Showing results 1 - 10 of 10
2024, Paper: "Comparison data elicited from people are fundamental to many machine learning tasks, including reinforcement learning from human feedback for large language models…
June 24, 2021, Paper: "There is evidence that prediction markets are useful tools to aggregate information on researchers’ beliefs about scientific results including the outcome…
Using prediction markets to predict the outcomes in DARPA’s Next Generation Social Science program
2020, Paper, "There is evidence that prediction markets are useful tools to aggregate information about researchers’ beliefs about scientific results including forecasting the…
Welfare and Distributional Impacts of Fair Classification. Yiling Chen, 2018, Paper, "Current methodologies in machine learning analyze the effects of various statistical…
A Short-term Intervention for Long-term Fairness in the Labor Market. Lily Hu, Yiling Chen, November 30, 2017, Paper, "The persistence of racial inequality in the U.S. labor…
Fairness at Equilibrium in the Labor Market. Yiling Chen, July 5, 2017, Paper, "Recent literature on computational notions of fairness has been broadly divided into two…
Learning to Incentivize: Eliciting Effort via Output Agreement. Yang Liu, Yiling Chen, April 19, 2016, Paper. "In crowdsourcing when there is a lack of verification for…
Market Manipulation with Outside Incentives. Yiling Chen, March 1, 2014, Paper. "Much evidence has shown that prediction markets can effectively aggregate dispersed information…
The Effects of Performance-Contingent Financial Incentives in Online Labor Markets. Yiling Chen, July 2013, Paper. "Online labor markets such as Amazon Mechanical Turk (MTurk)…
What you jointly know determines how you act: strategic interactions in prediction markets. Yiling Chen, June 2013, Paper. "The primary goal of a prediction market is to elicit…