Follow
Ming Yin
Title
Cited by
Cited by
Year
Understanding the effect of accuracy on trust in machine learning models
M Yin, J Wortman Vaughan, H Wallach
Proceedings of the 2019 chi conference on human factors in computing systems …, 2019
5222019
Are explanations helpful? a comparative study of the effects of explanations in ai-assisted decision-making
X Wang, M Yin
Proceedings of the 26th International Conference on Intelligent User …, 2021
2482021
The communication network within the crowd
M Yin, ML Gray, S Suri, JW Vaughan
Proceedings of the 25th International Conference on World Wide Web, 1293-1303, 2016
1442016
Curiosity killed the cat, but makes crowdwork better
E Law, M Yin, J Goh, K Chen, MA Terry, KZ Gajos
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems …, 2016
1192016
Human reliance on machine learning models when performance feedback is limited: Heuristics and risks
Z Lu, M Yin
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021
992021
The effects of performance-contingent financial incentives in online labor markets
M Yin, Y Chen, YA Sun
Proceedings of the AAAI Conference on Artificial Intelligence 27 (1), 1191-1197, 2013
752013
When confidence meets accuracy: Exploring the effects of multiple performance indicators on trust in machine learning models
A Rechkemmer, M Yin
Proceedings of the 2022 chi conference on human factors in computing systems …, 2022
742022
Task complexity moderates group synergy
A Almaatouq, M Alsobay, M Yin, DJ Watts
Proceedings of the National Academy of Sciences 118 (36), e2101062118, 2021
602021
Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making
S Ma, Y Lei, X Wang, C Zheng, C Shi, M Yin, X Ma
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023
582023
Bonus or not? learn to reward in crowdsourcing.
M Yin, Y Chen
IJCAI, 201-208, 2015
552015
You’d better stop! Understanding human reliance on machine learning models under covariate shift
CW Chiang, M Yin
Proceedings of the 13th ACM Web Science Conference 2021, 120-129, 2021
462021
Running out of time: The impact and value of flexibility in on-demand crowdwork
M Yin, S Suri, ML Gray
Proceedings of the 2018 CHI conference on human factors in computing systems …, 2018
432018
Monetary interventions in crowdsourcing task switching
M Yin, Y Chen, YA Sun
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 …, 2014
422014
Understanding the skill provision in gig economy from a network perspective: A case study of fiverr
K Huang, J Yao, M Yin
Proceedings of the ACM on Human-Computer Interaction 3 (CSCW), 1-23, 2019
392019
Synthetic data generation with large language models for text classification: Potential and limitations
Z Li, H Zhu, Z Lu, M Yin
Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023
382023
Exploring the effects of machine learning literacy interventions on laypeople’s reliance on machine learning models
CW Chiang, M Yin
Proceedings of the 27th International Conference on Intelligent User …, 2022
342022
Effects of explanations in ai-assisted decision making: Principles and comparisons
X Wang, M Yin
ACM Transactions on Interactive Intelligent Systems 12 (4), 1-36, 2022
322022
Will you accept the ai recommendation? predicting human behavior in ai-assisted decision making
X Wang, Z Lu, M Yin
Proceedings of the ACM web conference 2022, 1697-1708, 2022
302022
Leveraging peer communication to enhance crowdsourcing
W Tang, M Yin, CJ Ho
The World Wide Web Conference, 1794-1805, 2019
252019
Are two heads better than one in ai-assisted decision making? comparing the behavior and performance of groups and individuals in human-ai collaborative recidivism risk assessment
CW Chiang, Z Lu, Z Li, M Yin
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems …, 2023
242023
The system can't perform the operation now. Try again later.
Articles 1–20