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Paper Citation Record · LEDGER

Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.16092.

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

pith.paper-citation-record.v1
2401.16092 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:33:32.205428Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:39:29.448724Z

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 b1761e3e-73f3-4383-880d-7ceb76774317 · 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? Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:04.565145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:04.565145Z digest=sha256:e166c6c0f2b004b84f8ec522adf6060b35d89676b08a7339e22fda23c5cba0b4

Observation 268d88ca-c96c-4ef4-be31-ab05a75dbd2c · inbound

The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participation cites this paper.

The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participation Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-09T10:08:10.418030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:08:10.418030Z digest=sha256:83610ddae6531bc0539961b6ec0469be6f071a0aa2b8c1569e1d2f41cde28ca9

Observation 8f4935d7-f299-43c4-8cdd-be67e39d1496 · inbound

What do people expect from Artificial Intelligence? Public opinion on alignment in AI moderation from Germany and the United States cites this paper.

What do people expect from Artificial Intelligence? Public opinion on alignment in AI moderation from Germany and the United States Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You

Reference 1332

Resolution
unresolved
no resolver link, observed 2026-08-16T12:33:32.205428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:33:32.205428Z digest=sha256:3958ba93fe9ec56d5c79c568dfdeb129735fba43d4c87a2ba3aa5723b596e796

Observation d72cfab3-18e6-48e9-91b5-a235dabc64fd · inbound

NeoBabel: A Multilingual Open Tower for Visual Generation cites this paper.

NeoBabel: A Multilingual Open Tower for Visual Generation Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T19:15:26.989066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:15:26.989066Z digest=sha256:9fe923346dcc9728c1450a8ca8d0a7feee69e1b7a2cac508a97ba1c7ff542fe5

Observation acd9d29a-78fe-4433-8d3f-46d938d258f1 · inbound

BAFIS: Dataset + Framework to assess occupational Bias and Human Preference in modern Text-to-image Models cites this paper.

BAFIS: Dataset + Framework to assess occupational Bias and Human Preference in modern Text-to-image Models Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help You

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:39:29.451551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T17:53:46.206401Z digest=sha256:b825ca41ff44b1009edc7dd6ec0defb678c068caccaf5c1ec09cc7394fdcd110