Skip to main content
UTIL

Menu

UTIL Publications

  1. Qishen Han, G. Schoenebeck, B. Tao, L. Xia. (2026). The Art of Two-Round Voting. Proceedings of the ACM Web Conference 2026 (WWW 2026). Link to “The Art of Two-Round Voting” (opens in a new tab)
  2. David Gamba, Seura Ha, D. Romero, G. Schoenebeck. (2026). Can Ideologues Agree on Quality? From Non-identifiable Latent Factors to Collective Outcomes. Proceedings of the Fortieth Annual Conference on Neural Information Processing Systems (NeurIPS 2026), to appear
  3. Qishen Han, G. Schoenebeck, B. Tao, L. Xia. (2026). Aggregating Information and Preferences under Different Coordination Ability. Proceedings of the ACM Web Conference 2026 (WWW 2026). Link to “Aggregating Information and Preferences under Different Coordination Ability” (opens in a new tab)
  4. David Gamba, D. M. Romero, G. Schoenebeck. (2026). Agentic AI: User Empowerment or Foreclosure?. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES 2026), to appear. Link to “Agentic AI: User Empowerment or Foreclosure?” (opens in a new tab)
  5. Shengwei Xu, Yuxuan Lu, Y. Wu, J. Hartline, G. Schoenebeck. (2026). Scoring Rules! Statistical and Strategic Alignment for Text Evaluation Metrics. arXiv. Link to “Scoring Rules! Statistical and Strategic Alignment for Text Evaluation Metrics” (opens in a new tab)
  6. Zexuan Li, Derek Van Berkel, A. Hasell, G. Schoenebeck, J. B. Ryan, S. Tomkins. (2026). AnnotateThis: Analyzing a human-LLM system for annotating social media data with the concept of climate change mitigation pessimism. arXiv. Link to “AnnotateThis: Analyzing a human-LLM system for annotating social media data with the concept of climate change mitigation pessimism” (opens in a new tab)
  7. Shengwei Xu, Zhaohua Chen, X. Deng, Z. Huang, G. Schoenebeck. (2026). Ad Insertion in LLM-Generated Responses. arXiv. Link to “Ad Insertion in LLM-Generated Responses” (opens in a new tab)
  8. D. Goktas, A. Greenwald, T. Osogami, R. Patel, K. Leyton-Brown, G. Schoenebeck, D. Cornelisse, C. Daskalakis, I. Gemp, J. Horton, D. C. Parkes, D. M. Pennock, A. Prakash, S. S. Ravindranath, M. O. Smith, G. Swamy, E. Vinitsky, S. Wasserkrug, M. Wellman, J. Wu, H. Xu, J. Zhang, Y. Zhang, S. Zhao, Q. Zhu. (2025). Strategic Foundation Models. HAL. Link to “Strategic Foundation Models” (opens in a new tab)
  9. Qishen Han, G. Schoenebeck, B. Tao, L. Xia. (2025). Aggregating Information and Preferences with Bounded-Size Deviations. arXiv. Link to “Aggregating Information and Preferences with Bounded-Size Deviations” (opens in a new tab)
  10. P. Resnick, Y. Kong, G. Schoenebeck, T. Weninger. (2025). Rater Equivalence: Evaluating Classifiers in Human Judgment Settings. arXiv. Link to “Rater Equivalence: Evaluating Classifiers in Human Judgment Settings” (opens in a new tab)
  11. David Gamba, D. M. Romero, G. Schoenebeck. (2025). The Ideological Turing Test for Moderation of Outgroup Affective Animosity. arXiv. Link to “The Ideological Turing Test for Moderation of Outgroup Affective Animosity” (opens in a new tab)
  12. Yichi Zhang, D. Pennock, G. Schoenebeck. (2025). Stochastically Dominant Peer Prediction. Proceedings of the Thirty-Ninth Annual Conference on Neural Information Processing Systems (Neurips 2025)
  13. Sanzeed Anwar, P. Dhillon, G. Schoenebeck. (2025). Recommendation and Temptation. 19th ACM Conference on Recommender Systems (RecSys 2025)
  14. Shengwei Xu, Yuxuan Lu, G. Schoenebeck, Y. Kong. (2025). Benchmarking LLMs' Judgments with No Gold Standard. Proceedings of the Thirteenth International Conference on Learning Representations (ICLR 2025)
  15. Qishen Han, G. Schoenebeck, B. Tao, L. Xia. (2025). Strong Equilibria in Bayesian Games with Bounded Group Size. Proceedings of the 34nd The Web Conference (WWW 2025)
  16. Yuxuan Lu, Shengwei Xu, Yichi Zhang, Y. Kong, G. Schoenebeck. (2024). Eliciting Informative Text Evaluations with Large Language Models. Proceedings of the 24th ACM Conference on Economics and Computation (EC 2024)
  17. Shengwei Xu, Yichi Zhang, P. Resnick, G. Schoenebeck. (2024). Spot Check Equivalence: an Interpretable Metric for Information Elicitation Mechanisms. Proceedings of the 33rd The Web Conference (WWW 2024)
