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cs.GT2026
Efficient Ensemble Selection from Binary and Pairwise Feedback
Tzeh Yuan Neoh, Nicholas Teh, Je Qin Chooi +2
Organizations increasingly deploy multiple AI systems across task domains, but selecting a small, high-performing ensemble can require costly model calls, benchmark runs, and human…
cs.AI2026
Embeddings for Preferences, Not Semantics
Carter Blair, Ariel D. Procaccia, Milind Tambe
Modern AI is opening the door to collective decision-making in which participants express their views as free-form text rather than voting on a fixed set of candidates. A natural i…
cs.AI2026
Adaptive Multi-Round Allocation with Stochastic Arrivals
Yuqi Pan, Davin Choo, Haichuan Wang +3
We study a sequential resource allocation problem motivated by adaptive network recruitment, in which a limited budget of identical resources must be allocated over multiple rounds…