Document detail
ID
oai:arXiv.org:2403.12388
Topic
Computer Science - Information Ret... Computer Science - Artificial Inte...Author
Lin, Ying-Chun Neville, Jennifer Stokes, Jack W. Yang, Longqi Safavi, Tara Wan, Mengting Counts, Scott Suri, Siddharth Andersen, Reid Xu, Xiaofeng Gupta, Deepak Jauhar, Sujay Kumar Song, Xia Buscher, Georg Tiwary, Saurabh Hecht, Brent Teevan, JaimeCategory
Computer Science
Year
2024
listing date
6/12/2024
Keywords
systems conversational satisfaction userAbstract
Accurate and interpretable user satisfaction estimation (USE) is critical for understanding, evaluating, and continuously improving conversational systems.
Users express their satisfaction or dissatisfaction with diverse conversational patterns in both general-purpose (ChatGPT and Bing Copilot) and task-oriented (customer service chatbot) conversational systems.
Existing approaches based on featurized ML models or text embeddings fall short in extracting generalizable patterns and are hard to interpret.
In this work, we show that LLMs can extract interpretable signals of user satisfaction from their natural language utterances more effectively than embedding-based approaches.
Moreover, an LLM can be tailored for USE via an iterative prompting framework using supervision from labeled examples.
The resulting method, Supervised Prompting for User satisfaction Rubrics (SPUR), not only has higher accuracy but is more interpretable as it scores user satisfaction via learned rubrics with a detailed breakdown.
Lin, Ying-Chun,Neville, Jennifer,Stokes, Jack W.,Yang, Longqi,Safavi, Tara,Wan, Mengting,Counts, Scott,Suri, Siddharth,Andersen, Reid,Xu, Xiaofeng,Gupta, Deepak,Jauhar, Sujay Kumar,Song, Xia,Buscher, Georg,Tiwary, Saurabh,Hecht, Brent,Teevan, Jaime, 2024, Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models
A Novel MR Imaging Sequence of 3D-ZOOMit Real Inversion-Recovery Imaging Improves Endolymphatic Hydrops Detection in Patients with Ménière Disease
ménière disease p < detection imaging sequences 3d-zoomit 3d endolymphatic real tse reconstruction ir inversion-recovery hydrops ratio
