Researchers have introduced a new method called the Clipped Linear Lottery to address instability in selection processes that use partial lotteries based on evaluation scores. This new approach formalizes "smoothness" as a design principle, ensuring that small score changes do not lead to drastic shifts in selection probabilities. Experiments using real-world peer review data from major conferences and a national science foundation demonstrated that existing lottery designs are highly unstable, while the proposed Clipped Linear Lottery offers a better tradeoff between smoothness and utility. AI
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IMPACT Introduces a more stable and fair method for score-based selection, potentially impacting AI-driven review and hiring processes.
RANK_REASON Academic paper introducing a new method and theoretical analysis with experimental validation. [lever_c_demoted from research: ic=1 ai=0.7]