Yiling Chen

Gordon McKay Professor of Computer Science @ Harvard

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Publications

2025

• Tao Lin and Yiling Chen. Generalized Principal-Agent Problem with a Learning Agent. In Proc. of the Thirteenth International Conference on Learning Representations (ICLR), April 2025.
• Safwan Hossain, Evi Micha, Yiling Chen, and Ariel Procaccia. Strategic Classification with Externalities. In Proc. of the Thirteenth International Conference on Learning Representations (ICLR), April 2025.

2024

• Yiling Chen, Shi Feng, Fang-Yi Yu. Carrot and Stick: Eliciting Comparison Information and Beyond. In Proc. of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), December 2024.
• Yiling Chen, Tao Lin, Ariel D. Procaccia, Aaditya Ramdas, Itai Shapira. Bias Detection via Signaling. In Proc. of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), December 2024.
• Tao Lin, Kun Jin, Andrew Estornell, Xiaoying Zhang, Yiling Chen, Yang Liu. User-Creator Feature Polarization in Recommender Systems with Dual Influence. In Proc. of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), December 2024.
• Yiling Chen and Fang-Yi Yu. Optimal Scoring Rule Design Under Partial Knowledge. In Proc. of the Twentieth Conference on Web and Internet Economics (WINE), December 2024. 
• Felix Holzmeister, Magnus Johannesson, Colin F. Camerer, Yiling Chen, Teck-Hua Ho, Suzanne Hoogeveen, Juergen Huber, Noriko Imai, Taisuke Imai, Lawrence Jin, Michael Kirchler, Alexander Ly, Benjamin Mandl, Dylan Manfredi, Gideon Nave, Brian A. Nosek, Thomas Pfeiffer, Alexandra Sarafoglou, Rene Schwaiger, Eric-Jan Wagenmakers, Viking Waldén, and Anna Dreber. Examining the Replicability of Online Experiments Selected by A Decision Market. Nature Human Behavior, November 2024. 
• Safwan Hossain and Yiling Chen. Equilibrium of Data Markets with Externality. In Proc. of the Forty-first International Conference on Machine Learning (ICML), July 2024.
• Safwan Hossain, Andjela Mladenovia, Yiling Chen, and Gauthier Gidel. A Persuasive Approach to Combating Misinformation. In Proc. of the Forty-first International Conference on Machine Learning (ICML), July 2024.
• Safwan Hossain, Tonghan Wang, Tao Lin, Yiling Chen, David C. Parkes, and Haifeng Xu. Multi-Sender Persuasion – A Computational Perspective. In Proc. of the Forty-first International Conference on Machine Learning (ICML), July 2024.
• Edwin Zhang, Jiayi (Sadie) Zhao, Tonghan Wang, Safwan Hossain, Henry Gasztowtt, Stephan Zhang, David C. Parkes, Milind Tambe, and Yiling Chen. Social Environment Design. In Proc. of the Forty-first International Conference on Machine Learning (ICML), July 2024. 

2023

• Tao Lin and Yiling Chen. Sample Complexity of Forecast Aggregation. In Proc. of the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), December 2023. (Spotlight paper)
• Gali Noti and Yiling Chen. Learning When to Advise Human Decision Makers. In Proc. of the Thirty-second International Joint Conference on Artificial Intelligence (IJCAI), August 2023. [arXiv, dataset] 

2022

• Shi Feng, Fang-Yi Yu, and Yiling Chen. Peer Prediction for Learning Agents. In Proc. of the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), December 2022.
• Yang Liu, Juntao Wang and Yiling Chen. Surrogate Scoring Rules. ACM Transactions on Economics and Computation, October 2022. (Supersedes the ACM EC’20 paper below.)
• Michael Gordon, Michael Bishop, Yiling Chen, Anna Dreber, Brandon Goldfedder, Felix Holzmeister, Magnus Johannesson, Yang Liu, Louisa Tran, Charles Twardy, Juntao Wang and Thomas Pfeiffer. Forecasting the Publication and Citation Outcomes of COVID-19 Preprints. Royal Society Open Science (RSOS), 2022.
• Yiling Chen, Alon Eden and Juntao Wang. Cursed Yet Satisfied Agents. Conference on Innovations in Theoretical Computer Science (ITCS), February 2022.

