Paper Citation Record · LEDGER

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation

As of 13 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 2 inbound Pith citation observations for arXiv:2511.20635.

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

pith.paper-citation-record.v1
2511.20635 v3

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T06:47:12.160381Z

measured 79 of 79 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:08:49.594504Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:29:31.039583Z

Reference resolution

77 of 77 outbound references displayed

verified exact0
verified fuzzy0
unresolved77
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dbb1bb02-68da-4bb9-bb5b-81dc0779e639 · outbound

This paper cites Qwen2.5-VL Technical Report.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Qwen2.5-VL Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:02.521174Z

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Observation 544374ec-8a64-4add-937d-82fbd5e53e5a · outbound

This paper cites Lumiere: A space-time diffu- sion model for video generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Lumiere: A space-time diffu- sion model for video generation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:02.678126Z

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Observation b7242dd7-d25f-4d0a-b8aa-827df50abd9d · outbound

This paper cites Seedream4.0, 2025.https : / / seed.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Seedream4.0, 2025.https : / / seed

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:02.818809Z

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Observation ea4bcddd-a7e2-4cf2-a067-1ae53cde2aba · outbound

This paper cites HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:02.976356Z

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Observation ae6c611a-2f56-484a-845c-83de3644cc8c · outbound

This paper cites Openpose: Realtime multi-person 2d pose estimation using part affinity fields.IEEE transactions on pattern analysis and machine intelligence, 43(1):172–186,.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Openpose: Realtime multi-person 2d pose estimation using part affinity fields.IEEE transactions on pattern analysis and machine intelligence, 43(1):172–186,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:03.114478Z

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Observation 834da371-fb5d-422e-a978-70b69116f43e · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Emerg- ing properties in self-supervised vision transformers

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:03.233924Z

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Observation c0df67fd-3efc-4aad-b2af-120ea6c208c9 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:03.411590Z

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Observation 233482c9-4fb8-49e6-96f0-7c51ef73cc7e · outbound

This paper cites DeepVerse: 4D Autoregressive Video Generation as a World Model.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation DeepVerse: 4D Autoregressive Video Generation as a World Model

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:03.534918Z

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Observation cfca67ec-e377-438a-b390-a5741ff25a3e · outbound

This paper cites Univid: Unifying vi- sion tasks with pre-trained video generation models.arXiv preprint arXiv:2509.21760, 2025.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Univid: Unifying vi- sion tasks with pre-trained video generation models.arXiv preprint arXiv:2509.21760, 2025

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:03.642270Z

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Observation 5e545dbb-c9a7-4593-90bb-e0a3eb1220c8 · outbound

This paper cites Unireal: Universal image generation and editing via learning real-world dynamics.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Unireal: Universal image generation and editing via learning real-world dynamics

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:03.758730Z

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Observation c491ff43-79cd-40bf-9599-455153a9b709 · outbound

This paper cites UMO: Scaling Multi-Identity Consistency for Image Customization via Matching Reward.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation UMO: Scaling Multi-Identity Consistency for Image Customization via Matching Reward

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:03.874746Z

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Observation 89ebe157-906e-4531-b344-3e903c4f4837 · outbound

This paper cites Gemini2.5, 2025.https : / / deepmind.google/models/gemini/pro/.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Gemini2.5, 2025.https : / / deepmind.google/models/gemini/pro/

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:04.050275Z

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Observation df3f48df-8c46-4420-98f2-1f9dad40af31 · outbound

This paper cites Veo3, 2025.https://deepmind.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Veo3, 2025.https://deepmind

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:04.195649Z

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Observation 7fd60b4b-f7a4-4183-8bde-3ab79de1b739 · outbound

This paper cites Emerging Properties in Unified Multimodal Pretraining.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Emerging Properties in Unified Multimodal Pretraining

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:04.340696Z

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Observation 5634c617-34c3-446f-8757-adcaa3ce3a45 · outbound

This paper cites Yolov8-face-detection, 2024.https : //huggingface.co/arnabdhar/YOLOv8- Face- Detection.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Yolov8-face-detection, 2024.https : //huggingface.co/arnabdhar/YOLOv8- Face- Detection

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:04.500990Z

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Observation 153b526b-2c38-4feb-ae71-57b7ed1e5f13 · outbound

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

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:04.674385Z

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Observation dfb39ff3-0d2e-4d03-bc8a-581c4b679924 · outbound

This paper cites UniVG: A Generalist Diffusion Model for Unified Image Generation and Editing.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation UniVG: A Generalist Diffusion Model for Unified Image Generation and Editing

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:04.847612Z

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Observation e22bf4ad-90c0-485e-9b86-15ba0e62355b · outbound

This paper cites Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:04.960072Z

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Observation db6a5d71-0ece-4bd4-b225-0255de6e02e2 · outbound

