Why Does Feedback-Augmented Self-Distillation Fail to Improve Retrieval-Interleaved Search Agents?
This work instantiates Feedback-Augmented Self-Distillation (FA-SD), a self-distillation algorithm for agentic search that leverages successful demonstrations as privileged information and identifies that models can rely on recurring reasoning-and-search output templates, producing trajectories that appear diverse but...