Announcement_20

[ICLR 2026] “Native Reasoning Models: Training Language Models to Reason on Unverifiable Data” has been accepted to ICLR 2026; I am the corresponding author. The paper presents Native Reasoning Training, treating reasoning traces as latent variables so language models can learn from standard question-answer pairs without expert-written reasoning demonstrations or external verifiers.