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D-FUSEr: Diverse Failure, Unified Success via Error-Distribution Shaping in LLM Reasoning
David Baek*, Andrew Estornell*, Yichi Zhang*, Muhammad Faaiz Taufiq, Jean-Francois Ton, Jie Mei, Tao Wang
International Conference on Machine Learning (ICML), 2026.
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From Crowds to Codes: On Review Burden in Conference Review Protocols
Xingbo Wang, Fang‑Yi Yu, Yichi Zhang (authors ranked alphabetically)
ACM Conference on Economics and Computation (EC), 2026.
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Evaluating LLM‑contaminated Crowdsourcing Data Without Ground Truth
Yichi Zhang*, Jinlong Pang*, Zhaowei Zhu, Yang Liu
The Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
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Stochastically Dominant Peer Prediction
Yichi Zhang, Shengwei Xu, David Pennock, Grant Schoenebeck
The Annual Conference on Neural Information Processing Systems (NeurIPS), 2025
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Eliciting Informative Text Evaluations with Large Language Models
Yuxuan Lu, Shengwei Xu, Yichi Zhang, Yuqing Kong, Grant Schoenebeck
ACM Conference on Economics and Computation (EC), 2024.
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Spot Check Equivalence: an Interpretable Metric for Information Elicitation Mechanisms
Shengwei Xu, Yichi Zhang, Paul Resnick, Grant Schoenebeck
The Web Conference (WWW), 2024.
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Eliciting Honest Information From Authors Using Sequential Review
Yichi Zhang, Grant Schoenebeck, Weijie Su
AAAI Conference on Artificial Intelligence (AAAI), 2024.
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Multi‑task Peer Prediction With Task‑dependent Strategies
Yichi Zhang, Grant Schoenebeck
The Web Conference (WWW), 2023.
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High‑Effort Crowds: Limited Liability via Tournaments
Yichi Zhang, Grant Schoenebeck
The Web Conference (WWW), 2023.
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A System‑Level Analysis of Conference Peer Review
Yichi Zhang, Fang‑Yi Yu, Grant Schoenebeck, David Kempe
ACM Conference on Economics and Computation (EC), 2022.
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Information Elicitation From Rowdy Crowds
Grant Schoenebeck, Fang‑Yi Yu, Yichi Zhang (authors ranked alphabetically)
The Web Conference (WWW), 2021.