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TTPO: Test-Time Policy Optimization

72 upvotes · 27 AUG 2026 · Aozhe Wang, Zhengxi Lu, Jianze Wang et al.

This paper proposes a new method called Test-Time Policy Optimization (TTPO) that allows large language models to be trained without ground-truth labels, enabling test-time training. Practitioners may care about this because it enables models to be trained without labels, which can be difficult or expensive to obtain.

reinforcement learningcontinual learningon-policy self-distillationtest-time trainingpseudo-labels