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Paper Citation Record · LEDGER

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment

As of 14 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2607.05605.

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

pith.paper-citation-record.v1
2607.05605 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T05:04:54.584862Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

29 of 29 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e4a4889-4808-4f3c-b600-805251fd4868 · outbound

This paper cites Musiq: Multi- scale image quality transformer,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Musiq: Multi- scale image quality transformer,

Reference 1

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Observation 4eac5d19-bdcc-42a9-8694-312222ef4ec7 · outbound

This paper cites Maniqa: Multi-dimension attention network for no-reference image quality assessment,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Maniqa: Multi-dimension attention network for no-reference image quality assessment,

Reference 2

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Observation 5c647be5-027a-4113-af25-29aaf9634eee · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 248240148.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Available: https://api.semanticscholar.org/CorpusID: 248240148

Reference 3

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Observation 2a072507-3aea-4075-8747-b6b8b4ca9788 · outbound

This paper cites Bringing textual prompt to ai-generated image quality assessment,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Bringing textual prompt to ai-generated image quality assessment,

Reference 4

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Observation d2ccf236-e7ed-4e2e-ac1c-1f714591e287 · outbound

This paper cites PKU-I2IQA: An Image-to-Image Quality Assessment Database for AI Generated Images.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment PKU-I2IQA: An Image-to-Image Quality Assessment Database for AI Generated Images

Reference 5

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verified exact
local_arxiv, observed 2026-07-11T05:07:48.389521Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 617ab31b-70e0-42b5-a94a-15dfdc948cb5 · outbound

This paper cites PSCR: Patches Sampling-based Contrastive Regression for AIGC Image Quality Assessment.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment PSCR: Patches Sampling-based Contrastive Regression for AIGC Image Quality Assessment

Reference 6

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local_arxiv, observed 2026-07-11T05:07:48.396398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 2891d365-f4d3-4feb-95d7-187b9f540610 · outbound

This paper cites Aigc image quality assessment via image-prompt correspondence,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Aigc image quality assessment via image-prompt correspondence,

Reference 7

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Observation 528299c2-c9f5-413e-aae9-081357275bcb · outbound

This paper cites Sf-iqa: Quality and similarity integration for ai generated image quality assessment,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Sf-iqa: Quality and similarity integration for ai generated image quality assessment,

Reference 8

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Observation 5bb51768-29be-424a-8742-35ca91f7f253 · outbound

This paper cites Moe-agiqa: Mixture-of-experts boosted visual perception-driven and semantic-aware quality assessment for ai-generated images,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Moe-agiqa: Mixture-of-experts boosted visual perception-driven and semantic-aware quality assessment for ai-generated images,

Reference 9

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Observation 9e84506d-0aa4-4236-886b-30cd7f322083 · outbound

This paper cites Adaptive mixed-scale feature fusion network for blind ai-generated image quality assessment,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Adaptive mixed-scale feature fusion network for blind ai-generated image quality assessment,

Reference 10

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Observation a7529081-df37-4eab-80b2-d85becc53dcf · outbound

This paper cites Align-iqa: Aligning image quality assessment models with diverse human preferences via customizable guidance,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Align-iqa: Aligning image quality assessment models with diverse human preferences via customizable guidance,

Reference 11

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Observation 973f98ef-c31a-4eb4-a435-17a927443c81 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 273646294.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Available: https://api.semanticscholar.org/CorpusID: 273646294

Reference 12

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Observation c472d62a-19cb-4994-87b5-0f50b5ea8ed3 · outbound

This paper cites AI-Generated Image Quality Assessment Based on Task-Specific Prompt and Multi-Granularity Similarity.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment AI-Generated Image Quality Assessment Based on Task-Specific Prompt and Multi-Granularity Similarity

Reference 13

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verified exact
local_arxiv, observed 2026-07-11T05:07:48.382126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation d5f00801-bd6b-4f55-b7b4-c0815b985762 · outbound

This paper cites A Perceptual Quality Assessment Exploration for AIGC Images.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment A Perceptual Quality Assessment Exploration for AIGC Images

Reference 14

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Observation 6fd70ed9-7a6d-494f-9020-373c8dd33460 · outbound

This paper cites Agiqa-3k: An open database for ai-generated image quality assessment,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Agiqa-3k: An open database for ai-generated image quality assessment,

