56 citations · 104 across the 43 of their papers we have counts for
5 papers · 1 filter
When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop
Yang Zhang, Xiukun Wei, Xueru Zhang
Foundation models are increasingly trained on synthetic data generated by prior model iterations rather than exclusively on real data. This self-consuming training paradigm can lea…
Observations and Remedies for Large Language Model Bias in Self-Consuming Performative Loop
Yaxuan Wang, Zhongteng Cai, Yujia Bao +2
The rapid advancement of large language models (LLMs) has led to growing interest in using synthetic data to train future models. However, this creates a self-consuming retraining…
Non-linear Welfare-Aware Strategic Learning
Tian Xie, Xueru Zhang
This paper studies algorithmic decision-making in the presence of strategic individual behaviors, where an ML model is used to make decisions about human agents and the latter can…
Learning under Imitative Strategic Behavior with Unforeseeable Outcomes
Tian Xie, Zhiqun Zuo, Mohammad Mahdi Khalili +1
Machine learning systems have been widely used to make decisions about individuals who may behave strategically to receive favorable outcomes, e.g., they may genuinely improve the…
Fairness in Learning-Based Sequential Decision Algorithms: A Survey
Xueru Zhang, Mingyan Liu
Algorithmic fairness in decision-making has been studied extensively in static settings where one-shot decisions are made on tasks such as classification. However, in practice most…