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Paper Citation Record · LEDGER

A Friendly Face: Do Text-to-Image Systems Rely on Stereotypes when the Input is Under-Specified?

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.07159.

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

pith.paper-citation-record.v1
2302.07159 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:15:10.493833Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T14:01:05.298643Z

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 1215b9b1-8f03-46e3-98ee-c2eb46e35542 · inbound

The Generative AI Ethics Playbook cites this paper.

The Generative AI Ethics Playbook A Friendly Face: Do Text-to-Image Systems Rely on Stereotypes when the Input is Under-Specified?

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T13:15:10.493833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:15:10.493833Z digest=sha256:c23ee935e87e02259ea29eca1a2f4ed33c50b27208dd549f9a2569173f0d7375

Observation 379d978f-0856-40a9-bcb7-e72e67c611cb · inbound

Do Existing Testing Tools Really Uncover Gender Bias in Text-to-Image Models? cites this paper.

Do Existing Testing Tools Really Uncover Gender Bias in Text-to-Image Models? A Friendly Face: Do Text-to-Image Systems Rely on Stereotypes when the Input is Under-Specified?

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-10T14:01:05.303199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T14:01:04.557953Z digest=sha256:378826aa0f8e503061a21da10676d6d5841e2e7c4fa2484d4392103d1163a6a8