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Paper Citation Record · LEDGER

OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.10983.

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

pith.paper-citation-record.v1
2403.10983 v2

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 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:33:36.573699Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T14:20:30.577207Z

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 a597bea9-c146-43fd-87a0-f4092d822ce9 · inbound

DIVE: Taming DINO for Subject-Driven Video Editing cites this paper.

DIVE: Taming DINO for Subject-Driven Video Editing OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T22:33:36.573699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:33:36.573699Z digest=sha256:b168e20fb884f1b2a512e02fdb5ad4dcec9c0483ed637a2412416d44e04b70a9

Observation 31f4a26c-dc8d-4c6c-b79e-4a5e4082dccd · inbound

AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation cites this paper.

AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-10T20:01:21.456248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:01:21.456248Z digest=sha256:bb450db7a71c53fe03d1422673d67253b75b0ebcac4c0f27524496c7b6d35bfd

Observation f349e60d-a187-4b86-b72f-a1daa042e634 · inbound

Movie Weaver: Tuning-Free Multi-Concept Video Personalization with Anchored Prompts cites this paper.

Movie Weaver: Tuning-Free Multi-Concept Video Personalization with Anchored Prompts OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-09T11:21:20.501433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:21:20.501433Z digest=sha256:e63f9d0be6f9b0251fcb94535541468b8df3e0edd333b094d339dade6bd00263

Observation 605f47db-ab50-486d-8943-098706447e41 · inbound

LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers cites this paper.

LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T12:41:21.944497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:21.944497Z digest=sha256:b778c6d1e1eab460a4550282acc74213fb92f66d6ba5c2754be0814e9bc8165d

Observation 43e58457-0c96-4898-b289-be2fac7ee5de · inbound

PostureObjectstitch: Anomaly Image Generation Considering Assembly Relationships in Industrial Scenarios cites this paper.

PostureObjectstitch: Anomaly Image Generation Considering Assembly Relationships in Industrial Scenarios OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:20:30.580137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T14:16:40.509571Z digest=sha256:370acbf300a8a34d9e78e5a3d03325bf5f50687cb7f0708ac2786655bbdaa6f7