Paper Citation Record · LEDGER

Rethinking Layered Graphic Design Generation with a Top-Down Approach

As of 7 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 1 inbound Pith citation observation for arXiv:2507.05601.

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

pith.paper-citation-record.v1
2507.05601 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:26:18.308109Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T11:01:35.324580Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

65 of 65 outbound references displayed

verified exact2
verified fuzzy41
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e08ca519-ed03-4a30-b9c9-822cd9f0f535 · outbound

This paper cites Docsynth: a layout guided approach for controllable docu- ment image synthesis.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Docsynth: a layout guided approach for controllable docu- ment image synthesis

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.735335Z

Source-reported events for the cited work

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Observation c9903631-1085-480d-b8dc-f394e42b647f · outbound

This paper cites DocSynthv2: A Practical Autoregressive Modeling for Document Generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach DocSynthv2: A Practical Autoregressive Modeling for Document Generation

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:26:18.871889Z

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Observation 7af29048-411a-456a-b75e-cfba7fe96c20 · outbound

This paper cites Link: https://www.canva.com/magic-write/, 2024.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Link: https://www.canva.com/magic-write/, 2024

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.713648Z

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Observation 5c62953e-0475-4091-8112-51d18ee71c7d · outbound

This paper cites Two-stage content-aware layout generation for poster designs.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Two-stage content-aware layout generation for poster designs

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.694556Z

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Observation 858f803b-bdb5-4d04-af6d-b6ee629a777a · outbound

This paper cites Posta: A go-to framework for customized artistic poster gen- eration.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Posta: A go-to framework for customized artistic poster gen- eration

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.675998Z

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Observation 864d6850-f1bf-4888-9f71-188ebc80721b · outbound

This paper cites Textdiffuser: Diffusion models as text painters.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Textdiffuser: Diffusion models as text painters

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.656800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2554a2d9-a836-451b-b584-fecc34124a6e · outbound

This paper cites Textdiffuser-2: Unleashing the power of language models for text rendering.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Textdiffuser-2: Unleashing the power of language models for text rendering

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.636198Z

Source-reported events for the cited work

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Observation c6f37ce2-392e-4d7c-b7ef-5a0432866b8c · outbound

This paper cites Pixart-alpha: Fast training of diffusion transformer for photorealistic text-to-image synthesis.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Pixart-alpha: Fast training of diffusion transformer for photorealistic text-to-image synthesis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.612850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 51f9adfe-3130-450e-a8d7-4499886435f3 · outbound

This paper cites PosterCraft: Rethinking High-Quality Aesthetic Poster Generation in a Unified Framework.

Rethinking Layered Graphic Design Generation with a Top-Down Approach PosterCraft: Rethinking High-Quality Aesthetic Poster Generation in a Unified Framework

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:17.967430Z

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Observation 74b53744-9a55-4bc8-8986-ebfd096330f2 · outbound

This paper cites Graphic Design with Large Multimodal Model.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Graphic Design with Large Multimodal Model

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:17.972489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fb828b3-2092-41b2-b8d3-e21edabbbf48 · outbound

This paper cites Icdar2019 robust reading chal- lenge on arbitrary-shaped text-rrc-art.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Icdar2019 robust reading chal- lenge on arbitrary-shaped text-rrc-art

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.589541Z

Source-reported events for the cited work

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Observation d53210b8-6b0b-4e76-9774-8c9c25b95a34 · outbound

This paper cites Discovering the Hidden Vocabulary of DALLE-2.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Discovering the Hidden Vocabulary of DALLE-2

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:17.983554Z

Source-reported events for the cited work

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Observation 0d569ea9-6a80-484c-bc65-8bed87528836 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.561305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 18d9cdda-1067-4f41-9314-2041b93478f9 · outbound

This paper cites Link: https://blackforestlabs.ai/#get-flux, 2024.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Link: https://blackforestlabs.ai/#get-flux, 2024

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.539940Z

Source-reported events for the cited work

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Observation 76523da6-7da8-4e1f-9dd2-66ba70b0411b · outbound

This paper cites Textpainter: Multi- modal text image generation with visual-harmony and text- comprehension for poster design.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Textpainter: Multi- modal text image generation with visual-harmony and text- comprehension for poster design

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.519696Z

Source-reported events for the cited work

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Observation f00ab82b-4270-4e0c-8596-77b6ce582551 · outbound

This paper cites Layout- transformer: Layout generation and completion with self- attention.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Layout- transformer: Layout generation and completion with self- attention

Reference 16

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Observation 9ac7c98b-ab91-4129-ba9d-30a7e8bbde37 · outbound

This paper cites LLMs Meet Multimodal Generation and Editing: A Survey.

