Announcement_20

[ICLR 2026] “Native Reasoning Models: Training Language Models to Reason on Unverifiable Data” has been accepted to ICLR 2026. 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.