This paper cites MVImgNet2.0: A Larger-scale Dataset of Multi-view Images.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation MVImgNet2.0: A Larger-scale Dataset of Multi-view Images

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:05.055172Z

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Observation 6d27e716-eb2b-4890-9a26-5a76ad0398d6 · outbound

This paper cites Hidream-e1-1, 2025.https : / / huggingface.co/HiDream-ai/HiDream-E1-1.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Hidream-e1-1, 2025.https : / / huggingface.co/HiDream-ai/HiDream-E1-1

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:05.221223Z

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Observation ea1c90d0-21d7-435b-a5b1-5b0a465c8a75 · outbound

This paper cites Vbench: Comprehensive bench- mark suite for video generative models.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Vbench: Comprehensive bench- mark suite for video generative models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:05.359216Z

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Observation a3a24969-3acf-4f36-a1bb-19263558f5e7 · outbound

This paper cites Controlnet auxiliary models.https : //github.com/huggingface/controlnet_aux? tab=readme-ov-file, 2023.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Controlnet auxiliary models.https : //github.com/huggingface/controlnet_aux? tab=readme-ov-file, 2023

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:05.516200Z

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Observation 86bf3562-4b8f-4605-a262-6c5acb8e9d04 · outbound

This paper cites InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:05.660498Z

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Observation bef57812-93d2-4e07-a8cf-e4998f49a69b · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:05.784126Z

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Observation 8a4458db-a56d-4c30-b58b-9acbacd29f39 · outbound

This paper cites Let Them Talk: Audio-Driven Multi-Person Conversational Video Generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Let Them Talk: Audio-Driven Multi-Person Conversational Video Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:05.973725Z

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Observation f1a681b0-f1e2-47e3-b7b9-5cbdfc014ca0 · outbound

This paper cites Flux.1 [dev], 2024.https : / / huggingface.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Flux.1 [dev], 2024.https : / / huggingface

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:06.138680Z

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Observation 939b3a07-c8b7-4aae-8688-1cee7bee5837 · outbound

This paper cites Clip-based nsfw detector, 2021.https : //github.com/LAION- AI/CLIP- based- NSFW- Detector.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Clip-based nsfw detector, 2021.https : //github.com/LAION- AI/CLIP- based- NSFW- Detector

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:06.255830Z

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Observation 8f7a22fb-330f-43cb-8124-2416e21e5e00 · outbound

This paper cites UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:06.384931Z

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Observation cdf09944-1623-4c3a-8eec-a6edbe2ab54f · outbound

This paper cites UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:06.552623Z

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Observation f62f80e7-74cf-4f58-b552-a6f1ad172d51 · outbound

This paper cites RealGeneral: Unifying Visual Generation via Temporal In-Context Learning with Video Models.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation RealGeneral: Unifying Visual Generation via Temporal In-Context Learning with Video Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:06.699287Z

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Observation 579d9b89-804f-43d1-9098-27a306c19693 · outbound

This paper cites Flow Matching for Generative Modeling.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Flow Matching for Generative Modeling

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:06.821286Z

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Observation 54d1c0b1-7c25-4dab-bbe8-624cb88cfcf7 · outbound

This paper cites Audioldm 2: Learning holistic audio gen- eration with self-supervised pretraining.IEEE/ACM Trans- actions on Audio, Speech, and Language Processing, 32: 2871–2883, 2024.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Audioldm 2: Learning holistic audio gen- eration with self-supervised pretraining.IEEE/ACM Trans- actions on Audio, Speech, and Language Processing, 32: 2871–2883, 2024

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:06.925885Z

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Observation f5fc3315-0aef-4440-8444-b48a322f6ca7 · outbound

This paper cites Step1X-Edit: A Practical Framework for General Image Editing.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Step1X-Edit: A Practical Framework for General Image Editing

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:07.058673Z

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Observation a3ef9fcc-9480-4d6b-be50-8857081a835a · outbound

This paper cites Univid: The open-source unified video model.arXiv preprint arXiv:2509.24200, 2025.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Univid: The open-source unified video model.arXiv preprint arXiv:2509.24200, 2025

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:07.182018Z

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Observation f1b6c4e2-b526-4fb1-9e77-3f7c237e4e89 · outbound

This paper cites ACE++: Instruction-Based Image Creation and Editing via Context-Aware Content Filling.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation ACE++: Instruction-Based Image Creation and Editing via Context-Aware Content Filling

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:07.337393Z

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Observation 4341b93e-1ebc-4738-a333-ef7647fefc4c · outbound

This paper cites Gpt4o, 2024.https://www.openai.com/.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Gpt4o, 2024.https://www.openai.com/

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:07.445105Z

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Observation b6e49269-494e-484e-bba9-2dae4769ec21 · outbound

This paper cites Sora2, 2025.https://openai.com/index/ sora-2/.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Sora2, 2025.https://openai.com/index/ sora-2/

