Paper Citation Record · LEDGER

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps

As of 15 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2501.14046.

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

pith.paper-citation-record.v1
2501.14046 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:28:56.209954Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation c6167753-5f32-4bdb-9b97-dece69809d71 · outbound

This paper cites Blended diffusion for text-driven editing of natural images.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Blended diffusion for text-driven editing of natural images

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.748611Z

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Observation 77067a6d-39aa-4e86-b442-a160c7d6ab37 · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Break-a-scene: Extracting multiple concepts from a single image

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.734847Z

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Observation be8f0e30-fece-4698-bcdb-3937ce529e8a · outbound

This paper cites Blended latent diffusion.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Blended latent diffusion

Reference 3

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Observation 728c1fff-a6f1-4764-9035-40f8d3e28bb7 · outbound

This paper cites Universal guidance for diffusion models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Universal guidance for diffusion models

Reference 4

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Observation 3cfb0b04-3d65-4569-a84d-5aa0f7cf9c14 · outbound

This paper cites Improving image generation with better captions, 2023.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Improving image generation with better captions, 2023

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.694474Z

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Observation b0a9e1b1-23cd-4663-aa66-663c290a1583 · outbound

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LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Unresolved cited work

Reference 6

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Observation 2574eac1-a817-405e-851f-b46c423e705b · outbound

This paper cites Language models are few-shot learners.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Language models are few-shot learners

Reference 7

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Observation 1b26c6b8-dc92-493e-a2ab-213c6b82eddd · outbound

This paper cites DiffEdit: Diffusion-based semantic image editing with mask guidance.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps DiffEdit: Diffusion-based semantic image editing with mask guidance

Reference 8

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Observation fefe8c52-f2a5-4e08-93f9-250a8882c3f5 · outbound

This paper cites Diffusion models beat GANs on image syn- thesis.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Diffusion models beat GANs on image syn- thesis

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.639725Z

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Observation f7a5825d-9a3b-4877-a7dd-c447e3178876 · outbound

This paper cites Diffu- sion Self-Guidance for controllable image generation.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Diffu- sion Self-Guidance for controllable image generation

Reference 10

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Observation d8827997-e7d0-45d6-8238-7a97cae0c884 · outbound

This paper cites Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Reference 11

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Observation 780e8d1a-449f-48d8-92ff-6f32a01adc9a · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps An image is worth one word: Personalizing text-to-image genera- tion using textual inversion

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.612301Z

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Observation cbea1d66-5243-49e8-8855-017be9d9d569 · outbound

This paper cites Diffusion models as plug-and-play priors.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Diffusion models as plug-and-play priors

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.598469Z

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Observation 15a42542-c963-4cc9-b32d-756ee4eb125c · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Prompt-to-prompt image editing with cross-attention control

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.585383Z

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Observation ef35354b-de24-40af-9a0a-1b2134293da7 · outbound

This paper cites Classifier-free diffusion guidance.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Classifier-free diffusion guidance

Reference 15

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Observation 914b68cc-25f8-48b9-83d5-ce8129a356fc · outbound

This paper cites Denoising diffusion probabilistic models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Denoising diffusion probabilistic models

Reference 16

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Observation 11de8e1a-e3a6-404a-98fb-b0d200e71379 · outbound

This paper cites Mistral 7B.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Mistral 7B

Reference 17

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Observation 888dfb6d-b480-41b3-94cc-e76376368e73 · outbound

This paper cites Imagic: Text-based real image editing with diffusion models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Imagic: Text-based real image editing with diffusion models

Reference 18

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Observation 61a8b553-bcb5-4023-99f1-eecbef662f6f · outbound

This paper cites Variational diffusion models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Variational diffusion models

Reference 19

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Observation 6c3b6794-85c5-4013-a5d0-4a24e36c4564 · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Multi-concept customization of text-to-image diffusion

Reference 20

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Observation 3d237b25-88e6-47e2-ae72-8f8ceeee0e56 · outbound

This paper cites LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models

Reference 21

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Observation ab75c67c-b9a5-4f83-a478-f3a9aaf09f37 · outbound

This paper cites Compo- sitional visual generation with composable diffusion models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Compo- sitional visual generation with composable diffusion models

Reference 22

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Observation 33576f37-d36a-450c-bd66-883292bba580 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Gemma: Open Models Based on Gemini Research and Technology

Reference 23

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Observation 0c4e6579-f3e0-43b1-ae5f-af391c46a444 · outbound

This paper cites Scaling open-vocabulary object detection.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Scaling open-vocabulary object detection

Reference 24

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Observation 596db516-6881-480b-9b51-7194dfb41a36 · outbound

This paper cites DragonDiffu- sion: Enabling drag-style manipulation on diffusion models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps DragonDiffu- sion: Enabling drag-style manipulation on diffusion models

Reference 25

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Observation 77caa4de-f3b4-4a37-ab3b-cd691590c931 · outbound

This paper cites SDXL: Improving latent diffusion models for high-resolution image synthesis.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps SDXL: Improving latent diffusion models for high-resolution image synthesis

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.473292Z

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Observation ab422940-b4c1-44f7-9aa4-4240efdd7c19 · outbound

This paper cites Learning transferable visual models from natural language super- vision.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Learning transferable visual models from natural language super- vision

Reference 27

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Observation bdc06ff8-cf0e-4e95-baaf-c000b90a9e6b · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Zero-shot text-to-image generation

Reference 28

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Observation 94ecbbad-4356-458d-a05a-01280c522a47 · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps High-resolution image synthesis with latent diffusion models

Reference 29

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Observation 22e2dc97-2617-45ff-806a-3ad8d1e82cb6 · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 30

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Photorealistic text-to-image diffusion models with deep lan- guage understanding

Reference 31

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Observation 13ce9922-8653-4a78-b5e6-c0d3cda17966 · outbound

This paper cites Denoising diffusion implicit mod- els.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Denoising diffusion implicit mod- els

Reference 32

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This paper cites Score-based generative modeling through stochastic differential equations.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Score-based generative modeling through stochastic differential equations

Reference 33

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Observation e61b4fd5-6962-46b9-a686-2ea88c2c5d62 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 34

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Observation 39a5271a-a6dd-4b1d-8d46-e6f79eb07550 · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Plug-and-play diffusion features for text-driven image-to-image translation

Reference 35

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Observation 52aad501-4818-4260-9355-0b57c81a164a · outbound

This paper cites Dy- namic prompt learning: Addressing cross-attention leakage for text-based image edit- ing.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Dy- namic prompt learning: Addressing cross-attention leakage for text-based image edit- ing

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.360036Z

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Observation fd16baf5-8fc1-430c-a23e-4259795f900f · outbound

This paper cites Self-correcting LLM-controlled Diffusion Models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Self-correcting LLM-controlled Diffusion Models

Reference 37

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Observation 018fbb71-7047-4334-90a9-c711368fbe90 · outbound

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

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Adding conditional control to text- to-image diffusion models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.345042Z

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Observation 24088f72-890c-414a-815a-facae9994ccc · outbound

This paper cites Sur- adapter: Enhancing text-to-image pre-trained diffusion models with large language models.

LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps Sur- adapter: Enhancing text-to-image pre-trained diffusion models with large language models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:28:56.331088Z

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Pith citing papers

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