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Paper Citation Record · LEDGER

IGD: Instructional Graphic Design with Multimodal Layer Generation

As of 8 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.870086Z digest=sha256:35549f792750e6758b5440d0a3861b0082ed05a1f732190bac6af0178a4b28fb

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=sha256:20b357fbd563f1093529428146dff7444bdf5e16d53eb8adc71c7cbd9e02c449

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:cb32c27cf93acca3fc57bc418060b87448740773d394f2de9fc2b675b321b731

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.889936Z digest=sha256:de9319ef689e1d4c35d72728fde21578ce0bf39d2b5998e950c751c202d0b6b3

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=sha256:47b9a189feee60690eb46d47f88b0100da29824b13f31634fff7cd904f73d002

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=sha256:827a881bb69945be586a1889a1aafe85398c4947e0638a170d6a916ffc2e0c48

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:d66e301478abd929fe6b78c68e432be2f6224652f96f4c30e69893b1026f6713

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.915784Z digest=sha256:5ec1a3968f09c9ec65955307280b56aabc9373a5899ad5acf9cf4f7b3f98974e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.924619Z digest=sha256:95901b2938fbd051090ebc8311247f0679756a354957c02674c48671b9d726c6

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:bbfc134f0beaddbbb670053e1d898327542c28519c42d0f9b3db6676db3c689d

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:c6ecb9a6b4164659a4908d50ac38cede1b3fceb0b952ab2bc2ff52ad1fa5ec52

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

Resolution
unresolved
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=sha256:159a252357739da0c735eb49b31ea7652f34a1bd188b0b7fadc99a764c37a87e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.956111Z digest=sha256:93bda554b737a0f0f097580555e1b75ca5c61d54d0dff7468516ab0896077d5e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.963491Z digest=sha256:910c31c5f7181f074488aeb1579fa4dc58e3ad6e898b60694e5123a93ac5b938

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.968074Z digest=sha256:e7a78bc048fe86b95731473c45f8e7cac45f94d57f8ad225cda9ab734498d6e0

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=sha256:69f521ac900f88ad2ea37dea1cc74339b49130995f7dfaabbb1753d0d0effa4d

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:b372903c836416cb1ba8a176a4f755dc2a0662aae4665e816cce20ead3842ce0

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

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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:dcf2e4e770f8a79e0fa80d952cea0a0c1e2776e9cab7cb61dae09eb8bcd4a553

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.993765Z digest=sha256:cb48b2a7151a44a11a035622b401cb66e22af25a1b74143fa6da74ea09d82603

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:41.999236Z digest=sha256:d581df1cf17dce550c72fad4261f975992ece3562dd195d0de4826cb32c58429

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
unresolved
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:ab1d5d57f6497cb75371a84cf19852b61546392cc7ed596c91577cffe637ef99

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=sha256:498c7469dd7f2f2cd7b5263aa130cfa9f9a0407d61cf676ad2fbe2f63d28fba7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.019100Z digest=sha256:8f73db5f108cdb2408ce0cf0068ec4a785d3713f9eaaf569366a93c178764746

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
unresolved
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=sha256:7f06fb3489d6dddffddfa3aef84bd65a4efb3551e1e525eb4ceb80dc08e52d95

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.030050Z digest=sha256:1193c1dd5ec7607f06b634e5b83f3449ca78daa5c4dbd2a8f1c90e148c0cf5d0

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

Resolution
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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=sha256:927695b33b24476dbd1b31746a110b0222cb14a248a73eec1c25737b80da7c83

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.043255Z digest=sha256:ec04c5f411a6c24c28a78d0a6373e4f7dc1c965d7ab438583410d78771fec60d

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:c43a67a56218cabbe07552e669e43114ff22803b20460a10d6574b4af111e5cb

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.058715Z digest=sha256:d93f4e909bfcdc0c3634d779257cbed7e024e9cce872e120b744c1f9a1e03f2f