2021

• Juntao Wang, Yang Liu and Yiling Chen. Forecast Aggregation via Peer Prediction. In Proceedings of The 9th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), November 2021. [arXiv]
• Ben Green and Yiling Chen. Algorithmic Risk Assessments Can Alter Human Decision-Making Processes in High-Stakes Government Contexts. In Proceedings of The 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), October 2021.
• Yiling Chen, Biaoshuai Tao and Fang-Yi Yu. Cooperation in Threshold Public Projects with Binary Actions. In Proc. of the 30th International Joint Conference on Artificial Intelligence (IJCAI), August 2021. [arXiv]
• Shuran Zheng and Yiling Chen. Optimal Advertising for Information Products. In Proc. of the 22nd ACM Conference on Economics and Computation (EC), July 2021. [arXiv]
• Shuran Zheng, Fang-Yi Yu and Yiling Chen. The Limits of Multi-task Peer Prediction. In Proc. of the 22nd ACM Conference on Economics and Computation (EC), July 2021.
• Xiang Yan and Yiling Chen. Optimal Crowdfunding Design. In Proc. of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2021. (extended abstract)

2020

• Charles R. Ebersole et. al.. Many Labs 5: Testing pre-data collection peer review as an intervention to increase replicability. Advances in Methods and Practices in Psychological Science. 2020.
• Yiling Chen, Yiheng Shen, and Shuran Zheng. Truthful Data Acquisition via Peer Prediction. In Proc. of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2020. [Long version]
• Yiling Chen, Yang Liu, and Chara Podimata. Learning Strategy-Aware Linear Classifiers. In Proc. of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2020. [Long version]
• Michael Gordon, Domenico Viganola, Michael Bishop, Yiling Chen, Anna Dreber, Brandon Goldfedder, Felix Holzmeister, Magnus Johannesson, Yang Liu, Charles Twardy, Juntao Wang and Thomas Pfeiffer. Are Replication Rates the Same across Academic Fields? Community Forecasts from the DARPA SCORE Program. Royal Society Open Science (RSOS), 2020.
• Florian Berlinger, Lily Xu and Yiling Chen. A High-Performance Graph Model for Near-Optimal Payments for Ecosystem Services. The 4th Workshop on Mechanism Design for Social Good (MD4SG), 2020.
• Yang Liu, Juntao Wang and Yiling Chen. Surrogate Scoring Rules. In Proc. of the 21st ACM Conference on Economics and Computation (EC), 2020.
• Yang Liu, Michael Gordon, Juntao Wang, Michael Bishop, Yiling Chen, Thomas Pfeiffer, Charles Twardy and Domenico Viganola. Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication. AAAI Workshop on Reproducible AI (RAI), 2020.
• Lily Hu and Yiling Chen. Fair Classification and Social Welfare. In Proc. of the Third ACM Conference on Fairness, Accountability and Transparency (FAT*), Barcelona, Spain, January 2020. (Supersedes the MD4SG’19 paper.)
• Ben Green and Yiling Chen. Algorithm-in-the-Loop Decision Making. The 34st AAAI Conference on Artificial Intelligence (AAAI), Sister Conference Track. 2020.
• Yiling Chen, Haifeng Xu and Shuran Zheng. Selling Information Through Consulting. In Proc. of ACM-SIAM Symposium on Discrete Algorithms (SODA), Salt Lake City, UT, January, 2020. [arXiv]

2019

• Eskil Forsell, Domenico Viganola, Thomas Pfeiffer, Johan Almenberg, Brad Wilson, Yiling Chen, Brian A. Nosek, Magnus Johannesson and Anna Dreber. Predicting Replication Outcomes in the Many Labs 2 study. Journal of Economic Psychology, Volume 75, Part A, December 2019.
• Jerry Anunrojwong, Yiling Chen, Bo Waggoner, and Haifeng Xu. Computing Equilibria of Prediction Markets via Persuasion. In Proc. of The 15th Conference on Web and Internet Economics (WINE), New York, NY, December 2019.
• Ben Green and Yiling Chen. The Principles and Limits of Algorithm-in-the-Loop Decision Making. In Proc. of the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), Austin, TX, November 2019. （Best Paper Award)
• Shuran Zheng and Yiling Chen. Prior-free Data Acquisition for Accurate Statistical Estimation. In Proc. of the 20th ACM Conference on Economics and Computation (EC), Phoenix, AZ, June 2019. [Long version]
• Yiling Chen, Haifeng Xu and Shuran Zheng. Simple and Optimal Mechanisms for Selling Information to Budget-Constrained Buyers. ACM/INFORMS Workshop on Market Design, June 2019.
• Lily Hu and Yiling Chen. Fair Classification and Social Welfare. The 3rd Workshop on Mechanism Design for Social Good (MD4SG), June 2019.
• Yiling Chen, Yang Liu and Chara Podimata. Grinding the Space: Learning to Classify Against Strategic Agents. ACM EC Workshop on Learning in the Presence of Strategic Behavior, June 2019.
• Ben Green and Yiling Chen. Disparate Interactions: An Algorithm-in-the-Loop Analysis of Fairness in Risk Assessments. In Proc. of the Second ACM Conference on Fairness, Accountability and Transparency (FAT*), Atlanta, Georgia, January 2019. (Best Technical + Interdisciplinary Paper)
• Yiling Chen, Yang Liu and Juntao Wang. Randomized Wagering Mechanisms. In Proc. of the 33st AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, January 2019.

