AI RESEARCH
Self-Verified Distillation: Your Language Model Is Secretly Its Own Synthetic Data Pipeline
arXiv CS.LG
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ArXi:2605.26132v1 Announce Type: cross Can post-trained large language models (LLMs) further improve themselves using only unlabeled prompts, without external teachers or feedback from tools? We study this setting starting only from unlabeled seed questions with no ground-truth solutions, across three reasoning domains: math, science, and coding. We propose Self-Verified Distillation, a simple post-