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Paper Citation Record · LEDGER

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.03831.

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

pith.paper-citation-record.v1
2607.03831 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T23:39:16.487501Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

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Outbound references

Observation 3760a803-ae8b-4a31-867a-af99c2475ab8 · outbound

This paper cites Clip under the microscope: A fine-grained analysis of multi-object representation.2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9308–9317, 2025.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Clip under the microscope: A fine-grained analysis of multi-object representation.2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9308–9317, 2025

Reference 1

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Observation b9613bc2-11cf-4973-aeed-eb75520a94db · outbound

This paper cites Compositionality in con- trastive vision-language models: A survey of methods and benchmarks.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Compositionality in con- trastive vision-language models: A survey of methods and benchmarks

Reference 2

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Observation 0128c90e-d845-42f5-be88-5a96ef5bfa69 · outbound

This paper cites Improving image genera- tion with better captions, 2023.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Improving image genera- tion with better captions, 2023

Reference 3

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:727b7629cd77ff913fde8069ade1e280deb162e85c9083108f78595c3a96cd5d

Observation fd51f98c-31d6-4b0b-981b-dfc7e33e7edf · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 4

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:c183225fd5414aa1106f3718fa332a7eec57cfe676c4b3e735016675254e39b3

Observation 2e42127c-3de6-49aa-9926-b5bcd2953e07 · outbound

This paper cites Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, and Karsten Kreis.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, and Karsten Kreis

Reference 5

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:39ed9549c3bf2326c2a14d54933d9aa272df8e64c8faf31166d1303db4f0d2b8

Observation e072d46a-6362-4c36-9470-e3859ca09db2 · outbound

This paper cites Text-to-Image Diffusion Models are Zero-Shot Classifiers.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Text-to-Image Diffusion Models are Zero-Shot Classifiers

Reference 6

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:ebac8923249df18d0ac5628b68c12b58d2e9e5f417d3b23f5177531fde2d5dbf

Observation 9c10627d-05b8-484f-8fdf-1a4fa845ef6d · outbound

This paper cites Fast Timing-Conditioned Latent Audio Diffusion.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Fast Timing-Conditioned Latent Audio Diffusion

Reference 7

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:2a2c3fb3c35ca3f89ddaf3c9ddf639e3ccef6bc13b27eebd01352278f33749e3

Observation 129fe194-c5e3-4675-b942-0ac43f4fe283 · outbound

This paper cites Geneval: An object-focused framework for evaluating text- to-image alignment.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Geneval: An object-focused framework for evaluating text- to-image alignment

Reference 8

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Observation e3cbca4d-6198-4168-9b08-a74ae33e333f · outbound

This paper cites an unresolved cited work.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Unresolved cited work

Reference 9

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:4e3a464ec75110639a6c2053a4a323e911b21657024bd962eefcce53f2abb6d5

Observation 3197062a-4f32-427f-9442-5b11ac049a0a · outbound

This paper cites Narayana, Sugato Basu, William Yang Wang, and Xin Eric Wang.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Narayana, Sugato Basu, William Yang Wang, and Xin Eric Wang

Reference 10

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Observation 2892d4ca-5631-4e46-b5e8-10eb9857c4b9 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Denoising Diffusion Probabilistic Models

Reference 11

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:581142766227660fa605dffa30c7cf5e0a5aebe3880d730abcbdcc8c6e620f99

Observation 11f54a29-f23b-434e-b1c2-8aff5ace7bdd · outbound

This paper cites an unresolved cited work.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Unresolved cited work

Reference 12

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:5e35a2cee25ad1ed93cbcd8f9a504e688e3d5c382e0e613d5ee7c0ba5643df2c

Observation bd582801-2ee6-4742-abd1-314d28706d72 · outbound

This paper cites Diffusion classifiers understand compositional- ity, but conditions apply.ArXiv, abs/2505.17955, 2025.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Diffusion classifiers understand compositional- ity, but conditions apply.ArXiv, abs/2505.17955, 2025

Reference 13

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:26d2be7b76e72e4d374dedf94bbcf83b4fb6a6031544a00cf10a60df221310be

Observation eea2b085-bf60-4e5f-a62d-4f279a0f1cad · outbound

This paper cites V oleti, Christopher Joseph Pal, and Siva Reddy.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation V oleti, Christopher Joseph Pal, and Siva Reddy