  18. Md Sanzeed Anwar, G. Schoenebeck, P. S. Dhillon. (2024). Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns. Proceedings of the 33rd The Web Conference (WWW 2024)
  19. David Gamba, Yulin Yu, Y. Yuan, G. Schoenebeck, D. M. Romero. (2024). Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee Departures. Proceedings of the 33rd The Web Conference (WWW 2024)
  20. Yichi Zhang, G. Schoenebeck, W. Su. (2024). Eliciting Honest Information From Authors Using Sequential Review. Thirty-Eight Association for the Advancement of Artificial Intelligence Conference on Artificial intelligence (AAAI 2024)
  21. Noah Burrell, G. Schoenebeck. (2023). Testing Conventional Wisdom (of the Crowd). Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI 2023)
  22. Qishen Han, G. Schoenebeck, B. Tao, L. Xia. (2023). The Wisdom of Strategic Voting. Proceedings of the 24th ACM Conference on Economics and Computation (EC 2023)
  23. Noah Burrell, G. Schoenebeck. (2023). Measurement Integrity in Peer Prediction: A Peer Assessment Case Study. Proceedings of the 24th ACM Conference on Economics and Computation (EC 2023)
  24. Yichi Zhang, G. Schoenebeck. (2023). High-Effort Crowds: Limited Liability via Tournaments. Proceedings of the 32nd The Web Conference (WWW 2023)
  25. Yichi Zhang, G. Schoenebeck. (2023). Multitask Peer Prediction With Task-dependent Strategies. Proceedings of the 32nd The Web Conference (WWW 2023)
  26. Y. Kong, G. Schoenebeck. (2023). False Consensus, Information Theory, and Prediction Markets. Proceedings of 14th Innovations in Theoretical Computer Science (ITCS 2023)
  27. G. Schoenebeck, Fang-Yi Yu. (2023). Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question. ACM Transactions on Economics and Computation (TEAC). Link to “Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question” (opens in a new tab)
  28. W. Chen, Binghui Peng, G. Schoenebeck, B. Tao. (2022). Adaptive greedy versus non-adaptive greedy for influence maximization. Journal of Artificial Intelligence Research
  29. Yichi Zhang, Fang-Yi Yu, G. Schoenebeck, D. Kempe. (2022). A System-Level Analysis of Conference Peer Review. Proceedings of the 23rd ACM Conference on Economics and Computation (EC 2022)
  30. Zhihuan Huang, Y. Kong, T. X. Liu, G. Schoenebeck, Shengwei Xu. (2022). BONUS! Maximizing Surprise. Proceedings of the 31st ACM Web Conference (WWW 2022). Link to “BONUS! Maximizing Surprise” (opens in a new tab)
  31. Darshan Chakrabarti, J. Gao, Aditya Saraf, G. Schoenebeck, Fang-Yi Yu. (2022). Optimal Local Bayesian Differential Privacy over Markov Chains. Proceedings of Twenty-first International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2022)
  32. G. Schoenebeck, Biaoshuai Tao, Fang-Yi Yu. (2022). Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization. Information and Computation (I&C)
  33. Shih-Tang Su, V. Subramanian, G. Schoenebeck. (2021). Bayesian Persuasion in Sequential Trials. Proceedings of the 17th Conference on Web and Internet Economics (WINE 2021)
  34. G. Schoenebeck, Biaoshuai Tao. (2021). Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences. Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021)
  35. Zhihuan Huang, Shengwei Xu, You Shan, Yuxuan Lu, Y. Kong, T. X. Liu, G. Schoenebeck. (2021). SURPRISE! and When to Schedule Its. Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021)
  36. G. Schoenebeck, Fang-Yi Yu, Yichi Zhang. (2021). Information Elicitation from Rowdy Crowds. Proceedings of the 30th The Web Conference (WWW 2021)
  37. G. Schoenebeck, Chenkai Yu, Fang-Yi Yu. (2021). Timely Information from Prediction Markets. International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2021)
  38. Noah Burrell, G. Schoenebeck. (2021). Relaxing Common Belief for Social Networks. Proceedings of the 12th Innovations in Theoretical Computer Science (ITCS 2021)
  39. G. Schoenebeck, Fang-Yi Yu. (2021). Learning and Strongly Truthful Multi-task Setting Peer Prediction: A Variational Approach. Proceedings of the 12th Innovations in Theoretical Computer Science (ITCS 2021)
  40. G. Schoenebeck, Fang-Yi Yu. (2020). Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question. The 16th Conference on Web and Internet Economics (WINE 2020)
