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Large-scale Hybrid Approach for Predicting User Satisfaction with
  Conversational Agents

Large-scale Hybrid Approach for Predicting User Satisfaction with Conversational Agents

29 May 2020
Dookun Park
Haonan Yuan
Dongmin Kim
Yinglei Zhang
Matsoukas Spyros
Young-Bum Kim
R. Sarikaya
Edward Guo
Yuan Ling
Kevin Quinn
P. Hung
Benjamin Yao
Sungjin Lee
    LLMAG
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Papers citing "Large-scale Hybrid Approach for Predicting User Satisfaction with Conversational Agents"

4 / 4 papers shown
Title
Modeling User Satisfaction Dynamics in Dialogue via Hawkes Process
Modeling User Satisfaction Dynamics in Dialogue via Hawkes Process
Fanghua Ye
Zhiyuan Hu
Emine Yilmaz
26
6
0
21 May 2023
Scalable and Robust Self-Learning for Skill Routing in Large-Scale
  Conversational AI Systems
Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems
Mohammad Kachuee
Jinseok Nam
Sarthak Ahuja
J. Won
Sungjin Lee
29
5
0
14 Apr 2022
Deciding Whether to Ask Clarifying Questions in Large-Scale Spoken
  Language Understanding
Deciding Whether to Ask Clarifying Questions in Large-Scale Spoken Language Understanding
Joo-Kyung Kim
Guoyin Wang
Sungjin Lee
Young-Bum Kim
14
9
0
25 Sep 2021
Self-Supervised Contrastive Learning for Efficient User Satisfaction
  Prediction in Conversational Agents
Self-Supervised Contrastive Learning for Efficient User Satisfaction Prediction in Conversational Agents
Mohammad Kachuee
Hao Yuan
Young-Bum Kim
Sungjin Lee
27
25
0
21 Oct 2020
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