Paper Citation Record · LEDGER

Semantic to Structure: Learning Structural Representations for Infringement Detection

As of 12 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 2 inbound Pith citation observations for arXiv:2502.07323.

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

pith.paper-citation-record.v1
2502.07323 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:08:48.797918Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:45:52.929510Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:44:34.489375Z

Reference resolution

26 of 26 outbound references displayed

verified exact0
verified fuzzy13
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c640a282-31b9-4b41-80b6-bb0abe2244a2 · outbound

This paper cites Image Composition Assessment with Saliency-augmented Multi-pattern Pooling.

Semantic to Structure: Learning Structural Representations for Infringement Detection Image Composition Assessment with Saliency-augmented Multi-pattern Pooling

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.711725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fa63b84-ee7a-4405-94aa-f253826b26c1 · outbound

This paper cites Denoising diffusion probabilistic models,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Denoising diffusion probabilistic models,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.717997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2242f09b-e5b0-4df7-8dea-8e4d5d706cf9 · outbound

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

Semantic to Structure: Learning Structural Representations for Infringement Detection SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.722325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3488ccb2-cfe3-48b8-9e39-a82a49b94176 · outbound

This paper cites Understanding and mitigating copying in diffusion models,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Understanding and mitigating copying in diffusion models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:49.023477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 08820594-c5a9-406f-8853-d921eb86134a · outbound

This paper cites Diffusion art or digital forgery? investigating data replication in diffu- sion models,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Diffusion art or digital forgery? investigating data replication in diffu- sion models,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:49.015079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b19cd4fb-d5cf-4e7e-b249-ee304753396c · outbound

This paper cites Fantastic Copyrighted Beasts and How (Not) to Generate Them.

Semantic to Structure: Learning Structural Representations for Infringement Detection Fantastic Copyrighted Beasts and How (Not) to Generate Them

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.734797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86ff6f27-33bb-4ec7-b212-7df1e4b0ff2a · outbound

This paper cites Evaluating and Mitigating IP Infringement in Visual Generative AI.

Semantic to Structure: Learning Structural Representations for Infringement Detection Evaluating and Mitigating IP Infringement in Visual Generative AI

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.738397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbf0687a-119f-427f-b70a-833d266c2fd0 · outbound

This paper cites An empirical study of training self- supervised vision transformers,.

Semantic to Structure: Learning Structural Representations for Infringement Detection An empirical study of training self- supervised vision transformers,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.740928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99cde99e-f2e3-4632-903e-2ebae17b19fd · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Semantic to Structure: Learning Structural Representations for Infringement Detection DINOv2: Learning Robust Visual Features without Supervision

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.743560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1b51c8b-90b2-4716-9a35-ead547339d7b · outbound

This paper cites Emerging properties in self-supervised vision transformers,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Emerging properties in self-supervised vision transformers,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:49.001685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 75465895-e558-4fcf-a7b4-f39c6bd3808a · outbound

This paper cites Self-supervised Photographic Image Layout Representation Learning.

Semantic to Structure: Learning Structural Representations for Infringement Detection Self-supervised Photographic Image Layout Representation Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.750378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 280b79b6-5313-401c-a0ed-d9538bfad674 · outbound

This paper cites Hierarchical layout-aware graph convolutional network for unified aesthetics assessment,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Hierarchical layout-aware graph convolutional network for unified aesthetics assessment,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.993292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0cbe7079-7b53-4136-94da-8934ad746178 · outbound

This paper cites Object-level attention for aesthetic rating distribution prediction,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Object-level attention for aesthetic rating distribution prediction,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.984544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b8363c01-7af8-407e-a236-416c6216e79a · outbound

This paper cites Adding conditional control to text-to-image diffusion models,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Adding conditional control to text-to-image diffusion models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.975743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6254bbd8-3756-43cf-944d-3a3b42758aaf · outbound

This paper cites Vision transformers for dense prediction,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Vision transformers for dense prediction,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.966502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4df03771-48bd-48ee-a23e-7e9ef23c1153 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

Semantic to Structure: Learning Structural Representations for Infringement Detection A simple framework for contrastive learning of visual representations,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.957779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e5dead6-45aa-441b-84f0-62910f062754 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Momentum contrast for unsupervised visual representation learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.948456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cf99bbf9-5b86-4fe6-8cea-133c353ff5c5 · outbound

This paper cites Microsoft coco: Common objects in context,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Microsoft coco: Common objects in context,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.773913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af58451c-7ebf-4326-ab95-f3ad7a6fa321 · outbound

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

Semantic to Structure: Learning Structural Representations for Infringement Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.776846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af39c11e-8fde-4057-a2bf-55f9abc854a9 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Semantic to Structure: Learning Structural Representations for Infringement Detection LoRA: Low-Rank Adaptation of Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.780203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0abf4eb-5487-436c-8e6b-fada5e46136d · outbound

This paper cites Decoupled Weight Decay Regularization.

Semantic to Structure: Learning Structural Representations for Infringement Detection Decoupled Weight Decay Regularization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.783262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17f041ac-d8c6-487b-a771-a84ade0b87ba · outbound

This paper cites Billion-scale similarity search with gpus,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Billion-scale similarity search with gpus,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.933584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 47231d2c-88c9-4222-b470-703c965efdbd · outbound

This paper cites A self- supervised descriptor for image copy detection,.

Semantic to Structure: Learning Structural Representations for Infringement Detection A self- supervised descriptor for image copy detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.923958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 38a5ee35-ca38-4d6e-a680-54156171e717 · outbound

This paper cites A family of contextual measures of similarity between distributions with application to image retrieval,.

Semantic to Structure: Learning Structural Representations for Infringement Detection A family of contextual measures of similarity between distributions with application to image retrieval,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.914298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ec5ae3b2-d65b-4213-87d3-38fd5ecc7c8e · outbound

This paper cites Deep residual learning for image recognition,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Deep residual learning for image recognition,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:48.794576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4078d23b-874b-4032-8afa-8667983bbafd · outbound

This paper cites Aggregated residual transformations for deep neural networks,.

Semantic to Structure: Learning Structural Representations for Infringement Detection Aggregated residual transformations for deep neural networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:08:48.899828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation 784193e0-7fa7-4c41-970e-390885a53cf6 · inbound

A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets cites this paper.

A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets Semantic to Structure: Learning Structural Representations for Infringement Detection

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:52.929510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f9fe709-2441-40cf-9941-fd1a7e13a52f · inbound

From Imitation to Innovation: The Emergence of AI Unique Artistic Styles and the Challenge of Copyright Protection cites this paper.

From Imitation to Innovation: The Emergence of AI Unique Artistic Styles and the Challenge of Copyright Protection Semantic to Structure: Learning Structural Representations for Infringement Detection

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:44:34.520092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.