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Paper Citation Record · LEDGER

IGD: Instructional Graphic Design with Multimodal Layer Generation

As of 13 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2507.09910.

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

pith.paper-citation-record.v1
2507.09910 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:47:42.242811Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

55 of 55 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a4e54592-735e-4b61-977b-0fe01082064d · outbound

This paper cites an unresolved cited work.

IGD: Instructional Graphic Design with Multimodal Layer Generation Unresolved cited work

Reference 1

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raw_fallback, observed 2026-08-06T17:47:43.243860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 3c4fa836-310e-400e-ab99-fbd0a875cea8 · outbound

This paper cites an unresolved cited work.

IGD: Instructional Graphic Design with Multimodal Layer Generation Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.870086Z digest=sha256:f4c813a7867b2855030867e358a693979e425045dea481542fc1550e0d0d9845

Observation 6e88a922-1f40-4fe7-8189-52ea1204f035 · outbound

This paper cites GPT-4 Technical Report.

IGD: Instructional Graphic Design with Multimodal Layer Generation GPT-4 Technical Report

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.878400Z digest=sha256:720718009cb1ef8a0c5b1ae7f89cc19d00a6df368cd41b937784519194f005e1

Observation a5086db3-5d58-4a34-a95b-82559296c4ee · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

IGD: Instructional Graphic Design with Multimodal Layer Generation Flamingo: a visual language model for few-shot learning

Reference 4

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no resolver link, observed 2026-08-06T17:47:41.884469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.884469Z digest=sha256:20a03d2d38de3d91742ad9ddfae5b74d21e96878303b2fd14392566a8be6ee07

Observation 919c5d69-ec93-42ef-9cbf-c8e0a860fb12 · outbound

This paper cites Variational transformer networks for layout generation.

IGD: Instructional Graphic Design with Multimodal Layer Generation Variational transformer networks for layout generation

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.198889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.889936Z digest=sha256:56d2cc07dc300d74622f93c1b1564fcb33ef84878d5c21f9ec053d86c9bee17e

Observation 733f5543-a6eb-44d6-847f-688b5b187373 · outbound

This paper cites Qwen Technical Report.

IGD: Instructional Graphic Design with Multimodal Layer Generation Qwen Technical Report

Reference 6

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no resolver link, observed 2026-08-06T17:47:41.894526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.894526Z digest=sha256:eff1fc517dfe176235b5d9e6540e016d1b5f4490dce5ecd3039dc2a075adc0c8

Observation 5b2bc7a1-9ebf-4326-b4b4-f3a163d66eac · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

IGD: Instructional Graphic Design with Multimodal Layer Generation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 7

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no resolver link, observed 2026-08-06T17:47:41.899765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.899765Z digest=sha256:fbf80bdd419f4a6601c186d20e967bba65e813a6b491e80315596f1c74c9d5b1

Observation 445a8dba-1b05-4cba-a628-2d456a35a3c4 · outbound

This paper cites eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers.

IGD: Instructional Graphic Design with Multimodal Layer Generation eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

Reference 8

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no resolver link, observed 2026-08-06T17:47:41.908874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.908874Z digest=sha256:5622c6c0ec7a31ef0269d08102279103389040bea5e763490f6460af1a0461a4

Observation c224a429-d1c4-4f99-aab7-e75314fdc53a · outbound

This paper cites Improving image generation with better captions.

IGD: Instructional Graphic Design with Multimodal Layer Generation Improving image generation with better captions

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.184028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.915784Z digest=sha256:1707bd1aa5a8e34826a87a137a0a32f0d40271d712df7ed6309423f6bac0d480

Observation 74a07166-c16f-402d-b723-a1414da3285e · outbound

This paper cites Textdiffuser: Diffusion models as text painters.

IGD: Instructional Graphic Design with Multimodal Layer Generation Textdiffuser: Diffusion models as text painters

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.168793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.924619Z digest=sha256:39a06b3433c7bec552cfe90bb0be1daac1d6290d3bac3185dced5db85c00abb2

Observation 31929ebe-cb4e-4b4b-a9f3-294e446b3fd9 · outbound

This paper cites Graphic Design with Large Multimodal Model.

