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pith:2026:QIGCND7F5EA5UUZFFISGBCF4LU
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Few Channels Draw The Whole Picture: Revealing Massive Activations in Diffusion Transformers

Davide Bucciarelli, Evelyn Turri, Lorenzo Baraldi, Marcella Cornia, Sara Sarto

A small set of massive activation channels in Diffusion Transformers controls image semantics in function, space, and transfer.

arxiv:2605.13974 v1 · 2026-05-13 · cs.CV · cs.AI · cs.MM

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Claims

C1strongest claim

despite their sparsity, these few channels effectively draw the whole picture, in three complementary senses: functionally critical, spatially organized, and transferable.

C2weakest assumption

That the identification of massive channels via magnitude statistics is stable across prompts and models and that the controlled disruption probe isolates their causal role without confounding effects from the rest of the network dynamics.

C3one line summary

A sparse set of massive activation channels in DiTs carries semantic information, proven critical by disruption tests, spatially aligned with image subjects via clustering, and transferable for semantic interpolation between prompts.

References

41 extracted · 41 resolved · 4 Pith anchors

[1] Building normalizing flows with stochastic interpolants 2023
[2] All are Worth Words: A ViT Backbone for Diffusion Models 2023
[3] Tiny Inference-Time Scaling with Latent Verifiers 2026
[4] SANA-Sprint: One-Step Diffusion with Continuous-Time Consistency Distillation 2025
[5] Vision Transformers Need Registers 2024
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First computed 2026-05-17T23:39:13.458382Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

820c268fe5e901da53252a246088bc5d17b86e8743f2d57332aefa6ff59f0df3

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arxiv: 2605.13974 · arxiv_version: 2605.13974v1 · doi: 10.48550/arxiv.2605.13974 · pith_short_12: QIGCND7F5EA5 · pith_short_16: QIGCND7F5EA5UUZF · pith_short_8: QIGCND7F
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Canonical record JSON
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