Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing | Paper Citation Record

Observation 7c858f2d-37e2-4576-815b-b8b10a7ed626 · outbound

This paper cites GPT-Image-1.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing GPT-Image-1

Reference 1

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Observation a03491a0-32fc-4918-a1c2-092559d0f3af · outbound

This paper cites Nano banana pro.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Nano banana pro

Reference 2

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Observation 867dec0f-04de-4624-a832-1be74c18561a · outbound

This paper cites Seedream 4.0: Toward Next-generation Multimodal Image Generation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Seedream 4.0: Toward Next-generation Multimodal Image Generation

Reference 3

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Observation 2addad3b-66bf-4a6d-8788-c3773a22c735 · outbound

This paper cites Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.043949Z

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Observation caf5ae4d-3e9f-4c13-83b2-2f199c47bf31 · outbound

This paper cites Qwen-Image Technical Report.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Qwen-Image Technical Report

Reference 5

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Observation 2df78283-b3cb-422b-8a57-f5f8bade2bfe · outbound

This paper cites FLUX.2: Frontier Visual Intelligence.https://bfl.ai/blog/flux-2, 2025.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing FLUX.2: Frontier Visual Intelligence.https://bfl.ai/blog/flux-2, 2025

Reference 6

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Observation 4b0e7b2f-59c6-44a2-8965-c61c93a2fd25 · outbound

This paper cites HunyuanImage 3.0 Technical Report.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing HunyuanImage 3.0 Technical Report

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.205563Z

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Observation fe95fadf-4bd7-42fc-89ec-60dd58f60cbd · outbound

This paper cites FireRed-Image-Edit-1.0 technical report.arXiv preprint arXiv:2602.13344, 2026.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing FireRed-Image-Edit-1.0 technical report.arXiv preprint arXiv:2602.13344, 2026

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.251416Z

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Observation 201da4b4-d1c2-45ae-bfee-27fddabb5969 · outbound

This paper cites CoD-Lite: Real-Time Diffusion-Based Generative Image Compression.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing CoD-Lite: Real-Time Diffusion-Based Generative Image Compression

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.325252Z

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Observation de2cb3be-e99b-4213-9930-2e68296213a9 · outbound

This paper cites Native-Resolution Image Synthesis.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Native-Resolution Image Synthesis

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.401548Z

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Observation 20d1ab30-9d3d-4609-8e09-0118cf962b08 · outbound

This paper cites FlashAttention-2: Faster attention with better parallelism and work partitioning.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing FlashAttention-2: Faster attention with better parallelism and work partitioning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.454918Z

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Observation 09139313-3d93-4527-90ff-8e346da9065d · outbound

This paper cites Flashattention-4: Algorithm and kernel pipelining co-design for asymmetric hardware scaling.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Flashattention-4: Algorithm and kernel pipelining co-design for asymmetric hardware scaling

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.503480Z

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Observation 844ae3fe-4852-4558-80d8-134a32fda096 · outbound

This paper cites Qwen3-VL Technical Report.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Qwen3-VL Technical Report

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.554506Z

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Observation 2480606f-bc55-4b33-9b7b-ecea6f2b8686 · outbound

This paper cites DiffusionNFT: Online Diffusion Reinforcement with Forward Process.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing DiffusionNFT: Online Diffusion Reinforcement with Forward Process

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.629394Z

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Observation a7bb95ba-960a-4f80-b567-b7fd2d27a160 · outbound

This paper cites Decoupled DMD: CFG augmentation as the spear, distribution matching as the shield.arXiv preprint arXiv:2511.22677, 2025.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Decoupled DMD: CFG augmentation as the spear, distribution matching as the shield.arXiv preprint arXiv:2511.22677, 2025

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.679302Z

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Observation 4ad20234-223c-47f7-8ca9-149a0f2737f4 · outbound

This paper cites SenseFlow: Scaling distribution matching for flow-based text-to-image distillation.arXiv preprint arXiv:2506.00523, 2025.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing SenseFlow: Scaling distribution matching for flow-based text-to-image distillation.arXiv preprint arXiv:2506.00523, 2025

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.726959Z

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Observation 0e69ebc9-2c60-45c6-ba70-8a2af00871b6 · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing High-Resolution Image Synthesis with Latent Diffusion Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.803279Z

