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Paper Citation Record · LEDGER

APT: Adaptive Personalized Training for Diffusion Models with Limited Data

As of 11 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2507.02687.

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

pith.paper-citation-record.v1
2507.02687 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

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measured 41 of 41 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

41 of 41 outbound references displayed

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Outbound references

Observation a5452d41-1f2e-466a-bf6b-18fd617aef5b · outbound

This paper cites GPT-4 Technical Report.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data GPT-4 Technical Report

Reference 1

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Observation ad9f1c27-5d33-44c1-b3a7-853145a537fa · outbound

This paper cites A neural space-time representation for text- to-image personalization.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data A neural space-time representation for text- to-image personalization

Reference 2

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Observation 4c45a8c5-acca-4e2c-a3fa-68b46f10adc0 · outbound

This paper cites Break-a-scene: Extracting multi- ple concepts from a single image.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Break-a-scene: Extracting multi- ple concepts from a single image

Reference 3

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Observation e322e6a7-e79f-4ea3-91b6-2ef58cf69d12 · outbound

This paper cites Improving image generation with better captions.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Improving image generation with better captions

Reference 4

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Observation bedbfb31-2195-478f-9b3b-56ec1ce6d539 · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 5

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Observation 02ac7850-b16f-4c1d-b1a2-b3a53bda2b37 · outbound

This paper cites CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models

Reference 7

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Observation 66344aa5-da1c-4d65-aa5a-a4bc82c68f53 · outbound

This paper cites An image is worth one word: Personalizing text-to-image generation using textual inversion.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data An image is worth one word: Personalizing text-to-image generation using textual inversion

Reference 8

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Source-reported events for the cited work

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Observation 4af69ecb-fd77-4836-8a82-21320fb58078 · outbound

This paper cites Svdiff: Compact param- eter space for diffusion fine-tuning.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Svdiff: Compact param- eter space for diffusion fine-tuning

Reference 9

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b008af09-b610-4bfd-b472-e5a8c28fd21a · outbound

This paper cites Efficient diffu- sion training via min-snr weighting strategy.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Efficient diffu- sion training via min-snr weighting strategy

Reference 10

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Observation ba3635c0-bf25-4248-baac-878445e7fe3e · outbound

This paper cites ViCo: Plug-and-play Visual Condition for Personalized Text-to-image Generation.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data ViCo: Plug-and-play Visual Condition for Personalized Text-to-image Generation

Reference 11

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Observation 0e75709a-f4c3-4d8f-a703-b97950c33a81 · outbound

This paper cites Classifier-free diffusion guidance.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Classifier-free diffusion guidance

Reference 12

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Observation 0d3991d6-da75-481e-b25a-b763730b8526 · outbound

This paper cites Denoising diffu- sion probabilistic models.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Denoising diffu- sion probabilistic models

Reference 13

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Observation c3075787-1ee7-4e1b-a434-42c14e0abe5e · outbound

This paper cites Lora: Low- rank adaptation of large language models.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Lora: Low- rank adaptation of large language models

Reference 14

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Observation db62c716-0d31-406b-b742-dc39fe5b7ac8 · outbound

This paper cites Training generative adver- sarial networks with limited data.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Training generative adver- sarial networks with limited data

Reference 15

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Observation 7d266d92-bb49-43ca-9650-7998de943af1 · outbound

This paper cites Multi-concept customization of text-to-image diffusion.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Multi-concept customization of text-to-image diffusion

Reference 16

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Observation 75e2dc93-a5cb-41f9-b927-5986ea2344d6 · outbound

This paper cites Direct consistency optimization for compositional text- to-image personalization.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Direct consistency optimization for compositional text- to-image personalization

Reference 17

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 807af853-2722-42cb-b061-131795fbba84 · outbound

This paper cites Decoupled weight de- cay regularization.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Decoupled weight de- cay regularization

Reference 18

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Observation c664629c-f974-4532-9df8-bfde4ccd6dba · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 19

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Observation 7313ec10-14e9-4324-b754-7be4b200dabd · outbound

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

APT: Adaptive Personalized Training for Diffusion Models with Limited Data DINOv2: Learning Robust Visual Features without Supervision

Reference 20

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Observation ca740a5f-048a-4584-803b-543e492a6d52 · outbound

This paper cites Attndream- booth: Towards text-aligned personalized text-to-image gen- eration.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Attndream- booth: Towards text-aligned personalized text-to-image gen- eration

Reference 21

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Source-reported events for the cited work

