ForkGRPO: Efficient Exploration and Fine-Grained Credit Assignment for Diffusion Language Models
Branches rollouts from uncertain intermediate states and reuses their shared textual prefixes. Local outcome comparisons assign credit to reasoning segments, testing whether more targeted exploration improves diffusion-model reasoning with fewer generated training tokens.
First public: · Added to this list: October 18, 2026
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arXiv:2610.19408 · Initial submission: 2026-10-14
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Alternative generation methods — Change how intermediate steps are generated, revised, or searched—for example, by refining several steps in parallel. These are related approaches: some still produce written chains of thought.
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