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Paper Citation Record · LEDGER

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding

As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2606.10892.

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

pith.paper-citation-record.v1
2606.10892 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T13:38:44.707837Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T13:38:44.707837Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T04:47:38.315879Z

Reference resolution

32 of 32 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved30
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0185a2ac-0c67-4453-8a44-ab2efd08ef6c · outbound

This paper cites Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding

Reference 1

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verified exact
local_arxiv, observed 2026-07-03T04:47:38.317169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 60758d02-373b-4755-9b75-11b1d77be557 · outbound

This paper cites x should be artifact-free and conform to y.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding x should be artifact-free and conform to y

Reference 2

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Unavailable: canonical work link unavailable.

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Observation 7cf32bea-f358-4322-9f01-57ec39495e53 · outbound

This paper cites an unresolved cited work.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Unresolved cited work

Reference 3

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Observation 345aae86-c0a6-4ff6-8556-80125a2aa2ed · outbound

This paper cites an unresolved cited work.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Unresolved cited work

Reference 4

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:2478420588805373358c07da38bb1c45789b50d1392c7eea02e134269249ca33

Observation 18faf429-43b2-4410-a886-5a8073271cbf · outbound

This paper cites Blended latent diffusion,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Blended latent diffusion,

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:035e6c5030a91e3fc1418a4b4ff938ef1d98a9b630880ae02cb5e43a5e89106b

Observation a72479b5-8986-4552-bf69-ead4ce9ce181 · outbound

This paper cites Blended diffusion for text-driven editing of natural im- ages,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Blended diffusion for text-driven editing of natural im- ages,

Reference 6

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:b4f80c08b30d0bf9f1568b6e9b581e904ff99debd2f021b5c87be3b0d526fb3e

Observation 92a56736-21de-4ad4-b15e-66eb983df8b1 · outbound

This paper cites High-resolution image synthesis with latent dif- fusion models,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding High-resolution image synthesis with latent dif- fusion models,

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation cd1da71a-b9b4-4f04-9bcd-60708f49d0ec · outbound

This paper cites A task is worth one word: Learning with task prompts for high-quality versatile image inpainting,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding A task is worth one word: Learning with task prompts for high-quality versatile image inpainting,

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:9941ce61171ad97bbee0dfb6da015539b08e0917e5ac7903fa8bf6ff7a133ac9

Observation 872aedf7-eec2-44b8-a5dc-4b39139ef3a4 · outbound

This paper cites Transparent im- age layer diffusion using latent transparency,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Transparent im- age layer diffusion using latent transparency,

Reference 9

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no resolver link, observed 2026-06-27T13:38:44.707837Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:02260faed6725db9ea195124b9bc4ee52250ae362512bcd852187f8ea5c38b7f

Observation c862692a-64ab-4513-b9c3-12195d3be57e · outbound

This paper cites BrushNet: A plug-and-play image inpainting model with decom- posed dual-branch diffusion,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding BrushNet: A plug-and-play image inpainting model with decom- posed dual-branch diffusion,

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:74dc5aab707807a2e1df0be1e2ca401f5f9bb844a49465258fa2227edfcd27db

Observation 57397949-0712-43b6-b3d9-2f465ffa3ff7 · outbound

This paper cites an unresolved cited work.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Unresolved cited work

Reference 11

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no resolver link, observed 2026-06-27T13:38:44.707837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:4cd7cd5e779a1c60a9efb3031cf0a0510fe3bb9dac33bc1552eeb1caa5760543

Observation 0a3b2135-f773-497d-ba19-6b210fa621b4 · outbound

This paper cites GLIDE: towards photorealistic image generation and editing with text-guided diffusion mod- els,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding GLIDE: towards photorealistic image generation and editing with text-guided diffusion mod- els,

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6bc7b700-8e0e-442a-b6d3-cb1565edc40e · outbound

This paper cites Zero-shot text-to-image generation,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Zero-shot text-to-image generation,

Reference 13

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unresolved
no resolver link, observed 2026-06-27T13:38:44.707837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 44739a5d-8375-42da-85ba-99319d418008 · outbound

This paper cites PixArt-α: Fast training of diffusion transformer for photorealistic text-to-image synthesis,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding PixArt-α: Fast training of diffusion transformer for photorealistic text-to-image synthesis,

Reference 14

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1f60000f-47cc-4599-acb4-4afb50287e28 · outbound

This paper cites Null- text inversion for editing real images using guided dif- fusion models,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Null- text inversion for editing real images using guided dif- fusion models,

Reference 15

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unresolved
no resolver link, observed 2026-06-27T13:38:44.707837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 744edf53-072f-4fc0-8929-8f010efad6cf · outbound

This paper cites ProxEdit: improving tuning-free real image editing with proximal guidance,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding ProxEdit: improving tuning-free real image editing with proximal guidance,

