# TinyAstral

TinyAstral moves the improvement target outside the robot agent's planner: an open-weight teacher is frozen while frontier LLM agents read its trajectories and propose harness edits, each accepted only if it passes a paired statistical test, lifting the teacher's strict RoboTwin success from 33.4% to 63.6%. The final harness is then frozen and the teacher's reasoning and failure-recovery trajectories are distilled into a 4B student, which reaches 62.8% in that same harness and tracks its corresponding teacher across four harness versions.

TinyAstral moves the improvement target outside the robot agent's planner: an open-weight teacher is frozen while frontier LLM agents read its trajectories and propose harness edits, each accepted only if it passes a paired statistical test, lifting the teacher's strict RoboTwin success from 33.4% to 63.6%. The final harness is then frozen and the teacher's reasoning and failure-recovery trajectories are distilled into a 4B student, which reaches 62.8% in that same harness and tracks its corresponding teacher across four harness versions.