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Observation 9e06cb87-b24a-4320-8b34-35bcf6cefc1f · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.855740Z

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Observation c9f2b032-6057-4b7e-83de-8ba367a00a76 · outbound

This paper cites Scalable diffusion models with transformers.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Scalable diffusion models with transformers

Reference 19

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Observation 4e49f345-b2ed-4d04-9dd9-e9a07f901e9a · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:57.972786Z

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Observation cf826c32-e353-44c8-a806-33a7b733fc3e · outbound

This paper cites SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.003534Z

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Observation 2f36cf89-305f-4a2a-8bea-5aff780c04d2 · outbound

This paper cites LongCat-Image Technical Report.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing LongCat-Image Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.078447Z

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Observation 5298febc-690e-4bf0-bb70-b7468b877dba · outbound

This paper cites SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.155927Z

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Observation c2dbfc13-eb9a-4914-b814-2d5c8cb04fc8 · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.231018Z

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Observation 8b52b593-fa08-442f-9fb4-74f891b68927 · outbound

This paper cites Null-text Inversion for Editing Real Images using Guided Diffusion Models.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Null-text Inversion for Editing Real Images using Guided Diffusion Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.309489Z

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Observation f6d52b50-0b91-4bad-8c21-63dddc16fca9 · outbound

This paper cites Adding Conditional Control to Text-to-Image Diffusion Models.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Adding Conditional Control to Text-to-Image Diffusion Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.387540Z

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Observation eddd52a5-a990-4f9f-8fab-8d00bfc7410d · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.465961Z

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Observation c1b52947-7354-4cd5-b1bc-5a32b213b692 · outbound

This paper cites InstructPix2Pix: Learning to Follow Image Editing Instructions.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing InstructPix2Pix: Learning to Follow Image Editing Instructions

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.541944Z

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Observation 090f9787-40e8-4df9-8831-c0ee248d3ef9 · outbound

This paper cites MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.619557Z

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Observation 3f0a1cbb-d910-4645-bf05-9289ef78d3d8 · outbound

This paper cites AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.696043Z

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Observation c7e83a77-e2d9-4c4a-91b6-96dd4493fe33 · outbound

This paper cites UltraEdit: Instruction-based Fine-Grained Image Editing at Scale.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing UltraEdit: Instruction-based Fine-Grained Image Editing at Scale

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.775084Z

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Observation ffcbb146-f548-4a9d-bf67-e30f7a882312 · outbound

This paper cites OmniGen: Unified Image Generation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing OmniGen: Unified Image Generation

Reference 32

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Observation 36e25413-9e8c-4741-add3-0a35ae89995d · outbound

This paper cites FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:58.926972Z

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Observation 5f401557-ecb4-4f86-b1f2-03ccb4b38f43 · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Step1X-Edit: A Practical Framework for General Image Editing

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:59.002094Z

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Observation 1a7e7e98-7daa-4008-9502-e5cd10a8fbb4 · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:59.071167Z

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Observation 36ead65f-0f28-4550-80eb-e950efe7ff9c · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing OmniGen2: Towards Instruction-Aligned Multimodal Generation

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:59.153282Z

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Observation 5f7cdefe-80cf-497b-a054-552bee745057 · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation

Reference 37

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Observation edcccec8-7a7a-45d2-b4cb-ba914eeff2bf · outbound

This paper cites DreamOmni2: Multimodal instruction-based editing and generation.arXiv preprint arXiv:2510.06679, 2025.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing DreamOmni2: Multimodal instruction-based editing and generation.arXiv preprint arXiv:2510.06679, 2025

Reference 38

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Observation 8b3ec910-4a54-4bee-ac4c-4d29a3980316 · outbound

This paper cites ChronoEdit: Towards temporal reasoning for image editing and world simulation.arXiv preprint arXiv:2510.04290, 2025.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing ChronoEdit: Towards temporal reasoning for image editing and world simulation.arXiv preprint arXiv:2510.04290, 2025

Reference 39

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Observation c336bbc0-76c2-4e01-aa17-deb069316bb0 · outbound

This paper cites Unified multimodal understanding and generation models: Advances, challenges, and opportunities.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Unified multimodal understanding and generation models: Advances, challenges, and opportunities

