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Paper Citation Record · LEDGER

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2501.09014.

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

pith.paper-citation-record.v1
2501.09014 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:15:21.544522Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

34 of 34 outbound references displayed

  • verified exact4
  • verified fuzzy19
  • unresolved11
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 78c1fa22-d6d6-430d-bf35-35a1a3a51119 · outbound

This paper cites Large-scale text-to-image generation models for visual artists’ creative works,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Large-scale text-to-image generation models for visual artists’ creative works,

Reference 1

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Source-reported events for the cited work

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Observation 2b6fcfde-8fef-4ad4-958d-6307ecb9f30c · outbound

This paper cites AI Image Statistics for 2024: How Much Content Was Created by AI,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias AI Image Statistics for 2024: How Much Content Was Created by AI,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2c1bef55-2668-47f8-873e-84694e017e74 · outbound

This paper cites Easily accessible text-to-image generation amplifies demographic stereotypes at large scale,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Easily accessible text-to-image generation amplifies demographic stereotypes at large scale,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f142c2a3-c70f-4623-96e4-407f5455c7c5 · outbound

This paper cites Social biases through the text-to-image gener- ation lens,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Social biases through the text-to-image gener- ation lens,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.415281Z digest=sha256:630a83954641f3f299d180aca74e39627c330548001d438698e0aa9155d1b25f

Observation d8c48850-1706-4bf6-bf09-2d682cd120ae · outbound

This paper cites Data-driven analysis of gender fairness in the software engineering academic landscape,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Data-driven analysis of gender fairness in the software engineering academic landscape,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a3fee73a-2bf2-49b5-919a-f7d8830e7aad · outbound

This paper cites Uncovering gender gap in academia: A comprehensive analysis within the software engineering community,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Uncovering gender gap in academia: A comprehensive analysis within the software engineering community,

Reference 6

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raw_fallback, observed 2026-08-10T20:15:22.509330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7b820802-07eb-4ab5-94de-f2ab103c5496 · outbound

This paper cites Understanding fairness in software engineering: Insights from stack exchange sites,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Understanding fairness in software engineering: Insights from stack exchange sites,

Reference 7

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raw_fallback, observed 2026-08-10T20:15:22.494588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.430058Z digest=sha256:3f4f233f75b77033a826cc4d056fc0560c54c1a5bd31e742a97762fa9f1d7ad9

Observation 787ea564-4f6c-4bea-a65b-15981eb62e2d · outbound

This paper cites Perceived diversity in software engineering: a systematic literature review,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Perceived diversity in software engineering: a systematic literature review,

Reference 8

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no resolver link, observed 2026-08-10T20:15:21.434391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 803cf92e-4b90-4f25-ae25-d53b5e373119 · outbound

This paper cites It is Giving Major Satisfaction: Why Fairness Matters for Software Practitioners.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias It is Giving Major Satisfaction: Why Fairness Matters for Software Practitioners

Reference 9

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no resolver link, observed 2026-08-10T20:15:21.438812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:15:21.438812Z digest=sha256:e3f172cb21595ad652d51cfee4f58c83a850f66bfab5ad617942b261e9368079

Observation 06c7320c-e506-4bc5-950b-8cab004bfb89 · outbound

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

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias High- resolution image synthesis with latent diffusion models,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.443700Z digest=sha256:7f2e02168668ef5827272e78ed12c6b72f9158144de4bc77f433eb4bd15ea5ac

Observation a4dbe2ae-f809-4ac6-a6e5-f791a2e54943 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:15:21.448510Z digest=sha256:fd160e1cfbd55ef0b446f72965a6ba52a7dd5916c5ff12be6d60aade87d64039

Observation b73a7de0-c445-4264-b423-31a56983bb32 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Scaling rectified flow transformers for high-resolution image synthesis,

Reference 12

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.453456Z digest=sha256:f4bee54f75b2fa606921189bd3b2c798efe110c581da65ea414ac79d6c1a4bdd

Observation 1c421375-b75c-4c96-b4c1-50ea68609dbd · outbound

This paper cites A case study of fairness in generated images of Large Language Models for Software Engineering tasks,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias A case study of fairness in generated images of Large Language Models for Software Engineering tasks,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation dd2549ae-ddb7-465e-8c88-0a8988b4b1ef · outbound

This paper cites She Elicits Requirements and He Tests: Software Engineering Gender Bias in Large Language Models,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias She Elicits Requirements and He Tests: Software Engineering Gender Bias in Large Language Models,

Reference 14

Resolution
verified exact
raw_fallback, observed 2026-08-10T20:15:22.041369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b900a67d-7ee7-499e-8593-70d34b6a744c · outbound

This paper cites Replication Package,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Replication Package,

Reference 15

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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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.465638Z digest=sha256:d844dba7d9e46699e692bbb3c587aa8725e66d1941d834ff2bf646e983aed5c7

Observation 1ce9f210-58b6-4f3b-b3ae-15c6c6ab7a25 · outbound

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

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias High- resolution image synthesis with latent diffusion models,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9443294f-48d3-42e8-8f08-0a4a52c9a3a6 · outbound

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

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Laion- 5b: An open large-scale dataset for training next generation image-text models,

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 314a2c8a-110f-4a32-8cd1-0958cc7d741e · outbound

This paper cites Smiling women pitching down: auditing representational and presentational gender biases in image-generative ai,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Smiling women pitching down: auditing representational and presentational gender biases in image-generative ai,

Reference 18

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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 2026-08-18T06:34:40.430872+00:00.

