Then Assumption 2 holds withΓ = 1√ 𝐻 (tight), i.e., 𝑑(𝜏, 𝜏 ′) ≤Γ∥𝜏−𝜏 ′ ∥.(108) Moreover, since 𝐻≥1 , the same inequality also holds with any larger constant (e.g.,Γ =1)

Proof 4: Metric compatibility constant for the deviation metric used in experiments: Lemma 1(Metric compatibility for the experimental deviation metric)

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Muninn: Your Trajectory Diffusion Model But Faster

cs.RO · 2026-05-11 · unverdicted · novelty 7.0

Muninn accelerates diffusion trajectory planners up to 4.6x by spending an uncertainty budget to decide when to cache denoiser outputs, preserving performance and certifying bounded deviation from full computation.

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Muninn: Your Trajectory Diffusion Model But Faster cs.RO · 2026-05-11 · unverdicted · none · ref 110
Muninn accelerates diffusion trajectory planners up to 4.6x by spending an uncertainty budget to decide when to cache denoiser outputs, preserving performance and certifying bounded deviation from full computation.

Then Assumption 2 holds withΓ = 1√ 𝐻 (tight), i.e., 𝑑(𝜏, 𝜏 ′) ≤Γ∥𝜏−𝜏 ′ ∥.(108) Moreover, since 𝐻≥1 , the same inequality also holds with any larger constant (e.g.,Γ =1)

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