2018

• Yiling Chen, Chara Podimata, Ariel D. Procaccia, and Nisarg Shah. Strategyproof linear regression in high dimensions: an overview. ACM SIGecom Exchanges. Volume 17 Issue 1, November 2018.
• Ming Yin, Emma Heikensten and Yiling Chen. Is Time Our Friend or Enemy? The Impact of Timing on Online Experimentation. Conference on Digital Experimentation (CODE), October 2018.
• Colin F. Camerer, Anna Dreber, Felix Holzmeister, Teck-Hua Ho, Jürgen Huber, Magnus Johannesson, Michael Kirchler, Gideon Nave, Brian A. Nosek, Thomas Pfeiffer, Adam Altmejd, Nick Buttrick, Taizan Chan, Yiling Chen, Eskil Forsell, Anup Gampa, Emma Heikensten, Lily Hummer, Taisuke Imai, Siri Isaksson, Dylan Manfredi, Julia Rose, Eric-Jan Wagenmakers and Hang Wu. Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nature Human Behaviour, vol. 2 (9), pp. 637-644, 2018.
• Shuran Zheng, Bo Waggoner, Yang Liu and Yiling Chen. Active Information Acquisition for Linear Optimization. In Proc. of the Conference on Uncertainty in Artificial Intelligence (UAI), Monterey, California, August 2018. [Long version]
• Lily Hu and Yiling Chen. Welfare and Distributional Impacts of Fair Classification. Workshop on Fairness, Accountability, and Transparency in Machine Learning (FATML), Stockholm, Sweden, July 2018.
• Yiling Chen, Nicole Immorlica, Brendan Lucier, Vasilis Syrgkanis and Juba Ziani. Optimal Data Acquisition for Statistical Estimation. In Proc. of  the 19th ACM Conference on Economics and Computation (EC), Ithaca, NY, June 2018. [Long version]
• Yiling Chen, Chara Podimata, Ariel Procaccia and Nisarg Shah. Strategyproof Linear Regression in High Dimensions. In Proc. of  the 19th ACM Conference on Economics and Computation (EC), Ithaca, NY, June 2018. [Long version] (Among the 5 shortlisted papers for the Best Paper Award)
• Lily Hu and Yiling Chen. A Short-term Intervention for Long-term Fairness in the Labor Market. In Proc. of The Web Conference (WWW), Lyon, France, April 2018. (Research Paper Honorable Mention) (Supersedes the FATML’17 paper below.)

2017

• Yiling Chen, Chara Podimata, and Nisarg Shah. Strategyproof Linear Regression. NIPS’17 Workshop on Learning in the Presence of Strategic Behavior, Long Beach, CA, December 2017.
• Lily Hu and Yiling Chen. Fairness at Equilibrium in the Labor Market. Workshop on Fairness, Accountability, and Transparency in Machine Learning (FATML), Halifax, Nova Scotia, August 2017.
• Yiling Chen and Bo Waggoner. Intro to Informational Substitutes. ACM SIGecom Exchanges, Volume 16 Issue 1, August 2017.
• Yang Liu and Yiling Chen. Machine-Learning Aided Peer Prediction. In Proc. of  the 18th ACM Conference on Economics and Computation (EC), Cambridge, MA, June 2017.
• Yang Liu and Yiling Chen. Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices. In Proc. of the 31st AAAI Conference on Artificial Intelligence (AAAI), San Francisco, CA, February 2017.