IGD: Instructional Graphic Design with Multimodal Layer Generation Graphic Design with Large Multimodal Model

Reference 11

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no resolver link, observed 2026-08-06T17:47:41.931816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.931816Z digest=sha256:9edb67dccea899624eb71a02a6875ad8bce03b6bc2ab31f53d2d46a9c35e8f26

Observation 70155036-c6ca-4475-8b94-2042b36a02b2 · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

IGD: Instructional Graphic Design with Multimodal Layer Generation Gonzalez, Ion Stoica, and Eric P

Reference 12

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no resolver link, observed 2026-08-06T17:47:41.941981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.941981Z digest=sha256:61c09a3ae15f0073cac80c351695dc6b7c8e1968c37128dd46dd807138ed6672

Observation cf6090df-98ed-4ee5-ad71-6b3591a22ea3 · outbound

This paper cites DreamLLM: Synergistic Multimodal Comprehension and Creation.

IGD: Instructional Graphic Design with Multimodal Layer Generation DreamLLM: Synergistic Multimodal Comprehension and Creation

Reference 13

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no resolver link, observed 2026-08-06T17:47:41.947691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.947691Z digest=sha256:e904c7bbb321ff5a28caf0e8f056674e4cadf0672764658bf6941eb5abbf94ac

Observation 3b794eb6-5fad-440b-8743-27aa6c1f2f3e · outbound

This paper cites SVTR: scene text recognition with a single visual model.

IGD: Instructional Graphic Design with Multimodal Layer Generation SVTR: scene text recognition with a single visual model

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.144154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.956111Z digest=sha256:771f3bce3b477d0574c9c976f0cb75a12009ac13adcb85efe2dc9e909d9c0ac6

Observation e1541148-cc24-480e-9540-a48ea2b0d4de · outbound

This paper cites Instruction-guided scene text recognition.

IGD: Instructional Graphic Design with Multimodal Layer Generation Instruction-guided scene text recognition

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.129948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.963491Z digest=sha256:4dc298e8b285a82496bdb7790e7c7ac393529bf79521b4817f0a4c301f40dbfc

Observation 46609264-79a7-4edd-90d7-b7d7ba357821 · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.114389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.968074Z digest=sha256:898ae220ea1aa61e3768843a83b5ee1208c422c829aee90a100b9d7dc29fa6ad

Observation b5e7c1be-e26b-4f77-af65-067c569573de · outbound

This paper cites Layoutgpt: Compositional visual plan- ning and generation with large language models.

IGD: Instructional Graphic Design with Multimodal Layer Generation Layoutgpt: Compositional visual plan- ning and generation with large language models

Reference 17

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.973122Z digest=sha256:295e69d9c14b5e19d087dacf679f12d5669f54a83cc8b65cabcf0f36fb0871d4

Observation 05fce673-ba5d-4366-9c62-e29eeb872097 · outbound

This paper cites Making LLaMA SEE and Draw with SEED Tokenizer.

IGD: Instructional Graphic Design with Multimodal Layer Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T17:47:41.979247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.979247Z digest=sha256:d59f36f48bcf4eb3181c97423393b7abc1a3ad21f3b21df7e7c01a76b1df341e

Observation 88ca3cc1-fbc8-423e-9d9e-217e944030c2 · outbound

This paper cites SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation.

IGD: Instructional Graphic Design with Multimodal Layer Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 19

Resolution
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no resolver link, observed 2026-08-06T17:47:41.985558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:41.985558Z digest=sha256:36f3fdb1ceb4dc974ad315e2aa13885dc9a07d135ef72a3906103823fde6b85c

Observation 18edc930-1f67-4b6d-b9eb-fbcf9bcd0b3f · outbound

This paper cites Denoising dif- fusion probabilistic models.

IGD: Instructional Graphic Design with Multimodal Layer Generation Denoising dif- fusion probabilistic models

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.088348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.993765Z digest=sha256:8b0b3c75ec4cbdd731410f28e4b26391bf4e7f1f5306a75a2d617ff67a719d14

Observation dc38da2c-88b1-4629-8e91-e807231aba34 · outbound

This paper cites Opencole: Towards reproducible automatic graphic design generation.

IGD: Instructional Graphic Design with Multimodal Layer Generation Opencole: Towards reproducible automatic graphic design generation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.073239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:41.999236Z digest=sha256:4fb92db4f2c06bc1bc89244c423853f866b54838ab9e6044a901c45448454d82

Observation babf702b-01fb-4cd0-87d8-e236593b5333 · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation COLE: A Hierarchical Generation Framework for Multi-Layered and Editable Graphic Design

Reference 22

Resolution
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no resolver link, observed 2026-08-06T17:47:42.004083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.004083Z digest=sha256:cf14dce5b50dbf2b088658d65b542e385ce84e1c81fe34a082d3660f7d8e6017

Observation 096a90b3-fda0-4ac3-8022-32059becb0ee · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models, 2023.

