[2608.05687] Answer First, Reason Later: Commitment Order in Diffusion LLMs

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arXiv:2608.05687 (cs)

[Submitted on 6 Aug 2026]

Title:Answer First, Reason Later: Commitment Order in Diffusion LLMs

Authors:Jewon Yeom, Jaewon Sok, Seonghyeon Park, Jeongjae Park, Hwiyeong Lee, Taesup Kim<br>View a PDF of the paper titled Answer First, Reason Later: Commitment Order in Diffusion LLMs, by Jewon Yeom and 5 other authors

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Abstract:Masked diffusion language models (dLLMs) can commit tokens in any order -- a freedom marketed as their core advantage over autoregressive decoding. We show that on reasoning tasks this freedom is instead the axis of failure. Logging every commitment during decoding of LLaDA-8B on GSM8K, we find that unconstrained (pure) decoding commits the final answer at 15-24% of the trajectory while half the reasoning region is still masked, and collapses to answer-only outputs on up to 90% of problems as the canvas grows. The cause is not the model's termination beliefs -- EOS "pressure" is nearly identical across decoders -- but reachability: whether the sampler may act on those beliefs at distant positions. A 2x2 prompt-decoder design shows that chain-of-thought helps only under ordered commitment (interaction +34.8 percentage points, 95% CI [26.8, 42.8]; without reasoning text the decoders are indistinguishable), an interaction we decompose into a collapse channel and an order channel and replicate on Dream-7B and MATH-500. A single-knob intervention -- frontier-gated commitment -- causally recovers the full gap (0.528 to 0.852) while preserving up to 4x parallel decoding, along a measured frontier whose optimal window flips from w=1 at full refinement to unconstrained at 8 tokens/step. Our results reframe existing window-style samplers, previously motivated by efficiency, as the minimal fix for a reasoning pathology they were never designed to address.

Subjects:

Computation and Language (cs.CL); Artificial Intelligence (cs.AI)

Cite as:<br>arXiv:2608.05687 [cs.CL]

(or<br>arXiv:2608.05687v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.05687

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arXiv-issued DOI via DataCite (pending registration)

Submission history<br>From: Je Won Yeom [view email]<br>[v1]<br>Thu, 6 Aug 2026 07:25:04 UTC (421 KB)

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