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cs.AI2026
Defense via Consensus: Mitigating Subliminal Learning through Multi-Teacher Distillation
Adhyyan Narang, Artin Tajdini, Claire Zhang +1
Fine-tuning can introduce unwanted behaviors through deliberate poisoning or unexpected generalization from seemingly benign data. Because these effects may be difficult to anticip…
cs.LG2026
Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing
Adhyyan Narang, Sarah Dean, Lillian J Ratliff +1
In many economically relevant contexts where machine learning is deployed, multiple platforms obtain data from the same pool of users, each of whom selects the platform that best s…