Paper Citation Record · LEDGER

How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2210.15230.

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

pith.paper-citation-record.v1
2210.15230 v1

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 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:34:05.650261Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T11:34:37.765196Z

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 cc8be906-3243-4d11-a28f-71de5b977e95 · inbound

VideoPhy: Evaluating Physical Commonsense for Video Generation cites this paper.

VideoPhy: Evaluating Physical Commonsense for Video Generation How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:34:37.766934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation dc098d3c-874d-46ef-ad2b-a66686bc7cc8 · inbound

Image Generation Diversity Issues and How to Tame Them cites this paper.

Image Generation Diversity Issues and How to Tame Them How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:05.650261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 075052c4-9378-43f0-b0ce-9ae862b61f07 · inbound

Continuous Concepts Removal in Text-to-image Diffusion Models cites this paper.

Continuous Concepts Removal in Text-to-image Diffusion Models How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T05:18:55.928308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8fce792-7e90-4480-9bba-aa16756c3397 · inbound

Negative Token Merging: Image-based Adversarial Feature Guidance cites this paper.

Negative Token Merging: Image-based Adversarial Feature Guidance How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T04:31:05.658701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1962c018-e809-40dc-b36d-8137cb8ec9f8 · inbound

A Framework for Critical Evaluation of Text-to-Image Models: Integrating Art Historical Analysis, Artistic Exploration, and Critical Prompt Engineering cites this paper.

A Framework for Critical Evaluation of Text-to-Image Models: Integrating Art Historical Analysis, Artistic Exploration, and Critical Prompt Engineering How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:02.992537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e69ffd9-76d8-46f4-8807-98cc60226fcb · inbound

On Fairness of Unified Multimodal Large Language Model for Image Generation cites this paper.

On Fairness of Unified Multimodal Large Language Model for Image Generation How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T04:52:40.539422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac8d8f9c-b66e-4e55-ab83-963672003139 · inbound

Multi-Group Proportional Representation for Text-to-Image Models cites this paper.

Multi-Group Proportional Representation for Text-to-Image Models How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:43:32.063884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57174511-c3fb-448e-876e-0fd71bcad8cd · inbound

BiasIG: Benchmarking Multi-dimensional Social Biases in Text-to-Image Models cites this paper.

BiasIG: Benchmarking Multi-dimensional Social Biases in Text-to-Image Models How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:21:00.502391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.