IGD: Instructional Graphic Design with Multimodal Layer Generation Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models, 2023

Reference 23

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no resolver link, observed 2026-08-06T17:47:42.013451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.013451Z digest=sha256:9c7437aaaa2eca29cd74b44cf76fb44dfd9d11b4091e28fa1a3132bd095f200a

Observation fd0d7816-3cff-464b-9dfe-d78b4ff9b31e · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation Autoposter: A highly automatic and content-aware design system for ad- vertising poster generation

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.045116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.019100Z digest=sha256:964a9f2838d61fd7b328b1aa4984742481ae71abc0425148971cf5c7e3e7caa3

Observation b2704528-4dfe-49f8-9cd7-40541872ba29 · outbound

This paper cites Character-Aware Models Improve Visual Text Rendering.

IGD: Instructional Graphic Design with Multimodal Layer Generation Character-Aware Models Improve Visual Text Rendering

Reference 25

Resolution
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no resolver link, observed 2026-08-06T17:47:42.024222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.024222Z digest=sha256:33caefc244234c2fba2cdae2df814f742833a2228c361fa4b2fa327ab7179f16

Observation fa96d78e-d396-496c-a62a-441f87825ca6 · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation Glyph-byt5: A customized text encoder for accurate visual text rendering

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.030779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.030050Z digest=sha256:d7ce3df4bebbadbf0b45e25f6152e1011575e41ec2d0579416f06cd4bb662e00

Observation 2ddcc802-8b17-4f34-9de4-ece4572caa94 · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation GlyphDraw: Seamlessly Rendering Text with Intricate Spatial Structures in Text-to-Image Generation

Reference 27

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no resolver link, observed 2026-08-06T17:47:42.036151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.036151Z digest=sha256:0ffadbab9d68c18849f9834d9727a3ba30ffefae72a8a5b7aaef47919b12a033

Observation d788e3b7-32e8-4ea4-87dc-b8b1ee0aff3b · outbound

This paper cites Novelai improvements on stable diffusion, 2023.

IGD: Instructional Graphic Design with Multimodal Layer Generation Novelai improvements on stable diffusion, 2023

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.015767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.043255Z digest=sha256:5ef5db109339c362eb12e1374d55ef8d1bc7de489ae7d3bbfa146cb748e001da

Observation aff5b46b-fcc3-45f6-a307-41ff1fd70512 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

IGD: Instructional Graphic Design with Multimodal Layer Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T17:47:42.051268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.051268Z digest=sha256:433654ef1fc9171ae848314024431dd663245443f27952c3cc2dd2da4b5284b8

Observation e4bded86-80e2-403f-9a71-759394563fce · outbound

This paper cites Boosting semi- supervised scene text recognition via viewing and summariz- ing.

IGD: Instructional Graphic Design with Multimodal Layer Generation Boosting semi- supervised scene text recognition via viewing and summariz- ing

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:43.001415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.058715Z digest=sha256:dc7b2481aefbb8496a5d921598a1a2fee69d4ac358ab946e135a15205dc30546

Observation 91da3966-957b-4d08-b220-6b5504d921de · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation Learning transferable visual models from natural language supervi- sion

Reference 31

Resolution
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no resolver link, observed 2026-08-06T17:47:42.067377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.067377Z digest=sha256:24cf576aeccc46b31676ff797d55802ffb8f03a56a8c12f8d4dcf401466a3e52

Observation 3be1c975-559e-47fa-9d17-8118c74d5379 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

IGD: Instructional Graphic Design with Multimodal Layer Generation Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 32

Resolution
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no resolver link, observed 2026-08-06T17:47:42.074676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.074676Z digest=sha256:f27b78850ecad75e9e9eda55ce59f3f0b69c744e17c3933fa61d9864f980785f

Observation bb8ce54d-b144-4f0d-8dce-04bf941c641e · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation High-resolution image synthesis with latent diffusion models

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:42.966745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.080604Z digest=sha256:a8870e6d958b1e97093cd522a684eb98af9c01ecb8fb1e3be5b9568fddd08ab4

Observation f167a077-312d-4a70-a80e-e7cd79108757 · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation Photorealistic text-to-image diffusion models with deep language understanding

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:42.952023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.086926Z digest=sha256:4a0aa95bb10798ab3b7d28c113d0ec0c9b8b09634804107b65dc4a8c63d0e810

Observation b47c8be5-9084-4c27-a0e5-a4c037ba4327 · outbound

This paper cites Potrace: a polygon-based tracing algorithm,.

