6 citations · 11 across the 13 of their papers we have counts for
14 papers
When do prophets profit in prediction markets?
Anri Gu, Nicole Kagan, Alec Sun +2
Prediction markets aggregate dispersed beliefs into prices that act as probabilistic forecasts of uncertain events. Classical theory establishes how a better-than-market forecast c…
LLM-as-a-Prophet: Understanding Predictive Intelligence with Prophet Arena
Qingchuan Yang, Simon Mahns, Sida Li +3
Forecasting is not only a fundamental intellectual pursuit but also is of significant importance to societal systems such as finance and economics. With the rapid advances of large…
AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting
Jibang Wu, Chenghao Yang, Yi Wu +5
This paper develops an agentic framework that employs large language models (LLMs) for grounded persuasive language generation in automated copywriting, with real estate marketing…
Contractual Reinforcement Learning: Pulling Arms with Invisible Hands
Jibang Wu, Siyu Chen, Mengdi Wang +2
The agency problem emerges in today's large scale machine learning tasks, where the learners are unable to direct content creation or enforce data collection. In this work, we prop…
An Isotonic Mechanism for Overlapping Ownership
Yifan Guo, Weijie Su, Jibang Wu +1
Motivated by the problem of improving peer review at large scientific conferences, this paper studies how to elicit self-evaluations to improve review scores in a natural many-to-m…
Robust Stackelberg Equilibria
Jiarui Gan, Minbiao Han, Jibang Wu +1
This paper provides a systematic study of the robust Stackelberg equilibrium (RSE), which naturally generalizes the widely adopted solution concept of the strong Stackelberg equili…
Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model
Siyu Chen, Jibang Wu, Yifan Wu +1
We study the incentivized information acquisition problem, where a principal hires an agent to gather information on her behalf. Such a problem is modeled as a Stackelberg game bet…
Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality
Jibang Wu, Weiran Shen, Fei Fang +1
Optimizing strategic decisions (a.k.a. computing equilibrium) is key to the success of many non-cooperative multi-agent applications. However, in many real-world situations, we may…
Generalized Principal-Agency: Contracts, Information, Games and Beyond
Jiarui Gan, Minbiao Han, Jibang Wu +1
In the principal-agent problem formulated by Myerson'82, agents have private information (type) and make private decisions (action), both of which are unobservable to the principal…
Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning
Jibang Wu, Zixuan Zhang, Zhe Feng +4
In today's economy, it becomes important for Internet platforms to consider the sequential information design problem to align its long term interest with incentives of the gig ser…
Uncoupled Bandit Learning towards Rationalizability: Benchmarks, Barriers, and Algorithms
Jibang Wu, Haifeng Xu, Fan Yao
Under the uncoupled learning setup, the last-iterate convergence guarantee towards Nash equilibrium is shown to be impossible in many games. This work studies the last-iterate conv…
Least Square Calibration for Peer Review
Sijun Tan, Jibang Wu, Xiaohui Bei +1
Peer review systems such as conference paper review often suffer from the issue of miscalibration. Previous works on peer review calibration usually only use the ordinal informatio…
Auctioning with Strategically Reticent Bidders
Jibang Wu, Ashwinkumar Badanidiyuru, Haifeng Xu
We propose and study a novel mechanism design setup where each bidder holds two kinds of private information: (1) type variable, which can be misreported; (2) information variable,…
Déjà vu: A Contextualized Temporal Attention Mechanism for Sequential Recommendation
Jibang Wu, Renqin Cai, Hongning Wang
Predicting users' preferences based on their sequential behaviors in history is challenging and crucial for modern recommender systems. Most existing sequential recommendation algo…