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:59.536517Z

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Observation e5c40435-63c8-46d4-bbe6-4fb84ca9c26a · outbound

This paper cites Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:59.596720Z

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Observation 20f4b33d-764a-44e3-af8f-2f703e0e4874 · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:59.683081Z

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Observation 05b9b181-ce16-4210-ac53-c2ab4d676511 · outbound

This paper cites Emerging Properties in Unified Multimodal Pretraining.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Emerging Properties in Unified Multimodal Pretraining

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:59.778271Z

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Observation 42c2eeee-3ea5-4ec5-abb1-324f0b42951a · outbound

This paper cites Emu3.5: Native Multimodal Models are World Learners.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Emu3.5: Native Multimodal Models are World Learners

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-01T13:38:59.844112Z

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Observation f72ccbc2-56f5-4ffa-b4cb-6f596a0c66b4 · outbound

This paper cites Neural Discrete Representation Learning.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Neural Discrete Representation Learning

Reference 46

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Observation d0707cb4-3fa8-4053-8994-3dca0f5a748d · outbound

This paper cites Taming Transformers for High-Resolution Image Synthesis.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Taming Transformers for High-Resolution Image Synthesis

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.040780Z

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Observation c30cf372-f403-47b9-b7c8-a8cae7761fcf · outbound

This paper cites PSC: Posterior sampling-based compression.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing PSC: Posterior sampling-based compression

Reference 48

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Observation 15979df8-17ca-45f6-8cd7-ae92b0936cfc · outbound

This paper cites Idempotence and perceptual image compression.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Idempotence and perceptual image compression

Reference 49

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Observation 2426fc3d-d7fc-4c18-87fe-937d84e01605 · outbound

This paper cites Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.290997Z

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Observation c4b9c307-ced5-4b5c-ba3c-36b57d53c5fe · outbound

This paper cites Oscar: One-step diffusion codec across multiple bit-rates.arXiv preprint arXiv:2505.16091, 2025.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Oscar: One-step diffusion codec across multiple bit-rates.arXiv preprint arXiv:2505.16091, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.387092Z

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Observation c59652cb-0a85-491c-8cb7-75fb88110b5a · outbound

This paper cites One-step diffusion- based image compression with semantic distillation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing One-step diffusion- based image compression with semantic distillation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.454054Z

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Observation 99061f9e-94ed-48a7-8e9c-e894da94eddd · outbound

This paper cites Stablecodec: Taming one-step diffusion for extreme image compression.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Stablecodec: Taming one-step diffusion for extreme image compression

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Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.504066Z

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Observation b9375506-9260-4b10-a3c0-531fc23b75dc · outbound

This paper cites Diffusion Model Alignment Using Direct Preference Optimization.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Diffusion Model Alignment Using Direct Preference Optimization

Reference 54

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Observation 62e00815-c6f2-4b3c-a13b-9a73bf269324 · outbound

This paper cites Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.614946Z

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Observation c0d52c28-1555-44a7-8288-fdbe87edf7df · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Training Diffusion Models with Reinforcement Learning

Reference 56

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Observation 3fc4c5fe-f406-4084-a671-33dbcfab3280 · outbound

This paper cites ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation

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Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.645797Z

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Observation d24b80c5-1f5f-4fdf-ba7d-9c3b74d4c069 · outbound

This paper cites Flow-GRPO: Training Flow Matching Models via Online RL.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Flow-GRPO: Training Flow Matching Models via Online RL

Reference 58

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Observation 48cfba86-f6d4-456c-8a35-f3d9ff4f1694 · outbound

This paper cites Denoising Diffusion Implicit Models.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Denoising Diffusion Implicit Models

Reference 59

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Observation d47167c3-df29-49be-972d-961edb666606 · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Progressive Distillation for Fast Sampling of Diffusion Models

Reference 60

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Observation 0a311b42-3d05-4c4c-87a8-7738d67d31e3 · outbound

This paper cites Consistency Models.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Consistency Models

Reference 61

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Observation cbce2025-82bf-45f5-b34d-7221b4b28df8 · outbound

This paper cites Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.712002Z

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Observation b5dee52d-cb1c-48c3-9eeb-cd4b5da2ce82 · outbound

This paper cites InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.740696Z

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Observation abf273b7-fbfd-4bf3-ac8e-e1061e82f7f3 · outbound

