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Kaizhao Liu

2 accepted papers

2026

Statistical Impossibility and Possibility of Aligning LLMs with Human Preferences: From Condorcet Paradox to Nash Equilibrium

ICML 2026poster

Aligning large language models (LLMs) with diverse human preferences is critical for ensuring fairness and informed outcomes when deploying these models for decision-making. In this paper, we seek to uncover fundamental statistical limits concerning aligning LLMs with human preferences, with a focus…

Cited by 0SourcecodeScholar
2024

Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty

ICML 2024poster

Bootstrap is a popular methodology for simulating input uncertainty. However, it can be computationally expensive when the number of samples is large. We propose a new approach called **Orthogonal Bootstrap** that reduces the number of required Monte Carlo replications. We decomposes the target bein…

Cited by 0SourcePDFScholar