2016

• Yiling Chen, Arpita Ghosh, Michael Kearns, Tim Roughgarden, and Jennifer Wortman Vaughan. Mathematical Foundations for Social Computing. Communications of ACM, 2016.
• Yang Liu and Yiling Chen. A Bandit Framework for Strategic Regression. In Proc. of the 30th Annual Conference on Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016.
• Chien-Ju Ho, Rafael M. Frongillo and Yiling Chen. Eliciting Categorical Data for Optimal Aggregation, In Proc. of the 30th Annual Conference on Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016.
• Ming Yin and Yiling Chen. Predicting Crowd Work Quality under Monetary Interventions. In Proc. of the 4th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Austin, TX, October 30 – November 3, 2016.
• Yiling Chen and Bo Waggoner. Informational Substitutes. In Proc. of the 57th Annual IEEE Symposium on Foundations of Computer Science (FOCS), New Brunswick, NJ, October, 2016.
• Yang Liu and Yiling Chen. Learning to Incentivize: Eliciting Effort via Output Agreement. In Proc. of the 25th International Joint Conference on Artificial Intelligence (IJCAI), New York, NY, July 2016.

2015

• Anna Drebera, Thomas Pfeiffer, Johan Almenberg, Siri Isakssona, Brad Wilsone, Yiling Chen, Brian A. Nosek, and Magnus Johannesson. Using Prediction Markets to Estimate the Reproducibility of Scientific Research. PNAS, 2015.
• Marcus R. Munafo, Thomas Pfeiffer, Adam Altmejd, Emma Heikensten, Johan Almenberg, Alexander Bird, Yiling Chen, Brad Wilson, Magnus Johannesson and Anna Dreber. Using Prediction Markets to Forecast Research Evaluations. Royal Society Open Science 2: 150287, 2015.
• Ming Yin and Yiling Chen. Bonus or Not? Learn to Reward in Crowdsourcing. In Proc. of the 24th International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, July 2015.
• Jacob Abernethy, Yiling Chen, Chien-Ju Ho, and Bo Waggoner. Low-Cost Learning via Active Data Procurement. In Proc. of  the 16th ACM Conference on Economics and Computation (EC), Portland, Oregon, June 2015. [Long Version]
• Yiling Chen, Kobbi Nissim, and Bo Waggoner. Fair Information Sharing for Treasure Hunting. In Proc. of the 29th Conference on Artificial Intelligence (AAAI), Austin, TX, January 2015. [Long Version]
• Rafael M. Frongillo, Yiling Chen, and Ian A. Kash. Elicitation for Aggregation. In Proc. of the 29th Conference on Artificial Intelligence (AAAI), Austin, TX, January 2015.
• Yiling  Chen, Xi Alice Gao, Rick Goldstein, and Ian A. Kash. Market Manipulation with Outside Incentives. Autonomous Agents and Multi-Agent Systems. Vol. 29, no. 2, pp. 230-265, March 2015. (Supersedes the AAAI’11 paper below.)
• Nicolas S. Lambert, John Langford, Jennifer Wortman Vaughan, Yiling Chen, Daniel Reeves, Yoav Shoham, and David M. Pennock. An Axiomatic Characterization of Wagering Mechanisms. Journal of Economic Theory.  156 (2015) 389-416. (Supersedes the EC’08 paper below.)

2014

• Yiling Chen, Or Sheffet, and Salil Vadhan. Privacy Games. In Proc. of the 10th Conference on Web and Internet Economics (WINE), Beijing, China, December 2014. [Long Version]
• Bo Waggoner and Yiling Chen. Output Agreement Mechanisms and Common Knowledge. In Proc. of the 2nd AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Pittsburgh, PA, November 2014.  [Long Version] (The earlier SCUGC’13 workshop version contains the same results with different presentation.)
• Ming Yin, Yiling Chen, and Yu-An Sun. Monetary Interventions in Crowdsourcing Task Switching. In Proc. of the 2nd AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Pittsburgh, PA, November 2014.
• Simina Brânzei, Yiling Chen, Xiaotie Deng, Aris Filos-Ratsikas, Søren Kristoffer Stiil Frederiksen, and Jie Zhang. The Fisher Market Game: Equilibrium and Welfare. In Proc. of the 28th Conference on Artificial Intelligence (AAAI), Québec City, Québec, Canada, July 2014.
• Yiling Chen, Nikhil R. Devanur, David Pennock, and Jennifer Wortman Vaughan. Removing Arbitrage from Wagering Mechanisms. In Proc. of the 15th ACM Conference on Economics and Computation (EC), Palo Alto, CA, June 2014. [Long Version]
• Xi Alice Gao, Andrew Mao, Yiling Chen, and Ryan P. Adam. Trick or Treat: Putting Peer Prediction to the Test. In Proc. of the 15th ACM Conference on Economics and Computation (EC), Palo Alto, CA, June 2014. (Supersedes the COBE’13 paper below.)
• Peter Zhang and Yiling Chen. Elicitability and Knowledge-Free Elicitation with Peer Prediction. In Proc. of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Paris, France, May 2014.
• Yiling Chen, Ian A. Kash, Mike Ruberry, and Victor Shnayder. Eliciting Predictions and Recommendations for Decision Making. ACM Transactions on Economics and Computation. Vol. 2, no. 2, pp. 6:1-6:27, June 2014. (Supersedes the WINE’11 and the AAMAS’11 papers below.)
• Shaili Jain, Yiling Chen, and David C. Parkes. Designing Incentives for Online Question and Answer Forums. Games and Economic Behavior. Vol. 86, pp. 458-474, July 2014. (Supersedes the EC’09 paper below.)

