Georg Buscher — accepted AI-conference papers

2024

Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models

Ying-Chun Lin, Jennifer Neville, Jack Stokes, Longqi Yang, Tara Safavi, Mengting Wan +11

ACL 2024long

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…

Cited by 16 Source ↗PDF ↗code ↗Scholar ↗

2024

S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs

Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan, Jennifer Neville, Longqi Yang, Reid Andersen +2

ACL 2024findings

Traditional Dialogue State Tracking (DST) has focused on tracking preferences and intents in conversations centered around specific tasks (e.g. booking services). These conventional systems assume a relatively restricted conversation flow in which each turn gradually offers new information. However,…

Cited by 5 Source ↗PDF ↗Scholar ↗