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:07.542754Z

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Observation 2c0b917d-e397-4cc1-94d9-9a5cfe995558 · outbound

This paper cites Scalable diffusion models with transformers.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Scalable diffusion models with transformers

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:07.647770Z

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Observation b05af249-c56d-429f-816d-d6f449bae16d · outbound

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

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:07.767318Z

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Observation edb03314-eab6-4b4d-bcdb-be41978b3855 · outbound

This paper cites Lumina-Image 2.0: A Unified and Efficient Image Generative Framework.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Lumina-Image 2.0: A Unified and Efficient Image Generative Framework

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:07.873473Z

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Observation 03b10944-c7ca-4d04-8723-9cd6e51ff104 · outbound

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

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Learning transferable visual models from natural language supervi- sion

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.020620Z

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Observation 82d39e5b-8256-4159-9f93-d2df42ef8617 · outbound

This paper cites Make-a-story: Visual memory conditioned consistent story generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Make-a-story: Visual memory conditioned consistent story generation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.151908Z

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Observation 855b24d5-0b9e-4d05-91fe-08f815e53b20 · outbound

This paper cites Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.251845Z

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Observation 9f78cc0b-b93a-4168-b640-1ab405708b96 · outbound

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

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation High-resolution image synthesis with latent diffusion models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.346628Z

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Observation aabc1dd7-94e0-4512-a15f-e3f5e0fb6295 · outbound

This paper cites Pathways on the image manifold: Image editing via video generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Pathways on the image manifold: Image editing via video generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.450256Z

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Observation 11b55f3f-1f22-4257-9fcc-85987052d015 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.559024Z

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Observation 120f5d7d-03a0-429f-8f58-2eeb5103adaf · outbound

This paper cites HunyuanVideo-Foley: Multimodal Diffusion with Representation Alignment for High-Fidelity Foley Audio Generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation HunyuanVideo-Foley: Multimodal Diffusion with Representation Alignment for High-Fidelity Foley Audio Generation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.625247Z

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Observation 27d13411-0f0b-4ff9-ba90-53307b885476 · outbound

This paper cites Aether: Geometric-Aware Unified World Modeling.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Aether: Geometric-Aware Unified World Modeling

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.711461Z

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Observation 620b5149-c115-419a-9a7d-099a1b7c3c37 · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Raft: Recurrent all-pairs field transforms for optical flow

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.797000Z

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Observation abe87faf-64e1-4cfe-9174-d11e04825029 · outbound

This paper cites Audiobox: Unified Audio Generation with Natural Language Prompts.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Audiobox: Unified Audio Generation with Natural Language Prompts

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:08.922024Z

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Observation 98cd8732-bba7-4c19-a051-0aa3d3eae5c3 · outbound

This paper cites InstantID: Zero-shot Identity-Preserving Generation in Seconds.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation InstantID: Zero-shot Identity-Preserving Generation in Seconds

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:09.006094Z

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Observation b22e0ecf-34f4-4222-a246-8505d0bfe88a · outbound

This paper cites Autostory: Generating diverse storytelling images with minimal human efforts.Interna- tional Journal of Computer Vision, pages 1–22, 2024.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Autostory: Generating diverse storytelling images with minimal human efforts.Interna- tional Journal of Computer Vision, pages 1–22, 2024

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Observation 5b95dbdd-b7d7-40cd-8b07-15eb457e9171 · outbound

This paper cites UniVideo: Unified Understanding, Generation, and Editing for Videos.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation UniVideo: Unified Understanding, Generation, and Editing for Videos

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Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:09.213780Z

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Observation fe4599e1-f29a-4df5-9c6c-ec9a0030f03f · outbound

This paper cites OmniGen2: Towards Instruction-Aligned Multimodal Generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation OmniGen2: Towards Instruction-Aligned Multimodal Generation

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Unavailable: canonical work link unavailable.

Observation 090f917d-1ab2-4756-9670-8ceaf496dc68 · outbound

This paper cites Chronoedit: Towards temporal reason- ing for image editing and world simulation.arXiv preprint arXiv:2510.04290, 2025.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Chronoedit: Towards temporal reason- ing for image editing and world simulation.arXiv preprint arXiv:2510.04290, 2025

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Observation b453d790-b836-49af-bfa6-d49d5f7e63d5 · outbound

This paper cites USO: Unified Style and Subject-Driven Generation via Disentangled and Reward Learning.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation USO: Unified Style and Subject-Driven Generation via Disentangled and Reward Learning

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Observation 9ec24dd0-c196-4990-81ed-38cfda623f4c · outbound

This paper cites Less-to-More Generalization: Unlocking More Controllability by In-Context Generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

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Source-reported events for the cited work

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Observation 27c86e6a-e60e-4684-9736-24f0fb670d28 · outbound

This paper cites Dreamomni: Unified image generation and editing.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Dreamomni: Unified image generation and editing

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Unavailable: canonical work link unavailable.