Reference 14

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Observation 312dfbc6-6b9b-4398-b5d2-56350b347d2b · outbound

This paper cites Li, Mihir Prabhudesai, Shivam Duggal, Ellis Brown, and Deepak Pathak.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Li, Mihir Prabhudesai, Shivam Duggal, Ellis Brown, and Deepak Pathak

Reference 15

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Observation cf889587-eff1-496e-9c30-165256775708 · outbound

This paper cites Crepe: Can vision- language foundation models reason compositionally?2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10910–10921, 2023.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Crepe: Can vision- language foundation models reason compositionally?2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10910–10921, 2023

Reference 16

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Observation 28c76dbd-f58a-4ca6-be03-b00312df7345 · outbound

This paper cites Khan, and Fahad Shahbaz Khan.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Khan, and Fahad Shahbaz Khan

Reference 17

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Observation 3426a218-fd08-4abe-8a72-335247410ca9 · outbound

This paper cites Dick, and Hidenori Tanaka.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Dick, and Hidenori Tanaka

Reference 18

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:18349bd4af8b2f1e4aecc65191893a18d7ed49b6d5e1152a4cd0152eb1c1c170

Observation 09eecf3f-0e06-4647-b0b8-6611f0689ed9 · outbound

This paper cites Learning transferable visual models from natural language supervision.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Learning transferable visual models from natural language supervision

Reference 19

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Observation 7eaed040-c248-47d6-89b2-1b80f12d11cf · outbound

This paper cites Blattmann, Dominik Lorenz, Patrick Esser, and Bj ¨orn Ommer.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Blattmann, Dominik Lorenz, Patrick Esser, and Bj ¨orn Ommer

Reference 20

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Observation e7309cec-6b5c-446d-ac0d-1f0747ea36ec · outbound

This paper cites Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

Reference 21

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Observation 5b3c5a5d-fdd7-4ddb-9179-29b0a0bc75df · outbound

This paper cites Kingma, Ab- hishek Kumar, Stefano Ermon, and Ben Poole.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Kingma, Ab- hishek Kumar, Stefano Ermon, and Ben Poole

Reference 22

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Observation fa5620e1-151c-4e84-84c5-18e86f3f8f58 · outbound

This paper cites What the daam: Interpreting stable dif- fusion using cross attention.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation What the daam: Interpreting stable dif- fusion using cross attention

Reference 23

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Observation 11c313c2-56fd-4cae-b4f9-adf9c6a29c6e · outbound

This paper cites When are lemons purple? the concept association bias of vision-language models.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation When are lemons purple? the concept association bias of vision-language models

Reference 24

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Observation ebfc1bb3-db64-4bab-906a-32a6d67f1f84 · outbound

This paper cites A good crepe needs more than just sugar: Investigating biases in compositional vision-language benchmarks, 2025.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation A good crepe needs more than just sugar: Investigating biases in compositional vision-language benchmarks, 2025

Reference 25

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Observation 74cd8076-f41d-42e0-897f-fe9da9c44a75 · outbound

This paper cites an unresolved cited work.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Unresolved cited work

Reference 26

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Observation 9ddea8af-bba8-4b9f-bf16-39b4ec428ce9 · outbound

This paper cites Noise matters: Optimizing matching noise for diffusion classifiers.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Noise matters: Optimizing matching noise for diffusion classifiers

Reference 27

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source=pdf_text observed=2026-07-11T23:39:16.487501Z digest=sha256:e3b2963359bd203d981a868402d1e5984f378696065b1bc7d51e971840596fdc

Observation e3ab760c-832c-4426-a03d-7c1398c9f10d · outbound

This paper cites ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty

Reference 28

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Observation f9c2575c-58c7-4dbf-b460-144b7b0fdbd4 · outbound

This paper cites Few-Shot Learner Parameterization by Diffusion Time-Steps.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Few-Shot Learner Parameterization by Diffusion Time-Steps

Reference 29

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Observation b5421450-b479-417a-9cd9-3c831cb6b937 · outbound

This paper cites an unresolved cited work.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation Unresolved cited work

Reference 30

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Observation 622c4dbb-e806-4dff-bdf9-22cd6c9ade2e · outbound

This paper cites in a complex scene.

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation in a complex scene

Reference 31

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