  41. G. Schoenebeck, Fang-Yi Yu. (2020). Escaping Saddle Points in Constant Dimensional Spaces: an Agent-based Modeling Perspective. Proceedings of the 21st ACM Conference on Economics and Computation, (EC 2020)
  42. G. Schoenebeck, Biaoshuai Tao. (2020). Influence Maximization on Undirected Graphs: Towards Closing the (1-1/e) Gap. ACM Transactions on Economics and Computation (TEAC)
  43. G. Schoenebeck, Fang-Yi Yu, Biaoshuai Tao. (2020). Limitations of Greed: Influence Maximization in Undirected Networks Re-visited. International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2020)
  44. Yuqing Kong, G. Schoenebeck, Fang-Yi Yu, Biaoshuai Tao. (2020). Information Elicitation Mechanisms for Statistical Estimation. Thirty-Fourth Association for the Advancement of Artificial Intelligence Conference on Artificial intelligence (AAAI 2020)
  45. W. Chen, Binghui Peng, G. Schoenebeck, Biaoshuai Tao. (2020). Adaptive Greedy Versus Non-adaptive Greedy for Influence Maximization. Thirty-Fourth Association for the Advancement of Artificial Intelligence Conference on Artificial intelligence (AAAI 2020)
  46. Shih-Tang Su, V. G. Subramanian, G. Schoenebeck. (2019). Social learning with questions. Proceedings of the 14th Workshop on the Economics of Networks, Systems and Computation (NetEcon 2019). Link to “Social learning with questions” (opens in a new tab)
  47. J. Gao, Golnaz Ghsemisefeh, J. Jones, G. Schoenebeck. (2019). Penny For the Poor: Complex Contagions in Charitable Donations
  48. Yuqing Kong, C. Peikert, G. Schoenebeck, Biaoshuai Tao. (2019). Outsourcing Computation: the Minimal Refereed Mechanism. The 15th Conference on Web and Internet Economics (WINE 2019)
  49. G. Schoenebeck, Biaoshuai Tao. (2019). Influence Maximization on Undirected Graphs: Towards Closing the (1-1/e) Gap. Proceedings of the 20th ACM Conference on Economics and Computation, (EC 2019). Link to “Influence Maximization on Undirected Graphs: Towards Closing the (1-1/e) Gap” (opens in a new tab)
  50. J. Gao, G. Schoenebeck, Fang-Yi Yu. (2019). The Volatility of Weak Ties: Co-evolution of Selection and Influence in Social Networks. Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, (AAMAS 2019). Link to “The Volatility of Weak Ties: Co-evolution of Selection and Influence in Social Networks” (opens in a new tab)
  51. Yuqing Kong, G. Schoenebeck. (2019). An Information Theoretic Framework For Designing Information Elicitation Mechanisms That Reward Truth-telling. ACM Transactions on Economics and Computation (TEAC). Link to “An Information Theoretic Framework For Designing Information Elicitation Mechanisms That Reward Truth-telling” (opens in a new tab)
  52. G. Schoenebeck, Biaoshuai Tao. (2019). Beyond Worst-case (In)approximability of Nonsubmodular Influence Maximization. ACM Transactions on Computation Theory (ToCT). Link to “Beyond Worst-case (In)approximability of Nonsubmodular Influence Maximization” (opens in a new tab)
  53. G. Schoenebeck, Biaoshuai Tao, Fang-Yi Yu. (2019). Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization. International Conference on Randomization and Computation (RANDOM 2019). Link to “Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization” (opens in a new tab)
  54. Yuqing Kong, G. Schoenebeck. (2018). Eliciting Expertise without Verification. Proceedings of the 2018 ACM Conference on Economics and Computation (EC 2018)
  55. Yuqing Kong, G. Schoenebeck. (2018). Water from Two Rocks: Maximizing the Mutual Information. Proceedings of the 2018 ACM Conference on Economics and Computation (EC 2018)
  56. Boyu Tian, Jiamin Huang, B. Mozafari, G. Schoenebeck. (2018). Contention-Aware Lock Scheduling for Transactional Databases. Proceedings of the 44th International Conference on Very Large Data Bases (VLDB 2018)
  57. Xingjun Ma, Bo Li, Yisen Wang, S. M. Erfani, Sudanthi Wijewickrema, M. E. Houle, G. Schoenebeck, D. Song, J. Bailey. (2018). Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. Proceedings of the 6th International Conference on Learning Representations (ICLR 2018)
