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Paper Citation Record · LEDGER

The Bias Amplification Paradox in Text-to-Image Generation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2308.00755.

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

pith.paper-citation-record.v1
2308.00755 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:52:59.468045Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T14:07:02.407703Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 81bcf871-5642-4881-ad09-15e9cc5c1dbf · inbound

Mitigate One, Skew Another? Tackling Intersectional Biases in Text-to-Image Models cites this paper.

Mitigate One, Skew Another? Tackling Intersectional Biases in Text-to-Image Models The Bias Amplification Paradox in Text-to-Image Generation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T14:52:59.468045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:52:59.468045Z digest=sha256:c3c97765670f3c10e9f1dda49c852bfceb21e784f6a846fb312de8ce898519b7

Observation 55de9e57-6f95-456b-910f-ce727a6acfcc · inbound

VideoGuard: Protecting Video Content from Unauthorized Editing cites this paper.

VideoGuard: Protecting Video Content from Unauthorized Editing The Bias Amplification Paradox in Text-to-Image Generation

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T04:27:06.007003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:27:06.007003Z digest=sha256:b994adc9008cd9aa8af829b86f17fb6901936178ad451ceaec21540cb1127013

Observation 43af72db-905f-4b45-bd6a-33782115452d · inbound

Inference Time Debiasing Concepts in Diffusion Models cites this paper.

Inference Time Debiasing Concepts in Diffusion Models The Bias Amplification Paradox in Text-to-Image Generation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T18:47:20.813846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:47:20.813846Z digest=sha256:5abd59ec75cb70ee27018dc0064af7a98a87e43a3730bc3338bc73823a2982f9

Observation 69b46adf-5dd1-4907-b5e0-6b9d8abb7b90 · inbound

Understanding and evaluating computer vision models through the lens of counterfactuals cites this paper.

Understanding and evaluating computer vision models through the lens of counterfactuals The Bias Amplification Paradox in Text-to-Image Generation

Reference 196

Resolution
unresolved
no resolver link, observed 2026-08-05T14:49:31.738335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:49:31.738335Z digest=sha256:6d0d5f7104160c7e6af79bc3a87e37018cfef2817c343a941e9e497e6abd3444

Observation ba96c041-587e-491f-9442-7c5ec5b81594 · inbound

Prompting Away Stereotypes? Evaluating Bias in Text-to-Image Models for Occupations cites this paper.

Prompting Away Stereotypes? Evaluating Bias in Text-to-Image Models for Occupations The Bias Amplification Paradox in Text-to-Image Generation

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-05T13:11:56.907024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:11:56.907024Z digest=sha256:556fd0261f59b5b95204ebf4f102be6171690a58ac056f7bb07e2eb643a3974a

Observation aefcc969-9ed5-40df-9a0b-63fb8dc5276d · inbound

T2I-BiasBench: A Multi-Metric Framework for Auditing Demographic and Cultural Bias in Text-to-Image Models cites this paper.

T2I-BiasBench: A Multi-Metric Framework for Auditing Demographic and Cultural Bias in Text-to-Image Models The Bias Amplification Paradox in Text-to-Image Generation

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:11:14.963806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T15:35:07.057690Z digest=sha256:8c743f45a97edc2236c5727ace145aee15e664fe9676b4ec4df4ca38ab2d9da3

Observation 1825543b-c0ad-4389-a571-12bef5d70080 · inbound

Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning cites this paper.

Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning The Bias Amplification Paradox in Text-to-Image Generation

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-20T15:08:24.772390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-20T15:06:53.377360Z digest=sha256:9f3fc76a6a7e5d6ac97bc57dba7e2f07001d9efc268f8059d49718c0c8965965

Observation c44de37f-b2be-4e61-bb3d-08ca6895a10c · inbound

Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization cites this paper.

Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization The Bias Amplification Paradox in Text-to-Image Generation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-02T14:07:02.409471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-02T13:57:40.983894Z digest=sha256:27f1ce75fb8249ec33c100ceb2122ea3e1e04181244f0cf5fc102df52e9411e4