2013

• Andrew Mao, Ece Kamar, Yiling Chen, Eric Horvitz, Megan E. Schwamb, Chris J. Lintott, and Arfon M. Smith. Volunteering vs. Work for Pay: Incentives and Tradeoffs in Crowdsourcing. In Proc. of the 1st AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Palm Springs, CA, November 2013.
• Ming Yin, Yiling Chen, Yu-An Sun. Task Sequence Design: Evidence on Price and Difficulty. In Proc. of the 1st AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Palm Springs, CA, November 2013. (Work in Progress track)
• Ming Yin, Yiling Chen and Yu-An Sun. The Effects of Performance-Contingent Financial Incentives in Online Labor Markets. In Proc. of the 27th Conference on Artificial Intelligence (AAAI), Bellevue, WA, July 2013.
• Andrew Mao, Ariel D. Procaccia, and Yiling Chen. Better Human Computation Through Principled Voting. In Proc. of the 27th Conference on Artificial Intelligence (AAAI), Bellevue, WA, July 2013. (Supersedes the HCOMP’12 paper below.)
• Yiling Chen, Stephen Chong, Ian Kash, Tal Moran, and Salil Vadhan. Truthful Mechanisms for Agents that Value Privacy. In Proc. of the 14th ACM Conference on Electronic Commerce (EC), Philadelphia, PA, June 2013.
• Xi Alice Gao, Jie Zhang, and Yiling Chen. What You Jointly Know Determines How You Act — Strategic Interactions in Prediction Markets. In Proc. of the 14th ACM Conference on Electronic Commerce (EC), Philadelphia, PA, June 2013.
• Yiling Chen, Mike Ruberry, and Jennifer Wortman Vaughan. Cost Function Market Makers for Measurable Spaces. In Proc. of the 14th ACM Conference on Electronic Commerce (EC), Philadelphia, PA, June 2013. [Long Version]
• Bo Waggoner and Yiling Chen. Information Elicitation Sans Verification. The 3rd Workshop on Social Computing and User Generated Content (SCUGC), in conjunction with ACM EC’13, Philadelphia, PA, June 2013.
• Xi Alice Gao, Andrew Mao, and Yiling Chen. Trick or Treat: Putting Peer Prediction to the Test. Workshop on Crowdsourcing and Online Behavioral Experiments (COBE), in conjunction with ACM EC’13, Philadelphia, PA, June 2013.
• Reshef Meir, Yiling Chen and Michal Feldman. Efficient Parking Allocation as Online Bipartite Matching. In Proc. of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Saint Paul, MN, May 2013.
• Jacob Abernethy, Yiling Chen, and Jennifer Wortman Vaughan. Efficient Market Making via Convex Optimization, and a Connection to Online Learning. ACM Transactions on Economics and Computation. Vol. 1, no. 2, pp. 12:1-12:39 , May 2013. (Supersedes the EC’10 and EC’11 papers below.)
• Yiling Chen, John K. Lai, David C. Parkes, and Ariel D. Procaccia. Truth, Justice, and Cake Cutting. Games and Economic Behavior. Vol. 77, no. 1, pp. 284-297, January 2013. (Supersedes the AAAI’10 paper below.)
• Yiling Chen and Nicole Immorlica (Eds.), Web and Internet Economics (Proceedings of WINE 2013), Lecture Notes in Computer Science, Volume 8289. Springer Berlin Heidelberg, 2013.

