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Paper Citation Record · LEDGER

Interpretable Diffusion Models with B-cos Networks

As of 7 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2507.03846.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.03846 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:07:04.816368Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

  • verified exact0
  • verified fuzzy15
  • unresolved11
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 778b3478-b2c7-472c-9988-3e69c47c693a · outbound

This paper cites write newline.

Interpretable Diffusion Models with B-cos Networks write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:07:02.516100Z digest=sha256:0880e1f88fa81026f76c27fe006cced259c30a9df49c7389c0c07df2d7c1c7a5

Observation 9701121f-799e-46d9-a248-6d983eb61be9 · outbound

This paper cites B-cosification: Transforming deep neural networks to be inherently interpretable.

Interpretable Diffusion Models with B-cos Networks B-cosification: Transforming deep neural networks to be inherently interpretable

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 88ef6840-3540-4bd9-858b-14fcb276dc58 · outbound

This paper cites On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation.

Interpretable Diffusion Models with B-cos Networks On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f3a9d181-eb9b-4d6e-a153-b1b59764f6cc · outbound

This paper cites Is attention explanation? an introduction to the debate.

Interpretable Diffusion Models with B-cos Networks Is attention explanation? an introduction to the debate

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 47800a55-8c31-4d9c-815d-43aff0321655 · outbound

This paper cites B-cos networks: Alignment is all we need for interpretability.

Interpretable Diffusion Models with B-cos Networks B-cos networks: Alignment is all we need for interpretability

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 683fd3a8-42ec-4707-96d2-484559a811d4 · outbound

This paper cites B-cos alignment for inherently interpretable cnns and vision transformers.

Interpretable Diffusion Models with B-cos Networks B-cos alignment for inherently interpretable cnns and vision transformers

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation ae83feb2-694c-44ec-b976-1ad74ee93ca2 · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

Interpretable Diffusion Models with B-cos Networks CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 516a2bcd-ddf7-41c1-b498-acdd487f5166 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Interpretable Diffusion Models with B-cos Networks Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 8

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Observation 4b16fedb-b6ec-4ec1-8487-52d6a342c727 · outbound

This paper cites Denoising diffusion probabilistic models.

Interpretable Diffusion Models with B-cos Networks Denoising diffusion probabilistic models

Reference 9

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no resolver link, observed 2026-08-06T20:07:03.291066Z

Source-reported events for the cited work

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Observation fe3d30bc-a122-400d-8cd6-75a9e7671e14 · outbound

This paper cites an unresolved cited work.

Interpretable Diffusion Models with B-cos Networks Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 217b3051-19f3-4e57-8b14-3fc2d58d83bf · outbound

This paper cites Self-discovering interpretable diffusion latent directions for responsible text-to-image generation.

Interpretable Diffusion Models with B-cos Networks Self-discovering interpretable diffusion latent directions for responsible text-to-image generation

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation b8143e45-507a-4fde-bd71-d36be502c1b6 · outbound

This paper cites an unresolved cited work.

Interpretable Diffusion Models with B-cos Networks Unresolved cited work

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 175016d0-e8c0-4b89-a3ba-64b5a696b021 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

Interpretable Diffusion Models with B-cos Networks W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 13

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no resolver link, observed 2026-08-06T20:07:03.784623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 51ce228a-071b-43fb-8644-f54d8515fcfc · outbound

This paper cites why should i trust you?.

Interpretable Diffusion Models with B-cos Networks why should i trust you?

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f291a395-f708-4791-970d-8b428043eace · outbound

This paper cites S., and Teixeira, L.

Interpretable Diffusion Models with B-cos Networks S., and Teixeira, L

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 0c1a4531-898d-4114-9b77-16e92ed42ac3 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Interpretable Diffusion Models with B-cos Networks High-resolution image synthesis with latent diffusion models

Reference 16

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Source-reported events for the cited work

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Observation 229c0883-4ed8-482b-a55f-d27bbf8e4948 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Interpretable Diffusion Models with B-cos Networks U-net: Convolutional networks for biomedical image segmentation

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 15d5081a-4c69-4322-8653-1ec142e5cd0f · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Interpretable Diffusion Models with B-cos Networks Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation e88c06a3-4e20-4070-9947-18ca19a07d29 · outbound

This paper cites Denoising diffusion implicit models.

Interpretable Diffusion Models with B-cos Networks Denoising diffusion implicit models

Reference 19

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Observation 47585e18-6fb2-43fb-82c9-ff2979b86daa · outbound

This paper cites and Fleuret, F.

Interpretable Diffusion Models with B-cos Networks and Fleuret, F

Reference 20

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 2dc999d4-6dc3-471e-9e4f-f549651989e4 · outbound

This paper cites What the DAAM : Interpreting stable diffusion using cross attention.

Interpretable Diffusion Models with B-cos Networks What the DAAM : Interpreting stable diffusion using cross attention

Reference 21

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation bb5ef4ae-844c-4653-9e97-f17d25381572 · outbound

This paper cites Diffuse attend and segment: Unsupervised zero-shot segmentation using stable diffusion.

Interpretable Diffusion Models with B-cos Networks Diffuse attend and segment: Unsupervised zero-shot segmentation using stable diffusion

Reference 22

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 16629e78-eb5c-48ce-8cfb-f8abafc90573 · outbound

This paper cites J., Theis, F.

Interpretable Diffusion Models with B-cos Networks J., Theis, F

Reference 23

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 747105d3-042f-44c8-82d9-0fb96d883f24 · outbound

This paper cites Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter.

Interpretable Diffusion Models with B-cos Networks Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:07:04.763938Z digest=sha256:2bf901f4bf49630d6173524c759e55c773caebcf120c28e3f9c28d7e30d06d1b

Observation 1f72640a-4d50-4742-8802-5abf33f921b4 · outbound

This paper cites On Discrete Prompt Optimization for Diffusion Models.

Interpretable Diffusion Models with B-cos Networks On Discrete Prompt Optimization for Diffusion Models

Reference 25

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:07:04.780914Z digest=sha256:7663290ee053a4ec182037d1b7f4df4a59ec310330f85bb47a0131d2a7a347bb

Observation c4a83485-6cc9-42ed-8248-6e6092250b03 · outbound

This paper cites Prompt-free diffusion: Taking" text" out of text-to-image diffusion models.

Interpretable Diffusion Models with B-cos Networks Prompt-free diffusion: Taking" text" out of text-to-image diffusion models

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-08-06T20:07:04.816368Z digest=sha256:db370821559359652f14089237a3d02ae0133b66186d0e1164edba4ede76508c

Pith citing papers

No inbound Pith citation observations are available.