Bandit Learning in Matching Markets with Interviews (opens in new tab)

arXiv:2602.12224v1 Announce Type: cross Abstract: Two-sided matching markets rely on preferences from both sides, yet it is often impractical to evaluate preferences. Participants, therefore, conduct a limited number of interviews, which provide early, noisy impressions and shape final decisions. We study bandit learning in matching markets with interviews, modeling interviews as \textit{low-cost hints} that reveal partial preference information to both sides. Our framework departs from exis...