Reference 15

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source=pdf_text observed=2026-07-11T05:04:54.584862Z digest=sha256:9ab65d63e711dbc977812a98114bd072735c5db520a223e084fb76b64f30da81

Observation b0e8b02d-b5be-4c98-8a6f-ae3dc5b94e90 · outbound

This paper cites AIGCIQA2023: A Large-scale Image Quality Assessment Database for AI Generated Images: from the Perspectives of Quality, Authenticity and Correspondence.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment AIGCIQA2023: A Large-scale Image Quality Assessment Database for AI Generated Images: from the Perspectives of Quality, Authenticity and Correspondence

Reference 16

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Observation c23906e7-3834-4335-b465-0b3a838834f3 · outbound

This paper cites PKU-AIGIQA-4K: A Perceptual Quality Assessment Database for Both Text-to-Image and Image-to-Image AI-Generated Images.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment PKU-AIGIQA-4K: A Perceptual Quality Assessment Database for Both Text-to-Image and Image-to-Image AI-Generated Images

Reference 17

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verified exact
local_arxiv, observed 2026-07-11T05:07:48.402416Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-07-11T05:04:54.584862Z digest=sha256:7792e667fbc3e3517e56a327fcb6345408bc1f63d479e504c287edf536429587

Observation d6e25b5f-489c-41d6-a5ae-f1ac3328d95c · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 269449873.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Available: https://api.semanticscholar.org/CorpusID: 269449873

Reference 18

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Observation ce881e5b-6523-42e5-abd4-483f766c43e2 · outbound

This paper cites Clip-agiqa: Boosting the performance of ai-generated image quality assessment with clip,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Clip-agiqa: Boosting the performance of ai-generated image quality assessment with clip,

Reference 19

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Observation dc8e9e32-7ab7-4e8b-a725-cb5713af33f4 · outbound

This paper cites Exploring clip for assessing the look and feel of images,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Exploring clip for assessing the look and feel of images,

Reference 20

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Observation 1a538fa3-26ad-45cf-9275-312a6f279ef4 · outbound

This paper cites Blind image quality assessment via vision-language correspondence: A multitask learning perspective,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Blind image quality assessment via vision-language correspondence: A multitask learning perspective,

Reference 21

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Observation a60d0568-57a0-4c80-a7e2-890a35923d8f · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Adam: A Method for Stochastic Optimization

Reference 22

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Observation 5d25ade7-724f-45dd-a8da-40a1d746997f · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 23

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Observation 9e0533a5-bb01-4024-a304-e2207a3d0d3e · outbound

This paper cites Blindly assess image quality in the wild guided by a self-adaptive hyper network,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Blindly assess image quality in the wild guided by a self-adaptive hyper network,

Reference 24

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Observation 8ba08850-c04b-4890-9e52-3d985babb6f5 · outbound

This paper cites Blind quality assess- ment for in-the-wild images via hierarchical feature fusion strategy,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Blind quality assess- ment for in-the-wild images via hierarchical feature fusion strategy,

Reference 25

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T05:04:54.584862Z digest=sha256:0f747a42393daa8f34a7969e083dac5d9c2f956b33e024e8dee8b69cd3a65314

Observation 89e9119b-5677-4464-b255-6316e8fd7bc2 · outbound

This paper cites Re-iqa: Unsupervised learning for image quality assessment in the wild,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Re-iqa: Unsupervised learning for image quality assessment in the wild,

Reference 26

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Observation 28f7103c-8a58-49ef-844c-99fde2f41954 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 257913460.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Available: https://api.semanticscholar.org/CorpusID: 257913460

Reference 27

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Observation d4573573-eb9e-4cd4-9a48-b3d730c15212 · outbound

This paper cites Aigiqa-20k: A large database for ai-generated image quality assessment,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Aigiqa-20k: A large database for ai-generated image quality assessment,

Reference 28

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Observation 92276de7-1b78-4907-b0ab-00d404e0691e · outbound

This paper cites Norm-in-norm loss with faster con- vergence and better performance for image quality assessment,.

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment Norm-in-norm loss with faster con- vergence and better performance for image quality assessment,

Reference 29

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arxiv_id, observed 2026-07-11T05:07:48.351613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Pith citing papers

No inbound Pith citation observations are available.