This paper cites One-step Diffusion with Distribution Matching Distillation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing One-step Diffusion with Distribution Matching Distillation

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.769992Z

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Observation 47c7b04b-57df-48ad-8848-a89fb31b278b · outbound

This paper cites Improved Distribution Matching Distillation for Fast Image Synthesis.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Improved Distribution Matching Distillation for Fast Image Synthesis

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.804000Z

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Observation 0890521d-9330-4257-a37e-bb1ec2e819a7 · outbound

This paper cites Adversarial Diffusion Distillation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Adversarial Diffusion Distillation

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.844047Z

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Observation 18df3e63-b085-49dc-b6a2-60b408d9d962 · outbound

This paper cites Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.878827Z

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Observation 02ca7cdd-de6f-40dd-a998-84450ccd57d4 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Learning Transferable Visual Models From Natural Language Supervision

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.914446Z

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Observation df63657b-cab9-42ae-95d2-83d830e131af · outbound

This paper cites DINOv2: Learning robust visual features without supervision.Transactions on Machine Learning Research (TMLR),.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing DINOv2: Learning robust visual features without supervision.Transactions on Machine Learning Research (TMLR),

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.946160Z

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Observation 7f3b2dc1-4220-4de6-a698-f5c499de4024 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Taming transformers for high-resolution image synthesis

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:00.997668Z

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Observation bf2a221a-815e-44b7-a3ad-31e7c4e5665f · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing High-resolution image synthesis with latent diffusion models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.070376Z

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Observation 1fb8bc60-1137-493d-b132-0c4f93888226 · outbound

This paper cites Dico: Revitalizing convnets for scalable and efficient diffusion modeling.Advances in neural information processing systems, 38:123582–123618, 2026.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Dico: Revitalizing convnets for scalable and efficient diffusion modeling.Advances in neural information processing systems, 38:123582–123618, 2026

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.146797Z

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Observation 9ba22d58-4a5d-4d10-9e1f-74e84cfa4bc2 · outbound

This paper cites Deco: Frequency- decoupled pixel diffusion for end-to-end image generation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Deco: Frequency- decoupled pixel diffusion for end-to-end image generation

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.220849Z

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Observation 4e977c98-44d8-49f9-aff4-fc3a73154d75 · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.332817Z

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Observation b4e21bfb-8fb3-4844-8a64-d8adc314aca8 · outbound

This paper cites Cod: A diffusion foundation model for image compression.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Cod: A diffusion foundation model for image compression

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.393850Z

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Observation 16f74ce5-af68-4198-b619-0f30d58f1740 · outbound

This paper cites Projected gans converge faster.Advances in Neural Information Processing Systems, 34:17480–17492, 2021.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Projected gans converge faster.Advances in Neural Information Processing Systems, 34:17480–17492, 2021

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.484545Z

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Observation ee880791-15fe-48bd-b680-11a752b5b8cc · outbound

This paper cites Workshop and challenge on learned image compression(clic2020).

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Workshop and challenge on learned image compression(clic2020)

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.572512Z

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Observation f95c4b44-3529-433a-8e9d-605289a7b612 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing A style-based generator architecture for generative adversarial networks

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.662209Z

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Observation 92973f4a-1131-4b7a-8110-c83a7b20ab40 · outbound

This paper cites A self-supervised descriptor for image copy detection.Proc.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing A self-supervised descriptor for image copy detection.Proc

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.730192Z

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Observation ab548f73-158c-4cd4-9e11-5790eb679201 · outbound

This paper cites The faiss library.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing The faiss library

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.780574Z

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Observation 282dfb98-9c11-4967-9f5c-8fc5b304feea · outbound

This paper cites Qwen3.5: Towards native multimodal agents, February 2026.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Qwen3.5: Towards native multimodal agents, February 2026

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.841799Z

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Observation 7765a8cd-f69c-4363-823e-33e14df585e8 · outbound

This paper cites PaddleOCR-VL-1.5: Towards a Multi-Task 0.9B VLM for Robust In-the-Wild Document Parsing.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing PaddleOCR-VL-1.5: Towards a Multi-Task 0.9B VLM for Robust In-the-Wild Document Parsing

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:01.931696Z

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Observation 85f154f6-6202-42da-9ffd-d37415edcbad · outbound