2012

• Yiling Chen, Mike Ruberry, and Jennifer Wortman Vaughan. Designing Informative Securities. In Proc. of the 28th Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, CA, August 2012.
• Thomas Pfeiffer, Xi Alice Gao, Andrew Mao, Yiling Chen, and David G. Rand. Adaptive Polling and Information Aggregation. In Proc. of the 26th Conference on Artificial Intelligence (AAAI), Toronto, Ontario, Canada, July 2012.
• Andrew Mao, Yiling Chen, Krzysztof Gajos, David C. Parkes, Ariel D. Procaccia, and Haoqi Zhang. Turk Server: Enabling Synchronous and Longitudinal Online Experiments. The AAAI Human Computation Workshop (HCOMP), Toronto, Ontario, Canada, July 2012.
• Andrew Mao, Ariel D. Procaccia, and Yiling Chen. Social Choice for Human Computation. The AAAI Human Computation Workshop (HCOMP), Toronto, Ontario, Canada, July 2012.
• Haoqi Zhang, Eric Horvitz, Yiling Chen, and David C. Parkes. Task Routing for Prediction Tasks. In Proc. of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Valencia, Spain, June 2012.  (Supersedes the 2011 Workshop on Social Computing and User-Generated Content Paper below.)
• David F. Bacon, Yiling Chen, Ian A. Kash, David C. Parkes, Malvika Rao, and Manu Sridharan. Predicting Your Own Effort. In Proc. of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Valencia, Spain, June 2012. (Best Paper Award)
• Edited SIGecom Exchanges Issue 11.1. Contributed Editor’s Introduction. June, 2012.

2011

• Yiling Chen, Ian A. Kash, Mike Ruberry, and Victor Shnayder. Decision Markets with Good Incentives. In Proc. of the 7th Workshop on Internet and Network Economics (WINE), Singapore, December 2011.
• Yiling  Chen, Xi Alice Gao, Rick Goldstein, and Ian A. Kash. Market Manipulation with Outside Incentives. In Proc. of the 25th Conference on Artificial Intelligence (AAAI), pp. 614–619, San Francisco, CA, August 2011.
• Beatrice Liem, Haoqi Zhang, and Yiling Chen. An Iterative Dual Pathway Structure for Speech-to-Text Transcription. The AAAI Human Computation Workshop (HCOMP), San Francisco, CA, August 2011.
• Jacob Abernethy, Yiling Chen, and Jennifer Wortman Vaughan. An Optimization-Based Framework for Automated Maket-Making. In Proc. of the 12th ACM Conference on Electronic Commerce (EC), pp. 297–306, San Jose, CA, June 2011. [Long Version] (Supersedes the 2010 NIPS Workshop Paper below.)
• Haoqi Zhang, Eric Horvitz, Yiling Chen, and David C. Parkes. Task Routing for Prediction Tasks. The ACM EC Workshop on Social Computing and User Generated Content, San Jose, CA, June 2011.
• Yiling Chen and Ian A. Kash. Information Elicitation for Decision Making. In Proc. of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 175–182, Taipei, Taiwan, May 2011.
• Yiling Chen, Jerry Kung, David C. Parkes, Ariel D. Procaccia, and Haoqi Zhang. Incentive Design for Adaptive Agents. In Proc. of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 627–634, Taipei, Taiwan, May 2011.
• Yiling Chen. Mechanisms for Prediction Markets. In Prediction Markets: Theory and Applications, Leighton Vaughan Williams (editor). Routledge, 2011. (Book chapter.)
• Edited SIGecom Exchanges Issue 10.3. Contributed Editor’s Introduction. December, 2011.
• Edited SIGecom Exchanges Issue 10.2. Contributed Editor’s Introduction. June, 2011.
• Co-edited SIGecom Exchanges Issue 10.1 with Vincent Conitzer. Co-contributed Editors’ Introduction. March, 2011.