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Observation e44fae50-f9a4-4b3b-97bc-adab7f7b3f0b · outbound

This paper cites Sdxl: Im- proving latent diffusion models for high-resolution image synthesis.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Sdxl: Im- proving latent diffusion models for high-resolution image synthesis

Reference 22

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Observation d1a6061b-a3b6-4d93-b7ad-860d15554902 · outbound

This paper cites Controlling text-to-image diffusion by orthogo- nal finetuning.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Controlling text-to-image diffusion by orthogo- nal finetuning

Reference 23

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Observation 87a7197c-a653-4385-9556-3922ecf4ff33 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Learning transferable visual models from natural language supervi- sion

Reference 24

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Observation df8df168-a25e-4781-bd53-f188efab8634 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 25

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Observation 9299dac5-ffd6-44d6-9933-02351dda8911 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data High-resolution image syn- thesis with latent diffusion models

Reference 26

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Observation 8a9ae740-2661-4822-a737-bf90f7eac82c · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 27

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Observation 1cb4068f-b0e4-4812-b4fa-4cfd2bcdf7c8 · outbound

This paper cites Palette: Image-to-image diffusion models.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Palette: Image-to-image diffusion models

Reference 28

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Observation 1c198e0c-1929-4be1-b0b9-44e4e8fb92df · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Photorealistic text-to-image diffusion models with deep language understanding

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 7539d9ff-b28a-40b6-84ae-cd3a3d389e4f · outbound

This paper cites Assessing generative models via precision and recall.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Assessing generative models via precision and recall

Reference 30

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 230e34e6-4762-4f0f-9bdd-fc6682728185 · outbound

This paper cites Rethinking the spatial inconsistency in classifier- free diffusion guidance.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Rethinking the spatial inconsistency in classifier- free diffusion guidance

Reference 31

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation a4435bc2-da4c-4fcf-ae45-65969a97c426 · outbound

This paper cites Face2diffusion for fast and editable face personalization.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Face2diffusion for fast and editable face personalization

Reference 32

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 8aad4c30-6e30-4f88-aa41-ff3fa462067e · outbound

This paper cites Denois- ing diffusion implicit models.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Denois- ing diffusion implicit models

Reference 33

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fbddec4c-a082-4ead-a494-e87151fedb0c · outbound

This paper cites P+: Extended Textual Conditioning in Text-to-Image Generation.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data P+: Extended Textual Conditioning in Text-to-Image Generation

Reference 34

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Observation cc1ca4b7-000c-4976-965d-965d9b456737 · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 35

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Observation 64a470f1-3ccf-455e-8aaa-69b0484e7651 · outbound

This paper cites Scaling Autoregressive Models for Content-Rich Text-to-Image Generation.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 36

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Unavailable: canonical work link unavailable.

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Observation 90a7d339-986a-46e7-8020-5ae3573772e3 · outbound

This paper cites Jedi: Joint- image diffusion models for finetuning-free personalized text- to-image generation.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Jedi: Joint- image diffusion models for finetuning-free personalized text- to-image generation

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:30:26.749366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 68dbf57f-eb8a-4f34-9cfb-8741132ba30c · outbound

This paper cites Attention calibration for disentangled text-to-image person- alization.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Attention calibration for disentangled text-to-image person- alization

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T20:30:26.559521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:30:26.559521Z digest=sha256:3eebf1c6264d5b3ef0e0506740cae29fdc8a11a2ad3db72251c7ca829b7a13b8

Observation 9149c6a5-d8fa-4c08-a12d-b1ffc48bbc39 · outbound

This paper cites zoomed-in.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data zoomed-in

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:30:26.732944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d8d16e36-5463-4242-80b2-4b8c5877feed · outbound

This paper cites an unresolved cited work.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:30:26.722003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T20:30:26.567288Z digest=sha256:5b0a73053a91dd78aa6da536cd3b7d2c1d168970de223e88b843cace9ee1c17f

Observation 13df2444-c646-42d4-9108-163c368c80e1 · outbound

This paper cites an unresolved cited work.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:30:26.712286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T20:30:26.571123Z digest=sha256:0eb06b107a2d4811d97b3642fb2864de68082e3884f21fb40ef4a6e69941bb44

Observation aa0968b0-f209-49d1-88ad-3c0d70bc6ad8 · outbound

This paper cites Figure 12 shows the interface presented to users during the study.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data Figure 12 shows the interface presented to users during the study

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:30:26.701834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Pith citing papers

No inbound Pith citation observations are available.