IGD: Instructional Graphic Design with Multimodal Layer Generation Potrace: a polygon-based tracing algorithm,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:42.936592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.096229Z digest=sha256:52b0587a223ceb8c18fb1afb4221dcddd6c7e0203b59cce6584fde6b4fdba644

Observation 415d539d-9c43-4796-8eee-dca08f895b24 · outbound

This paper cites Denoising Diffusion Implicit Models.

IGD: Instructional Graphic Design with Multimodal Layer Generation Denoising Diffusion Implicit Models

Reference 36

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.108931Z digest=sha256:b3a300f4b50796cccece0fbe11c545602a264016efe60c493acf01a0c3300ca4

Observation 21956ea7-c28a-42f7-863f-f05cb26a2042 · outbound

This paper cites Emu: Generative pretraining in multimodality.

IGD: Instructional Graphic Design with Multimodal Layer Generation Emu: Generative pretraining in multimodality

Reference 37

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raw_fallback, observed 2026-08-06T17:47:42.922603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.116688Z digest=sha256:c210e7c8d372929103bc61fa692767a37b073a043808802edf655e17dfca7e3c

Observation f82b1e0f-c223-43c8-881a-3f9ee12d6e47 · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

IGD: Instructional Graphic Design with Multimodal Layer Generation Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.124987Z digest=sha256:33f9d67460a32893526fb0db3500e6fee933e7376d879f708a6e68b8f36018aa

Observation 42d2d490-4099-47d5-bd80-5866f4bce8a6 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

IGD: Instructional Graphic Design with Multimodal Layer Generation LLaMA: Open and Efficient Foundation Language Models

Reference 39

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T17:47:42.130015Z digest=sha256:3778cf6f7bb46baf4fc7a38abec4e73e0a53d77d9296a0eb2ec995740d05bf91

Observation 4f180de3-5e9d-43a7-9968-a0d7f54a9c4d · outbound

This paper cites AnyText: Multilingual Visual Text Generation And Editing.

IGD: Instructional Graphic Design with Multimodal Layer Generation AnyText: Multilingual Visual Text Generation And Editing

Reference 40

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no resolver link, observed 2026-08-06T17:47:42.136102Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T17:47:42.136102Z digest=sha256:ca1d808670fc7d8a4f23c70111959dbb3290b8423b117b0974978b5fb4f3b118

Observation 349e10fd-3156-4aee-88bc-9defb7f64707 · outbound

This paper cites Neural discrete representation learning.

IGD: Instructional Graphic Design with Multimodal Layer Generation Neural discrete representation learning

Reference 41

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T17:47:42.141183Z digest=sha256:96c71fe17c933dfc808fd2c98c2528f0b99683d953b432bc66dcb4ab32aa2b61

Observation 835e50c9-c67b-4656-9988-7c2800815202 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

IGD: Instructional Graphic Design with Multimodal Layer Generation Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 42

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T17:47:42.148888Z digest=sha256:995b245f49a5be376657c86ee4d210c02ede0b665eb00208ab47636a5be604ac

Observation 8ca5c10e-e30f-435e-9a27-aadbf8e43556 · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

IGD: Instructional Graphic Design with Multimodal Layer Generation Emu3: Next-Token Prediction is All You Need

Reference 43

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T17:47:42.156308Z digest=sha256:05efaa476aaac896831b3644fcde9a9675d0cca6b839d16c5112950dd7325690

Observation 54ddac35-e20a-46b0-b768-1c0de6e45bf3 · outbound

This paper cites Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation.

IGD: Instructional Graphic Design with Multimodal Layer Generation Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation

Reference 44

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no resolver link, observed 2026-08-06T17:47:42.162445Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T17:47:42.162445Z digest=sha256:69088d389d73aaaab7781b926a21dae4ed2a41a39fbb79a0361871a685e4b9b2

Observation 0d483399-029a-4025-af25-f559a1e4b9e7 · outbound

This paper cites Show-o: One Single Transformer to Unify Multimodal Understanding and Generation.

IGD: Instructional Graphic Design with Multimodal Layer Generation Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 45

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T17:47:42.167491Z digest=sha256:41b5fc0138ada927d1ccef67a2546d857a40e08e09d97f58d7cbe723e417106a

Observation ec8ccf61-5e2a-4ef2-90d2-3f8abc6388b1 · outbound

This paper cites Qwen2.5 Technical Report.