2010

• Yiling Chen and David M. Pennock. Designing Markets for Prediction. AI Magazine, 31(4): 42-52, 2010.
• Jacob Abernethy, Yiling Chen and Jennifer Wortman Vaughan. An Optimization-Based Framework for Combinatorial Prediction Market Design. The NIPS Workshop on Computational Social Science and the Wisdom of Crowds, Whistler, Canada, December 2010.
• Xi Alice Gao and Yiling Chen. An Axiomatic Characterization of Continuous-Outcome Market Makers. In Proc. of the 6th Workshop on Internet and Network Economics (WINE), pp. 505–514, Stanford, CA, December 2010.
• Yiling Chen,  Stanko Dimitrov, Rahul Sami, Daniel M. Reeves, David M. Pennock, Robin D. Hanson, Lance Fortnow, and Rica Gonen. Gaming Prediction Markets: Equilibrium Strategies with a Market Maker. Algorithmica, vol. 58, no. 4, pp. 930-969, 2010. (Supersedes the 2007 WINE Paper below.)
• David F. Bacon, Eric Bokelberg, Yiling Chen, Ian A. Kash, David C. Parkes, Malvika Rao, and Manu Sridharan. Software Economies. The FSE/SDP Workshop on the Future of Software Engineering Research (FoSER), Santa Fe, NM, November 2010.
• Yiling Chen, John K. Lai, David C. Parkes, and Ariel D. Procaccia. Truth, Justice, and Cake Cutting. In Proc. of the 24th Conference on Artificial Intelligence (AAAI), pp. 756–761, Atlanta, Georgia, July 2010.
• Eric Huang, Haoqi Zhang, David C. Parkes, Krzysztof Gajos, and Yiling Chen. Toward Automatic Task Design: A Progress Report. The KDD Human Computation Workshop (HCOMP), Washington, D.C., July 2010.
• Yiling Chen and Jennifer Wortman Vaughan. Connections Between Markets and Learning. ACM SIGecom Exchanges, vol. 9, no. 1, 2010. (Research letter.)
• Yiling Chen and Jennifer Wortman Vaughan. A New Understanding of Prediction Markets Via No-Regret Learning. In Proc. of the 11th ACM Conference on Electronic Commerce (EC), pp. 189–198, Cambridge, MA, June 2010. [Long Version]

2009

• Qianya Lin and Yiling Chen. Gaming Dynamic Parimutuel Markets. In Proc. of the 5th Workshop on Internet and Network Economics (WINE), pp. 623–631, Rome, Italy, December 2009.
• Xi Alice Gao, Yiling Chen, and David P. Pennock. Betting on the Real Line. In Proc. of the 5th Workshop on Internet and Network Economics (WINE), pp. 553–560, Rome, Italy, December 2009.
• David F. Bacon, Yiling Chen, D.C. Parkes, and M. Rao. A Market-Based Approach to Software Evolution. In Proc. of the ACM Onward! Conference, pp. 973–980, Orlando, FL, October 2009.
• Haoqi Zhang, Yiling Chen, and David C. Parkes. A General Approach to Environment Design with One Agent. In Proc. of the 21st International Joint Conference on Artificial Intelligence (IJCAI), pp. 2002–2008, Pasadena, CA, July 2009.
• Shaili Jain, Yiling Chen, and David C. Parkes. Designing Incentives for Online Question and Answer Forums. In Proc. of the 10th ACM Conference on Electronic Commerce (EC), pp. 129–138, Stanford, CA, July 2009.
• Haoqi Zhang, David C. Parkes, and Yiling Chen. Policy Teaching Through Reward Function Learning. In Proc. of the 10th ACM Conference on Electronic Commerce (EC), pp. 295–304, Stanford, CA, July 2009.

2008

• P.M. Polgreen, Y. Chen, D.M. Pennock, and F.D. Nelson. Using Internet Searches for Influenza Surveillance. Clinical Infectious Diseases, vol. 47, no. 11, pp. 1443–1448, 2008.
• Yiling Chen, Arpita Ghosh, R. Preston McAfee, and David M. Pennock. Sharing Online Advertising Revenue with Consumers. In Proc. of the 4th International Workshop on Internet and Network Economics (WINE), pp. 456–465, Shanghai, China, December 2008. (A preliminary version appeared in the 4th Workshop on Ad Auctions, Chicago, IL, June 2008.)
• Yiling Chen, David M. Pennock, and Tejaswi Kasturi. An Empirical Study of Dynamic Pari-mutuel Markets: Evidence from the Tech Buzz Game. The KDD Workshop on Web Mining and Web Usage Analysis (WebKDD), Las Vegas, NV, August 2008.
• Yiling Chen, Lance Fortnow, Nicolas Lambert, David M. Pennock, and Jennifer Wortman. Complexity of Combinatorial Market Makers. In Proc. of the 9th ACM Conference on Electronic Commerce (EC), pp. 190–199, Chicago, IL, July 2008.
• Nicolas Lambert, John Langford, Jennifer Wortman, Yiling Chen, Daniel M. Reeves, Yoav Shoham, and David M. Pennock. Self-Financed Wagering Mechanisms for Forecasting. In Proc. of the 9th ACM Conference on Electronic Commerce (EC), pp. 170–179, Chicago, IL, July 2008. (Outstanding Paper Award)
• Yiling Chen, Sharad Goel, and David M. Pennock. Pricing Combinatorial Markets for Tournaments. In Proc. of the 40th ACM Symposium on Theory of Computing (STOC), pp. 305–314, Victoria, Canada, May 2008.

