investigating LLM Denials of User Requests

lightbulbPractical problemDialogue System Management and Error Handling

Existing conversational systems cannot naturally switch between chat and task-processing modes, degrading user experience.

CUI '23Unified Conversational Models with System-Initiated Transitions between Chit-Chat and Task-Oriented Dialogues

Related papers

Chorus of the Past: Toward Designing a Multi-agent Conversational Reminiscence System with Digital Artifacts for Older Adults

Jingwei Sun, Zhongyue Zhang, Mengyang Wang

Diagnosing and Prioritizing Issues in Automated Order-Taking Systems: A Machine-Assisted Error Discovery Approach

Maeda F Hanafi, Frederick Reiss, Yannis Katsis

SCAINs Presenter: Preventing Miscommunication by Detecting Context-Dependent Utterances in Spoken Dialogue

Aoto Tsuchiya, Tomoyuki Maekawa, Michita Imai

“As an AI language model, I cannot”: Investigating LLM Denials of User Requests

Joel Wester, Tim Schrills, Henning Pohl

Unified Conversational Models with System-Initiated Transitions between Chit-Chat and Task-Oriented Dialogues

Ye Liu, Stefan Ultes, Wolfgang Minker