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:c232845eb2054d853a957356d1d12817bb84c6e1bdc7c2e8599711e4a89f4aa3

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:c73338e3ce2308cd99db4321958d4cd13e9b4d051519a564c84bb07ec2d8dadd

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.080604Z digest=sha256:7d3275ea7b99730d28a85ab7f6a2f006e4a31770822e91b1c675c51050456d30

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.086926Z digest=sha256:7811f8c08fb7ea3e4efdc1f670776d87ab8dcc73aced6f50e887960bb093d422

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.096229Z digest=sha256:32bc10682f3bad109427bfde69cec055c4f4fb39c990ea020db9ab52d7689d6c

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

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unresolved
no resolver link, observed 2026-08-06T17:47:42.108931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.108931Z digest=sha256:9e559a0e64d5b12506ae7133c261e0a528ef56c5dcdeea4fe5af63cd8c21e163

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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verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.116688Z digest=sha256:aa41b26d7be4c2da0beb0b2b2796318cc5a258764c8116741a89a7d2391d0b3e

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=sha256:65666f3185c0d13716983f1e2d08b2b255dd95b99d63a088d56b4c2138ccf711

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.130015Z digest=sha256:bd4064d5ecc0f606e4347c3b6707a039e669354e07f20e8ebce312329fba59fe

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.136102Z digest=sha256:e446badb6c3c86341927762e80822d054d2b973c934b6de06913d8863c495cdf

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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no resolver link, observed 2026-08-06T17:47:42.141183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.141183Z digest=sha256:fa6752338cc2d6ac425d9b0187ef07a624c4201300afd33a5c82dcf02aa7208d

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:dc9770b30500e822ddd13d977afb82b891f2d28f3ff32ad8f0c32a23020e9f3c

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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no resolver link, observed 2026-08-06T17:47:42.156308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.156308Z digest=sha256:51a61c7578c1833496f2596b07f818c7c3ee5aafc12203f6c91bb519a82fe1bb

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.162445Z digest=sha256:0fe9213fb2b984c254deff522d3b2a8a45da709e836d1e1eff34ba0be4333415

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.167491Z digest=sha256:60d6e8109693a2bb093516de7059466299e29bcd37c37a70a8f0e29db12fef9b

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=sha256:3fd0fa5ae714b4ce109cb1515f98b9c6f2a13560f2a7881f5fda73d2538aee80

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:c10133d8d4428b2f6c68fc1fa453ce22d0befc13c5dce94927c0c2ca86b909cb

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.191543Z digest=sha256:90858d40f4ecb0d7f98563c8c527619a7f4cc0d8dbff3cea1f774c5c4a91fb69

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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no resolver link, observed 2026-08-06T17:47:42.202248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.202248Z digest=sha256:6249d67dd9bb295846e1e2cf6ef8cbe0cbfec7c06d3f56e4b4ec850fb7cafef7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.207523Z digest=sha256:d55fb513f360c99efefc748ccac03cc3a64a0d0ab73c2f951cc1007629a6eaa5

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.213468Z digest=sha256:a5848181f336a6a30e423746e2ee846e51f3891ce32c1060382454509abf1d36

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.219019Z digest=sha256:925b611c17793cfb1aeb899e407395be5ed9b139ac528f93ccf09b9a205906e1

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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no resolver link, observed 2026-08-06T17:47:42.225102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:47:42.225102Z digest=sha256:e0578331aa4915c2ed4d0e0554b772c44a8d93461b4659f740117ad2cf023d3b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T17:47:42.235544Z digest=sha256:38a493a6b69fa96e12fbc5aaf6ebfea1167c0702722e97953510ab4641103154

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:d1befb8b2e93f49ef2ff114b7b5732773b9d8de330360f9b3775cbd1255422d9

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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no resolver link, observed 2026-07-13T11:01:35.324580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T11:01:35.324580Z digest=sha256:489c60893540c5b5479f5e95c57df5d7ef6c9ed00ab2c1cf89f37f0bb824e9aa