  58. Yuqing Kong, G. Schoenebeck. (2018). Equilibrium Selection in Information Elicitation without Verification via Information Monotonicity. Proceedings of the 9th Innovations in Theoretical Computer Science (ITCS 2018)
  59. Yuqing Kong, G. Schoenebeck. (2018). Optimizing Bayesian Information Revelation Strategy in Prediction Markets: the Alice Bob Alice Case. Proceedings of the 9th Innovations in Theoretical Computer Science (ITCS 2018)
  60. G. Schoenebeck, Fang-Yi Yu. (2018). Consensus of Interacting Particle Systems on Erdös-Rényi Graphs. Proceedings of the Twenty-Nineth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2018)
  61. J. Gao, G. Schoenebeck, Fang-Yi Yu. (2017). Cascades and Myopic Routing in Nonhomogeneous Kleinberg's Small World Model. The 13th Conference on Web and Internet Economics (WINE 2017)
  62. Rico Angell, G. Schoenebeck. (2017). Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization. The 13th Conference on Web and Internet Economics (WINE 2017)
  63. G. Schoenebeck, Biashuai Tao. (2017). Beyond Worst-Case (In)approximability of Nonsubmodular Influence Maximization. The 13th Conference on Web and Internet Economics (WINE 2017)
  64. Huang, Jiamin, B. Mozafari, G. Schoenebeck, T. F. Wenisch. (2017). A top-down approach to achieving performance predictability in database systems. Proceedings of the 2017 ACM International Conference on Management of Data (SIGMOD 2017)
  65. J. Gao, Bo Li, G. Schoenebeck, Fang-Yi Yu. (2017). Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents. Proceedings of the Thirty-First Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence (AAAI 2017)
  66. Roozbeh Ebrahimi, J. Gao, Golnaz Ghasemiesfeh, G. Schoenebeck. (2017). How Complex Contagions Spread Quickly in the Preferential Attachment Model and Other Time-Evolving Networks. IEEE Transactions on Network Science and Engineering
  67. J. Gao, Ghasemiesfeh, Golnaz, G. Schoenebeck, Fang-Yi Yu. (2016). General Threshold Model for Social Cascades: Analysis and Simulations. Proceedings of the 2016 ACM Conference on Economics and Computation (EC 2016)
  68. G. Schoenebeck, Snook, Aaron, Fang-Yi Yu. (2016). Sybil Detection using latent network structure. Proceedings of the 2016 ACM Conference on Economics and Computation (EC 2016)
  69. G. Schoenebeck, Fang-Yi Yu. (2016). Complex Contagions on Configuration Model Graphs with a Power-Law Degree Distribution. The 13th Conference on Web and Internet Economics (WINE 2016)
  70. Yuqing Kong, K. Ligett, G. Schoenebeck. (2016). Putting Peer Prediction Under the Micro(economic)scope and Making Truth-telling Focal. The 13th Conference on Web and Internet Economics (WINE 2016)
  71. Roozbeh Ebrahimi, J. Gao, Golnaz Ghasemiesfeh, G. Schoenebeck. (2015). Complex Contagions in Kleinberg's Small World Model. Proceedings of the 6th Innovations in Theoretical Computer Science (ITCS 2015)
  72. A. Ghosh, K. Ligett, A. Roth, G. Schoenebeck. (2014). Buying Private Data without Verification. Proceedings of the 15th ACM Symposium on Economics and Computation (EC 2014)
  73. Travis Martin, G. Schoenebeck, M. P. Wellman. (2014). Characterizing Strategic Cascades on Networks. Proceedings of the 15th ACM Symposium on Economics and Computation (EC 2014)
  74. Shiri Chechik, Daniel Larkin, L. Roditty, G. Schoenebeck, R. E. Tarjan, V. V. Williams. (2014). Better Approximation Algorithms for the Graph Diameter. Proceedings of the 25th ACM-SIAM Symposium on Discrete Algorithms (SODA 2014)
  75. Paolo Codenotti, G. Schoenebeck, Aaron Snook. (2013). Graph Isomorphism and the Lasserre Hierarchy. arXiv
  76. G. Schoenebeck. (2013). Potential Networks, Contagious Communities, and Social Network Structure.. Proceedings of the 22nd International World Wide Web Conference (WWW 2013)
  77. G. Schoenebeck, S. Vadhan. (2012). The computational complexity of Nash equilibria in concisely represented games. ACM Transactions on the Theory of Computation (ToTC)
  78. S. Arora, Rong Ge, Sushant Sachdeva, G. Schoenebeck. (2012). Finding Overlapping Communities in Social Networks: Toward a Rigorous Approach. Proceedings of the 13th ACM conference on Electronic Commerce (EC 2012)
  79. Aaron Roth, G. Schoenebeck. (2012). Conducting Truthful Surveys, Cheaply. Proceedings of the 13th ACM conference on Electronic Commerce (EC 2012)