TY - GEN
T1 - Continually Improving Extractive QA via Human Feedback
AU - Gao, Ge
AU - Chen, Hung Ting
AU - Artzi, Yoav
AU - Choi, Eunsol
N1 - Publisher Copyright:
©2023 Association for Computational Linguistics.
PY - 2023
Y1 - 2023
N2 - We study continually improving an extractive question answering (QA) system via human user feedback. We design and deploy an iterative approach, where information-seeking users ask questions, receive model-predicted answers, and provide feedback. We conduct experiments involving thousands of user interactions under diverse setups to broaden the understanding of learning from feedback over time. Our experiments show effective improvement from user feedback of extractive QA models over time across different data regimes, including significant potential for domain adaptation.
AB - We study continually improving an extractive question answering (QA) system via human user feedback. We design and deploy an iterative approach, where information-seeking users ask questions, receive model-predicted answers, and provide feedback. We conduct experiments involving thousands of user interactions under diverse setups to broaden the understanding of learning from feedback over time. Our experiments show effective improvement from user feedback of extractive QA models over time across different data regimes, including significant potential for domain adaptation.
UR - http://www.scopus.com/inward/record.url?scp=85184827005&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85184827005&partnerID=8YFLogxK
U2 - 10.18653/v1/2023.emnlp-main.27
DO - 10.18653/v1/2023.emnlp-main.27
M3 - Conference contribution
AN - SCOPUS:85184827005
T3 - EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings
SP - 406
EP - 423
BT - EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings
A2 - Bouamor, Houda
A2 - Pino, Juan
A2 - Bali, Kalika
PB - Association for Computational Linguistics (ACL)
T2 - 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023
Y2 - 6 December 2023 through 10 December 2023
ER -