IGD: Instructional Graphic Design with Multimodal Layer Generation Qwen2.5 Technical Report

Reference 46

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no resolver link, observed 2026-08-06T17:47:42.177873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.177873Z digest=sha256:72e9a86847d95ec56f381cb9e5997281f00edf98b51da6832195ec51e29b7b35

Observation 65f3be12-cf3c-416b-8424-352dd227a140 · outbound

This paper cites PosterLLaVa: Constructing a Unified Multi-modal Layout Generator with LLM.

IGD: Instructional Graphic Design with Multimodal Layer Generation PosterLLaVa: Constructing a Unified Multi-modal Layout Generator with LLM

Reference 47

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no resolver link, observed 2026-08-06T17:47:42.183539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.183539Z digest=sha256:0d37880702af973fe5906ac9a1cd09a9f1fbb4d913214bf7c79a6806f84b821a

Observation 6856253a-2d9e-4c4b-937c-68b9fb68e6d7 · outbound

This paper cites Glyphcontrol: Glyph conditional control for visual text generation.

IGD: Instructional Graphic Design with Multimodal Layer Generation Glyphcontrol: Glyph conditional control for visual text generation

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:42.897579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.191543Z digest=sha256:25d9313f7b167bb7a30bf508e54216edead758a4de1078ecc3f69048730a3ecb

Observation 2d5e9827-7b29-4420-b91b-f365fe9ac499 · outbound

This paper cites mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality.

IGD: Instructional Graphic Design with Multimodal Layer Generation mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 49

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.202248Z digest=sha256:f1b45ba79e5d286f9cfaf05bc370a6fb0b351f2125ec7f33520404b45ba55b90

Observation 05cf33f3-0a00-4dbf-a5be-a25db379dd1b · outbound

This paper cites How Control Information Influences Multilingual Text Image Generation and Editing?.

IGD: Instructional Graphic Design with Multimodal Layer Generation How Control Information Influences Multilingual Text Image Generation and Editing?

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:47:42.393461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.207523Z digest=sha256:a96e2109c26b459710932c7faf151319c49930881b2042ac2fab2727c4d6b8c8

Observation 0614e2be-3e94-4567-92b2-7e43003ffb8f · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation Adding conditional control to text-to-image diffusion models

Reference 51

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no resolver link, observed 2026-08-06T17:47:42.213468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.213468Z digest=sha256:fdfd5e39be6436d29fad414d4e7e96d86f9d388c3c6e942df7efd43e4ae0511d

Observation e1c6f685-7263-48b0-81f1-238cb89da82d · outbound

This paper cites CDistNet: Perceiving multi- domain character distance for robust text recognition.

IGD: Instructional Graphic Design with Multimodal Layer Generation CDistNet: Perceiving multi- domain character distance for robust text recognition

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:47:42.866265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.219019Z digest=sha256:71bcb23375a0e32ff9d98aaa64a6b58865dd8627c434a0cec8969d0868de78f7

Observation b6b1bb84-aaa4-4ff0-8c76-80cfd7e16f45 · outbound

This paper cites Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model.

IGD: Instructional Graphic Design with Multimodal Layer Generation Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

Reference 53

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.225102Z digest=sha256:20bfe6ba5f3465455874078591bfb8154ab0b6834ac69d2eadfd7417fbfaf80d

Observation e5371ea6-71c1-47f7-8e12-ec26bd8019f9 · outbound

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

IGD: Instructional Graphic Design with Multimodal Layer Generation Composition-aware Graphic Layout GAN for Visual-textual Presentation Designs

Reference 54

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:47:42.329176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T17:47:42.235544Z digest=sha256:5f8e30de4381bdff7a67471d24bea42640c376621fad90316879971086d064f1

Observation 887eddcf-7498-4b2e-932c-14868959cb8b · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

IGD: Instructional Graphic Design with Multimodal Layer Generation MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 55

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.242811Z digest=sha256:0eac22780faa4b5172abf27b771ddb9f2186a800d9258e5581d8b837a519522e

Pith citing papers

Observation 5298d330-c62b-4909-82ab-65f92a3c9499 · 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 IGD: Instructional Graphic Design with Multimodal Layer Generation

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T11:01:35.324580Z digest=sha256:a41a02b9d10f6edd94ccd4919edb110964a6557ae3e9e5e263770d4fd6694cef