Rethinking Layered Graphic Design Generation with a Top-Down Approach LLMs Meet Multimodal Generation and Editing: A Survey

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.014630Z

Source-reported events for the cited work

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Observation 22749525-00e3-4a17-bbde-e7556f4067e1 · outbound

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

Rethinking Layered Graphic Design Generation with a Top-Down Approach Prompt-to-prompt image editing with cross attention control

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.488343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 06791204-0507-419e-b686-25add382fce1 · outbound

This paper cites Retrieval-augmented layout transformer for content-aware layout generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Retrieval-augmented layout transformer for content-aware layout generation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.026973Z

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Observation b954de5d-5b12-4f66-8c37-f397ddd7392a · outbound

This paper cites Posterlayout: A new benchmark and ap- proach for content-aware visual-textual presentation layout.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Posterlayout: A new benchmark and ap- proach for content-aware visual-textual presentation layout

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.456449Z

Source-reported events for the cited work

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Observation ca5bf0dc-65d3-423b-b850-59d84df28d91 · outbound

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

Rethinking Layered Graphic Design Generation with a Top-Down Approach Lora: Low-rank adaptation of large language models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.039112Z

Source-reported events for the cited work

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Observation 85738b43-3fc1-4806-9c2f-319154a0cf24 · outbound

This paper cites Towards flexible multi-modal document models.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Towards flexible multi-modal document models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.045842Z

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Observation bb6c719e-7bf0-40ee-b4b3-c03adf263b35 · outbound

This paper cites OpenCOLE: Towards Reproducible Automatic Graphic Design Generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach OpenCOLE: Towards Reproducible Automatic Graphic Design Generation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.052390Z

Source-reported events for the cited work

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Observation 5adc3b6d-d22d-4593-85bb-67dcbe5f7dac · outbound

This paper cites Improving diffusion models for scene text editing with dual encoders.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Improving diffusion models for scene text editing with dual encoders

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.411061Z

Source-reported events for the cited work

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Observation 984f735c-b728-4e62-b629-bbb04b4682fd · outbound

This paper cites COLE: A Hierarchical Generation Framework for Multi-Layered and Editable Graphic Design.

Rethinking Layered Graphic Design Generation with a Top-Down Approach COLE: A Hierarchical Generation Framework for Multi-Layered and Editable Graphic Design

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.064140Z

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Observation 5147524c-0842-4f42-b7e9-0cd2bc61fd4d · outbound

This paper cites DesignEdit: Multi-Layered Latent Decomposition and Fusion for Unified & Accurate Image Editing.

Rethinking Layered Graphic Design Generation with a Top-Down Approach DesignEdit: Multi-Layered Latent Decomposition and Fusion for Unified & Accurate Image Editing

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.070896Z

Source-reported events for the cited work

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Observation d45b4e8f-419e-42b8-a3bd-f477c0bec3aa · outbound

This paper cites Coarse-to-fine generative modeling for graphic layouts.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Coarse-to-fine generative modeling for graphic layouts

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.390523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation eac122e3-6625-4238-b310-b54d7caa3d8e · outbound

This paper cites Layoutvae: Stochastic scene layout gen- eration from a label set.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Layoutvae: Stochastic scene layout gen- eration from a label set

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.372077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 49358588-58dc-4bd3-97e9-1da9db857760 · outbound

This paper cites Multimodal markup docu- ment models for graphic design completion.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Multimodal markup docu- ment models for graphic design completion

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.086320Z

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Observation eb4dea7b-e227-4c84-8aa3-bf43fd23f045 · outbound

This paper cites Segment any- thing.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Segment any- thing

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.355141Z

Source-reported events for the cited work

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Observation 780405d8-dad2-4fb5-8a72-b363f057455f · outbound

This paper cites Flux-text: A simple and advanced diffusion transformer baseline for scene text editing.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Flux-text: A simple and advanced diffusion transformer baseline for scene text editing

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.096470Z

Source-reported events for the cited work

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Observation ee25fa56-6b9c-44da-a1ed-a1dbb36ba674 · outbound

This paper cites Har- monious textual layout generation over natural images via deep aesthetics learning.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Har- monious textual layout generation over natural images via deep aesthetics learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.336434Z

Source-reported events for the cited work

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Observation 7497e8a6-b007-4a76-a1ee-285bb593e183 · outbound

This paper cites Layoutgan: Generating graphic layouts with wireframe discriminators.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Layoutgan: Generating graphic layouts with wireframe discriminators

