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Ming Yin
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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
5872019
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
3072021
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
1502016
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
1212021
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
1212016
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
932023
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
912022
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
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
722023
Task complexity moderates group synergy
A Almaatouq, M Alsobay, M Yin, DJ Watts
Proceedings of the National Academy of Sciences 118 (36), e2101062118, 2021
712021
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
542021
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
502018
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
432019
Monetary interventions in crowdsourcing task switching
M Yin, Y Chen, YA Sun
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 …, 2014
432014
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
422022
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
422022
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
412022
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
382023
The effects of AI-based credibility indicators on the detection and spread of misinformation under social influence
Z Lu, P Li, W Wang, M Yin
Proceedings of the ACM on Human-Computer Interaction 6 (CSCW2), 1-27, 2022
302022
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