arXiv Machine Learning June 2, 2026 By Guanghan Wang, Gilad Turok, Yair Schiff, Marianne Arriola, Volodymyr Kuleshov

d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation

Read the original on arXiv Machine Learning →

arXiv:2509. 21474v4 Announce Type: replace Abstract: While diffusion language models (DLMs) have achieved competitive performance in text generation, improving their reasoning ability with reinforcement learning remains an active research area.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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