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.317448Z

Source-reported events for the cited work

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Observation b5d1179f-08a7-45b5-ae8e-60425f4a7865 · outbound

This paper cites Planning and Rendering: Towards Product Poster Generation with Diffusion Models.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Planning and Rendering: Towards Product Poster Generation with Diffusion Models

Reference 34

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Observation 708933e0-bd10-48dc-9259-523266926138 · outbound

This paper cites TextCenGen: Attention-Guided Text-Centric Background Adaptation for Text-to-Image Generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach TextCenGen: Attention-Guided Text-Centric Background Adaptation for Text-to-Image Generation

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:26:18.533064Z

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Observation b3ea9865-4573-4005-8cd7-1c84fb871843 · outbound

This paper cites Autoposter: A highly automatic and content-aware design system for ad- vertising poster generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Autoposter: A highly automatic and content-aware design system for ad- vertising poster generation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.299866Z

Source-reported events for the cited work

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Observation 5170bb46-eee1-4805-972e-97526e705d59 · outbound

This paper cites Visual instruction tuning.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Visual instruction tuning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.279757Z

Source-reported events for the cited work

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Observation c793a685-a8ac-4c5d-b184-5ca410bb7a60 · outbound

This paper cites Glyph-byt5: A customized text encoder for accurate visual text rendering.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Glyph-byt5: A customized text encoder for accurate visual text rendering

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.259117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 57a1d602-91e1-4cf7-b0c3-ddf6284f40da · outbound

This paper cites Glyph-ByT5-v2: A Strong Aesthetic Baseline for Accurate Multilingual Visual Text Rendering.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Glyph-ByT5-v2: A Strong Aesthetic Baseline for Accurate Multilingual Visual Text Rendering

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.144443Z

Source-reported events for the cited work

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Observation ee4c418e-489c-4017-9467-e902bd9805ec · outbound

This paper cites GlyphDraw: Seamlessly Rendering Text with Intricate Spatial Structures in Text-to-Image Generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach GlyphDraw: Seamlessly Rendering Text with Intricate Spatial Structures in Text-to-Image Generation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.150683Z

Source-reported events for the cited work

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Observation 32125537-7103-4860-8493-d3b7aea04aec · outbound

This paper cites GlyphDraw2: Automatic Generation of Complex Glyph Posters with Diffusion Models and Large Language Models.

Rethinking Layered Graphic Design Generation with a Top-Down Approach GlyphDraw2: Automatic Generation of Complex Glyph Posters with Diffusion Models and Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.157522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae551e35-5ae1-4f0f-a718-af4f832f8bcd · outbound

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

Rethinking Layered Graphic Design Generation with a Top-Down Approach Sdxl: Improving latent diffusion models for high-resolution image synthesis

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.241549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3a643e73-1f08-4899-aeb5-d0934ff7e6df · outbound

This paper cites Art: Anonymous region transformer for variable multi-layer transparent image generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Art: Anonymous region transformer for variable multi-layer transparent image generation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.224215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 72dde413-7fde-4e1c-a842-8fd807d9d012 · outbound

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

Rethinking Layered Graphic Design Generation with a Top-Down Approach High-resolution image syn- thesis with latent diffusion models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.203535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 58829b04-071a-45fb-b88c-fe016a77970a · outbound

This paper cites PosterLlama: Bridging Design Ability of Langauge Model to Contents-Aware Layout Generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach PosterLlama: Bridging Design Ability of Langauge Model to Contents-Aware Layout Generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:18.179610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba942368-5be7-47a9-8038-ec0da6c0e813 · outbound

This paper cites Visual layout composer: Image-vector dual diffusion model for de- sign layout generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Visual layout composer: Image-vector dual diffusion model for de- sign layout generation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.184736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 927aded6-9d85-4187-8e86-772eacf17edb · outbound

This paper cites De-rendering stylized texts.

