FIELD NOTES TOPIC

dialogue systems

5 notes, newest first.

  1. Preference Tree Optimization: Enhancing Goal-Oriented Dialogue with Look-Ahead Simulations

    Source note ·

    The research presents a new framework called Preference Tree Optimization (PTO) for enhancing dialogue systems in specialized domains with limited data. It focuses on Motivational Interviewing (MI), a counseling…

  2. Preference Tree Optimization: Enhancing Goal-Oriented Dialogue with Look-Ahead Simulations

    Source note ·

    Researchers propose Preference Tree Optimization (PTO), a framework that enhances dialogue systems in specialized domains like Motivational Interviewing by using preference data generated through Look-Ahead Simulations…

  3. Cognitive-structured Multimodal Agent for Multimodal Understanding, Generation, and Editing

    Source note ·

    Researchers have proposed a new type of multimodal agent called the Cognitive-structured Multimodal Agent. This agent is designed to improve long-horizon multimodal dialogue by externalizing visual information into an…

  4. Accuracy and Satisfaction in Multi-Turn LLM Dialogues for NFR Assessment

    Source note ·

    Researchers evaluate the accuracy and quality of conversations between developers and a Language Model (LLM)-based agent in the context of Health Insurance Portability and Accountability Act (HIPAA) regulatory…

  5. Accuracy and Satisfaction in Multi-Turn LLM Dialogues for NFR Assessment

    Source note ·

    Researchers examined the accuracy of Large Language Model (LLM)-based dialogue assistants in handling Non-Functional Requirements (NFRs) related to Health Insurance Portability and Accountability Act (HIPAA) regulatory…