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5c04a25e-0acc-4dde-b45f-07158e9abdd1 · outbound

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

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Adding conditional control to text-to-image diffusion models,

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1216dc7a-d6e9-4e03-9004-7633c13da358 · outbound

This paper cites Imagen Editor and EditBench: advancing and evaluat- ing text-guided image inpainting,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Imagen Editor and EditBench: advancing and evaluat- ing text-guided image inpainting,

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2339ff2d-07ca-4854-ae21-1b97426f4a6e · outbound

This paper cites Attend- and-excite: Attention-based semantic guidance for text- to-image diffusion models,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Attend- and-excite: Attention-based semantic guidance for text- to-image diffusion models,

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:4412bfbc6badd951286095d89e3fb0119a89749fbac5bf65856767bf12082350

Observation 78df26b9-158f-4b4f-bb1e-217a216c5473 · outbound

This paper cites Prompt-to-prompt image editing with cross-attention control,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Prompt-to-prompt image editing with cross-attention control,

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e5f9352d-6359-4728-8ac1-031312e4c97e · outbound

This paper cites Learning transferable visual models from natural lan- guage supervision,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Learning transferable visual models from natural lan- guage supervision,

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 26750e58-3284-4e81-aa9c-b28168771bf9 · outbound

This paper cites Plug-and-play diffusion features for text-driven image- to-image translation,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Plug-and-play diffusion features for text-driven image- to-image translation,

Reference 22

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2bce5a5e-492c-44bb-abe0-57c5d9ecc702 · outbound

This paper cites An im- age is worth one word: Personalizing text-to-image gen- eration using textual inversion,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding An im- age is worth one word: Personalizing text-to-image gen- eration using textual inversion,

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 92c4a788-dc97-439b-9754-68097784814f · outbound

This paper cites Subject- Diffusion: open domain personalized text-to-image gen- eration without test-time fine-tuning,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Subject- Diffusion: open domain personalized text-to-image gen- eration without test-time fine-tuning,

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 496547ed-c058-448e-a816-755e68ff575f · outbound

This paper cites BLIP- Diffusion: pre-trained subject representation for control- lable text-to-image generation and editing,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding BLIP- Diffusion: pre-trained subject representation for control- lable text-to-image generation and editing,

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:516eb50f80e88bd07a35e965fc7251f104ccc680c51b020842f737f0e1baa01a

Observation bcafd246-db44-4bfb-9bf9-e48066e6dd36 · outbound

This paper cites From colouring-in to pointillism: revisiting semantic segmentation supervision.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding From colouring-in to pointillism: revisiting semantic segmentation supervision

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-03T04:47:38.319934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:72424bc39ce231701362b2427d51bea2521294c8c4fe08498f2040286858fba8

Observation d30c39b7-5bf5-479a-8328-947fede000c7 · outbound

This paper cites Decoupled weight decay regularization,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Decoupled weight decay regularization,

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:8c21d291785c658e5256c3785a3859f0ddeb899a2c5159fdb9ea4441e6383701

Observation ffb59a2e-5fab-43e6-93b5-310059f27eaf · outbound

This paper cites De- noising diffusion implicit models,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding De- noising diffusion implicit models,

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:fd12e4c578ac5c41080bccc1562f8e8816a32269cb089ffcafa35287526d494b

Observation 7a342623-166d-493e-8dfe-fe1623f960bc · outbound

This paper cites Segment anything,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Segment anything,

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:785eefde3dc05ebbc385c2027c3a0923a9087732795af1ec66f13de166ce1d37

Observation b5504037-e7b5-4780-86bb-1ed8aabb6e2c · outbound

This paper cites Grounding DINO: marrying DINO with grounded pre- training for open-set object detection,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Grounding DINO: marrying DINO with grounded pre- training for open-set object detection,

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:1759fe1bf26ec19aa7c92d9aaecdc85568aed7aec8903ed8122f5a7d88e6beee

Observation d5e645bc-6bb3-462e-8d56-0670641d1bf8 · outbound

This paper cites ImageRe- ward: learning and evaluating human preferences for text-to-image generation,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding ImageRe- ward: learning and evaluating human preferences for text-to-image generation,

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T13:38:44.707837Z digest=sha256:96f24cc7a444f5f208f6c6f2eef6069ea9585bfae0d3a8b5c518579bb81ff7f8

Observation d914fec5-f3a7-42e4-a37e-17a47acb3fed · outbound

This paper cites LAION-5B: an open large-scale dataset for training next generation image-text models,.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding LAION-5B: an open large-scale dataset for training next generation image-text models,

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

Observation 0185a2ac-0c67-4453-8a44-ab2efd08ef6c · inbound

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding cites this paper.

Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding Improving Text-Instance Alignment Of Foreground Conditioned Out-Painting Via Customized Concept Embedding

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-07-03T04:47:38.317169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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