Rethinking Layered Graphic Design Generation with a Top-Down Approach De-rendering stylized texts

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.165341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 37fc88d1-6f19-40b3-9581-ff113858f5e7 · outbound

This paper cites Mulan: A multi layer annotated dataset for controllable text-to-image generation.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Mulan: A multi layer annotated dataset for controllable text-to-image generation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.146365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1a6df481-c96d-447e-99cf-618bc5c610d3 · outbound

This paper cites Anytext: Multilingual visual text gener- ation and editing.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Anytext: Multilingual visual text gener- ation and editing

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.129154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7639d3f0-d82c-47bf-8100-2a656f07b1c7 · outbound

This paper cites Versatile diffusion: Text, images and variations all in one diffusion model.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Versatile diffusion: Text, images and variations all in one diffusion model

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.111963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8633b885-7151-4ed2-aa2d-9a47434f5483 · outbound

This paper cites Canvasvae: Learning to generate vector graphic documents.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Canvasvae: Learning to generate vector graphic documents

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.092690Z

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Observation 6a055538-7885-42bb-854e-d069f44a3521 · outbound

This paper cites LayoutDETR: Detection Transformer Is a Good Multimodal Layout Designer.

Rethinking Layered Graphic Design Generation with a Top-Down Approach LayoutDETR: Detection Transformer Is a Good Multimodal Layout Designer

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Observation 29de6a4e-b46e-44dd-9e28-092b81e880f4 · outbound

This paper cites Textctrl: Diffusion-based scene text editing with prior guidance control.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Textctrl: Diffusion-based scene text editing with prior guidance control

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Observation 8ea874e3-63c7-4dd3-a2e8-a4f2a6b58835 · outbound

This paper cites Layoutdiffusion: Improving graphic lay- out generation by discrete diffusion probabilistic models.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Layoutdiffusion: Improving graphic lay- out generation by discrete diffusion probabilistic models

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.048103Z

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Observation ed727f9f-d4d2-4c36-b2a3-3c5073764e53 · outbound

This paper cites Transparent image layer diffusion using latent transparency.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Transparent image layer diffusion using latent transparency

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.028253Z

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Observation b0b0f8f4-c264-4405-bfe6-74fa8cfd9554 · outbound

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

Rethinking Layered Graphic Design Generation with a Top-Down Approach Adding conditional control to text-to-image diffusion models

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:19.006361Z

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Observation a55ec0f4-130f-4d59-8ef5-a93c9b012a26 · outbound

This paper cites Brush your text: Synthesize any scene text on im- ages via diffusion model.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Brush your text: Synthesize any scene text on im- ages via diffusion model

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:18.986925Z

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Observation 12ae43e7-6f74-41d0-8bba-f3ce3a6ee443 · outbound

This paper cites Text2Layer: Layered Image Generation using Latent Diffusion Model.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Text2Layer: Layered Image Generation using Latent Diffusion Model

Reference 58

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This paper cites Layout-agnostic scene text image synthesis with diffusion models.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Layout-agnostic scene text image synthesis with diffusion models

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:18.967280Z

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Observation 92d89972-4cb0-4382-963e-06a000e9b4df · outbound

This paper cites Modeling fonts in context: Font prediction on web designs.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Modeling fonts in context: Font prediction on web designs

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:18.947287Z

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Observation 1f8e63c4-a8db-4725-9349-7b79c6beca62 · outbound

This paper cites Udifftext: A unified frame- work for high-quality text synthesis in arbitrary images via character-aware diffusion models.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Udifftext: A unified frame- work for high-quality text synthesis in arbitrary images via character-aware diffusion models

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:18.927669Z

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Observation d0a62b10-3cf3-40ff-9902-e09fd6502f3d · outbound

This paper cites Harmonizing visual text comprehension and gen- eration.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Harmonizing visual text comprehension and gen- eration

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:18.909530Z

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Observation 8ff380ba-65dc-46cf-b46f-c50f663d4a33 · outbound

This paper cites Content-aware generative modeling of graphic design layouts.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Content-aware generative modeling of graphic design layouts

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:26:18.890209Z

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Observation 235dabfe-001e-4476-88c5-421a8bf143d2 · outbound

This paper cites Composition-aware Graphic Layout GAN for Visual-textual Presentation Designs.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Composition-aware Graphic Layout GAN for Visual-textual Presentation Designs

Reference 64

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Observation da21e971-44d7-4db9-9bbc-3ee6079df5b9 · outbound

This paper cites Automatic Layout Planning for Visually-Rich Documents with Instruction-Following Models.

Rethinking Layered Graphic Design Generation with a Top-Down Approach Automatic Layout Planning for Visually-Rich Documents with Instruction-Following Models

Reference 65

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Pith citing papers

Observation c9510cb2-b8d9-4356-84a6-c03e243f689b · inbound

Graphic-Design-Bench: A Comprehensive Benchmark for Evaluating AI on Graphic Design Tasks cites this paper.

Graphic-Design-Bench: A Comprehensive Benchmark for Evaluating AI on Graphic Design Tasks Rethinking Layered Graphic Design Generation with a Top-Down Approach

Reference 5

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