Observation 3b7a6045-e1a2-43d3-9564-57f4e992f09f · outbound

This paper cites Omnigen: Unified image genera- tion.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Omnigen: Unified image genera- tion

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Observation 81d87c44-f2d2-41c6-89e0-4d9a13bd4347 · outbound

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

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

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Source-reported events for the cited work

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Observation 0dfa7745-8b8d-4803-b8f7-4b5edcad2b7c · outbound

This paper cites CSGO: Content-Style Composition in Text-to-Image Generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation CSGO: Content-Style Composition in Text-to-Image Generation

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Observation c16ad3f9-1e63-47d0-a882-c7d3c5f377f3 · outbound

This paper cites Withanyone: Towards control- lable and id consistent image generation.arXiv preprint arXiv:2510.14975, 2025.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Withanyone: Towards control- lable and id consistent image generation.arXiv preprint arXiv:2510.14975, 2025

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Observation 3fb4263e-3399-4e4f-b0ee-b933c3288000 · outbound

This paper cites UniAudio: An Audio Foundation Model Toward Universal Audio Generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation UniAudio: An Audio Foundation Model Toward Universal Audio Generation

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Source-reported events for the cited work

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Observation ed23f208-f311-426c-b74c-e7ebf9059ae4 · outbound

This paper cites Depth any- thing v2.Advances in Neural Information Processing Sys- tems, 37:21875–21911, 2024.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Depth any- thing v2.Advances in Neural Information Processing Sys- tems, 37:21875–21911, 2024

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Source-reported events for the cited work

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Observation 2b5ee6e0-242a-49d6-9209-000c2d6bb892 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34440ad9-f74a-43e0-816f-c8d31e660894 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

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Source-reported events for the cited work

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Observation 930cac71-df1c-4ade-85a8-a73f533250b2 · outbound

This paper cites Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation

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Source-reported events for the cited work

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Observation 7a6b1941-4420-4b9d-b3fa-ea4cc57e6778 · outbound

This paper cites ImgEdit: A Unified Image Editing Dataset and Benchmark.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation ImgEdit: A Unified Image Editing Dataset and Benchmark

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Source-reported events for the cited work

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Observation b1f5b6d1-ed67-41a6-89ee-3564bae7afc7 · outbound

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

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Adding conditional control to text-to-image diffusion models

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Source-reported events for the cited work

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Observation 4e43feea-a87f-439a-9f7a-1c4a7f78eee5 · outbound

This paper cites In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a715269-7317-4d48-bd85-48f9045caa8f · outbound

This paper cites VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

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Observation e17bd8a3-7b86-4592-ab72-e872ba646a3d · outbound

This paper cites Open-Sora: Democratizing Efficient Video Production for All.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Open-Sora: Democratizing Efficient Video Production for All

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07bda8c2-5a14-440b-92ee-f4e36c3c7e56 · outbound

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iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Storydiffusion: Consistent self- attention for long-range image and video generation.Ad- vances in Neural Information Processing Systems, 37: 110315–110340, 2024

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Source-reported events for the cited work

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Observation ca84c11a-e5f1-4be1-b78e-5c0caa3d8f09 · outbound

This paper cites In pre- training stage, we start with more video clip data and less image editing data, then gradually counting more image editing data for better instruction following capability.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation In pre- training stage, we start with more video clip data and less image editing data, then gradually counting more image editing data for better instruction following capability

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Source-reported events for the cited work

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Observation 8b79f121-43a9-444a-84bd-23a83d6a3c5c · outbound

This paper cites Please find our image editing results in Fig.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Please find our image editing results in Fig

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0133ca88-3140-498a-b29e-eade5444e621 · outbound

This paper cites Storyboard Generation Evaluation For a comprehensive evaluation on our many-to-many set- ting, we choose storyboard generation to report numerical metrics.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation Storyboard Generation Evaluation For a comprehensive evaluation on our many-to-many set- ting, we choose storyboard generation to report numerical metrics

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72300f1b-3abf-465a-9cf1-e0b7f802ec3d · outbound

This paper cites vi- sual sentences,.

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation vi- sual sentences,

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Pith citing papers

Observation 4777e389-dbf3-463b-8163-6f5f9b762b5d · inbound

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FreeStyle: Free Control of Style-Content Dual-Reference Generation from Community LoRA Mining iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation

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Source-reported events for the cited work

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Observation ab42dc16-8c92-4fa1-8467-e2109f11d4cf · inbound

ControlRef: Efficient Layout-Guided Multi-Instance Generation via Anchored 4D-RoPE cites this paper.

ControlRef: Efficient Layout-Guided Multi-Instance Generation via Anchored 4D-RoPE iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.