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Observation d34c1c91-7575-4653-ba3a-416a29b29adc · outbound

This paper cites Stable Bias: Evaluating Societal Representations in Diffusion Models,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Stable Bias: Evaluating Societal Representations in Diffusion Models,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4c0beffb-09d0-4916-bf29-bbf19ef02bc8 · outbound

This paper cites Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f2b4456d-2ea5-4961-8074-82b7e6b03b14 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 21

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Unavailable: canonical work link unavailable.

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Observation c48df531-4873-467a-ac7b-cc447a6c64d0 · outbound

This paper cites Organizational research: Determining appro- priate sample size in survey research appropriate sample size in survey research,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Organizational research: Determining appro- priate sample size in survey research appropriate sample size in survey research,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 099d20f3-e99d-4b7b-b992-6b4f5ea74328 · outbound

This paper cites A coefficient of agreement as a measure of thematic classification accuracy.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias A coefficient of agreement as a measure of thematic classification accuracy

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 64cee9a7-5c1a-4575-96bc-c09c2833d5e1 · outbound

This paper cites Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool,

Reference 24

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Source-reported events for the cited work

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Observation 9871b810-3810-401c-95ea-2e7719c7756c · outbound

This paper cites On the use of evaluation measures for defect prediction studies,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias On the use of evaluation measures for defect prediction studies,

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f1af31bf-a050-499c-a0c4-997610aeda7d · outbound

This paper cites The misgendering machines: Trans/hci implications of au- tomatic gender recognition,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias The misgendering machines: Trans/hci implications of au- tomatic gender recognition,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-10T20:15:22.351155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6533784c-4933-4c07-985d-8d065bc72a27 · outbound

This paper cites Debiaser for Multiple Variables to enhance fairness in classification tasks,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Debiaser for Multiple Variables to enhance fairness in classification tasks,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T20:15:21.519369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bc7cadd1-0206-477b-8899-6f7aa4dfcb67 · outbound

This paper cites Democratizing quality- based machine learning development through extended feature models,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Democratizing quality- based machine learning development through extended feature models,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-10T20:15:22.334523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4fe2bdbd-48b2-4535-af9c-c922f75bcd73 · outbound

This paper cites Weerts, An Introduction to Responsible Machine Learning, 2024.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Weerts, An Introduction to Responsible Machine Learning, 2024

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-10T20:15:22.319817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.527509Z digest=sha256:ab2eeedaf9594e79d72b7f8d6d5f9a60514ca4059cfb42116b4c2b395e98a122

Observation eeb428ce-76ed-4d57-a7ed-6d1dcf0892f4 · outbound

This paper cites Greenstableyolo: Optimizing inference time and image quality of text- to-image generation,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Greenstableyolo: Optimizing inference time and image quality of text- to-image generation,

Reference 30

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raw_fallback, observed 2026-08-10T20:15:22.305390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a0bd73f5-f4c8-412b-9249-8731afad734a · outbound

This paper cites Search-based software engineering in the era of modern software systems,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Search-based software engineering in the era of modern software systems,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-10T20:15:22.290320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.535934Z digest=sha256:63cef63a561cae7bcf79ca1cff4619efb4f53d94551b641bc844b17c0833ba00

Observation 78825a9b-e89f-498c-b230-03f71e3a62bc · outbound

This paper cites Multi-objective search for gender-fair and semantically correct word embeddings,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Multi-objective search for gender-fair and semantically correct word embeddings,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:15:22.275271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.540477Z digest=sha256:c955e153536c70044b589c0af30db5fb67773b955e4f7ffbb8f5eab55492c63f

Observation 1a7daa50-f410-4f01-bbbd-449c9064cd4b · outbound

This paper cites Search-based automatic repair for fairness and accuracy in decision-making software,.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias Search-based automatic repair for fairness and accuracy in decision-making software,

Reference 33

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verified exact
doi, observed 2026-08-10T20:15:21.581234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T20:15:21.544522Z digest=sha256:9c9453305fa35ba4b35e002631b3bfd707fd808c6db0b0eeb3d59bca5f377a18

Observation d1958c10-42ea-438b-8eb3-9c9d01be1d5a · outbound

This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation.

How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T20:15:21.494606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.