2007

• Yiling Chen, David M. Reeves, David M. Pennock, Robin D. Hanson, Lance Fortnow, and Rica Gonen. Bluffing and Strategic Reticence in Prediction Markets. In Proc. of the 3rd International Workshop on Internet and Network Economics (WINE), pp. 70–81, San Diego, CA, December 2007.
• Yiling Chen, Lance Fortnow, Evdokia V. Nikolova, and David M. Pennock. Combinatorial Betting. ACM SIGecom Exchanges, vol. 7, no. 1, 2007. (Research letter.)
• Yiling Chen and David M. Pennock. A Utility Framework for Bounded-Loss Market Makers. In Proc. of the 23rd Conference on Uncertainty in Artificial Intelligence (UAI), pp. 49–56, Vancouver, BC Canada, July 2007.
• Yiling Chen, Lance Fortnow, Evdokia V. Nikolova, and David M. Pennock. Betting on Permutations. In Proc. of the 8th ACM Conference on Electronic Commerce (EC), pp. 326–335, San Diego, CA, June 2007.
• Yiling Chen and David M. Pennock. Socially Embedded Prediction Markets. Special Issue Workshop for Economica on the Growth of Gambling and Prediction Markets: Economic and Financial Implications, Palm Desert, CA, May 2007.

2006 and earlier

• Yiling Chen, Chao-Hsien Chu, and Tracy Mullen. Predicting Uncertain Outcomes Using Information Markets: Trader Behavior and Information Aggregation. New Mathematics and Natural Computation, vol. 2, no. 3, pp. 281–297, 2006.
• Yiling Chen, Tracy Mullen, and Chao-Hsien Chu. An In-Depth Analysis of Information Markets with Aggregate Uncertainty. Electronic Commerce Research, vol. 6, no. 2, pp. 201–22, 2006.
• Yiling Chen. Markets as an Information Aggregation Mechanism for Decision Support. Ph.D. Dissertation, School of Information Sciences and Technology, The Pennsylvania State University, December 2005.
• Yiling Chen, Chao-Hsien Chu, Tracy Mullen, and David M. Pennock. Information Markets vs. Opinion Pools: An Empirical Comparison. In Proc. of the 6th ACM Conference on Electronic Commerce (EC), pp. 58–67, Vancouver, BC Canada, June 2005.
• Yiling Chen, Tracy Mullen, Chao-Hsien Chu. Predicting Uncertain Outcomes Using Information Markets. In Proc. of the 8th Joint Conference on Information Sciences (JCIS), Salt Lake City, UT, July 2005.
• Yiling Chen and Anthony M. Kwasnica. Security Design and Information Aggregation in Markets. Technical Report, The Pennsylvania State University, 2005.
• Yiling Chen, Tracy Mullen, and Chao-Hsien Chu. Theoretical Investigation of Prediction Markets with Aggregate Uncertainty. In Proc. of the 7th International Conference on Electronic Commerce Research (ICECR), pp. 81–90, Dallas, TX, June 2004.
• Yiling Chen and Frederico Fonseca. A Bipartite Graph Co-Clustering Approach for Ontology Mapping. Workshop of Semantic Web Technologies for Searching and Retrieving Scientific Data, in conjunction with the 2nd International Semantic Web Conference (ISWC), Sanibel Island, FL, October, 2003.
• Yiling Chen and Isaac G. Council. An Introduction to Support Vector Machines: A Review. AI Magazine, vol. 24, no. 2, pp. 105–106, 2003. (Book review.)
• Yiling Chen and Fengming Song. An Empirical Study on the Relationship between Price Changes and Trading Volume in China Stock Market (In Chinese). Journal of Management Sciences in China, vol. 3,  no. 2, pp. 62–68, 2000.