This paper cites RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.050193Z

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Observation cdfa1da9-0b93-4582-98d5-414bbe3a6f68 · outbound

This paper cites GenEval: An object-focused framework for evaluating text-to-image alignment.Advances in Neural Information Process- ing Systems (NeurIPS), 2023.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing GenEval: An object-focused framework for evaluating text-to-image alignment.Advances in Neural Information Process- ing Systems (NeurIPS), 2023

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.137873Z

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Observation cb372af2-8094-4a66-9d64-ab9b0d0024e9 · outbound

This paper cites ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.199843Z

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Observation 4feca48a-f4ad-44a7-a0c2-3b5d4199eb00 · outbound

This paper cites TIIF-Bench: How Does Your T2I Model Follow Your Instructions?.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing TIIF-Bench: How Does Your T2I Model Follow Your Instructions?

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.289063Z

Source-reported events for the cited work

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Observation 63e413cf-ac4b-4e54-97dc-57392f0ec55e · outbound

This paper cites Oneig-bench: Omni-dimensional nuanced evaluation for image generation.Advances in Neural Information Processing Systems, 38, 2026.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Oneig-bench: Omni-dimensional nuanced evaluation for image generation.Advances in Neural Information Processing Systems, 38, 2026

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.359479Z

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Observation bda2eae2-6e1d-40c8-9e17-cb5a4d868bca · outbound

This paper cites Textcrafter: Accurately rendering multiple texts in complex visual scenes.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Textcrafter: Accurately rendering multiple texts in complex visual scenes

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.440005Z

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Observation a3caf18f-d45e-4e1b-9917-598c31b18316 · outbound

This paper cites X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.492645Z

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Observation a071b6cb-173c-4e00-afb2-4d7d455b6ef0 · outbound

This paper cites Seedream 3.0 Technical Report.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Seedream 3.0 Technical Report

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.571456Z

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Observation ba699391-2add-48ee-9047-d65e73d3d5ae · outbound

This paper cites Kolors: Effective training of diffusion model for photorealistic text-to-image synthesis.arXiv preprint, 2024.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Kolors: Effective training of diffusion model for photorealistic text-to-image synthesis.arXiv preprint, 2024

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.645140Z

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Observation 92c55759-5306-4014-adfe-f5cb6937b001 · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Emu3: Next-Token Prediction is All You Need

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.706687Z

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Observation 58d5f81c-f01a-45ac-988d-52b0e61a3831 · outbound

This paper cites Internvl-u: Democratizing unified multimodal models for understanding, reasoning, generation and editing.arXiv preprint arXiv:2603.09877, 2026.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Internvl-u: Democratizing unified multimodal models for understanding, reasoning, generation and editing.arXiv preprint arXiv:2603.09877, 2026

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Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.789784Z

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Observation 7feddf75-2d9c-4cbd-9b90-0bcd4e1bda71 · outbound

This paper cites Ovis-U1 Technical Report.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Ovis-U1 Technical Report

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.846343Z

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Observation 59717f9d-397a-446a-a8dc-acc4ccb2d39c · outbound

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

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:02.912248Z

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Observation ff561262-9e70-49ef-becb-90f991b00039 · outbound

This paper cites Flux.https://github.com/black-forest-labs/flux, 2024.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Flux.https://github.com/black-forest-labs/flux, 2024

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Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:03.024435Z

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Observation e04c6d32-64c6-4081-9d71-0e542dd3cc7e · outbound

This paper cites FLUX.1 Krea [dev].

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing FLUX.1 Krea [dev]

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:03.142773Z

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Observation d96657bd-7282-46d6-9cc4-98e0a09575bc · outbound

This paper cites JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:03.262803Z

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Observation e9b9bfc8-ac8e-4706-ad99-30b05681b41c · outbound

This paper cites Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:03.440104Z

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Observation c105e6e8-ceae-4a54-94f5-7dbf7ab7e9b3 · outbound

This paper cites Show-o2: Improved Native Unified Multimodal Models.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Show-o2: Improved Native Unified Multimodal Models

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:03.551669Z

Source-reported events for the cited work

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Observation f7ecdc18-6770-4109-bd69-2cd8c894a18d · outbound

This paper cites Improving image generation with better captions.Computer Science,https: // cdn.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Improving image generation with better captions.Computer Science,https: // cdn

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Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:03.631499Z

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