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New classification aggregation framework introduced, drawing parallels to Arrow's theorem

Researchers have developed a new framework for classification aggregation that handles multiple memberships, where individuals assign one category to an object, but the aggregated result can include multiple categories. The study, drawing parallels to Arrow's theorem, introduces axioms like Responsibility, Split Stability, and Rejection Stability to define "junta rules." These rules assign a category to an object if a specific coalition of members does so, with the coalitions forming a structure implied by an ultrafilter. The research also explores an infinite population setting to further differentiate the axioms. AI

RANK_REASON Academic paper detailing a new theoretical framework for classification aggregation. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New classification aggregation framework introduced, drawing parallels to Arrow's theorem

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Academic paper detailing a new theoretical framework for classification aggregation. [lever_c_demoted from research: ic=1 ai=0.4]
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  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Vasilis Stamatis ·

    Classification Aggregation with Multiple Memberships

    People face the problem of classifying objects into categories while aggregating their opinions. We axiomatically study such a classification aggregation problem with multiple memberships, meaning that each individual assigns one category to every object, whereas the resulting cl…