Paper Citation Record · LEDGER

Improving Progressive Generation with Decomposable Flow Matching

As of 20 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2506.19839.

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

pith.paper-citation-record.v1
2506.19839 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:32:57.210632Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T06:10:14.080177Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T06:11:09.046165Z

Reference resolution

51 of 51 outbound references displayed

verified exact1
verified fuzzy14
unresolved36
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f120f09a-8d60-4864-9e89-53c5f43a8690 · outbound

This paper cites Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models.

Improving Progressive Generation with Decomposable Flow Matching Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:56.991226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f66efc13-13b4-4b55-a45b-d87b382ee1d3 · outbound

This paper cites One transformer fits all distributions in multi-modal diffusion at scale.

Improving Progressive Generation with Decomposable Flow Matching One transformer fits all distributions in multi-modal diffusion at scale

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:56.996426Z

Source-reported events for the cited work

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Observation e22bcbb8-dc7c-406c-baf9-81c42620b970 · outbound

This paper cites A Short Note on the Kinetics-700 Human Action Dataset.

Improving Progressive Generation with Decomposable Flow Matching A Short Note on the Kinetics-700 Human Action Dataset

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.001272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4c6abea-ce66-4ce7-ab37-8c6a9b0e97fc · outbound

This paper cites Generative pretraining from pixels.

Improving Progressive Generation with Decomposable Flow Matching Generative pretraining from pixels

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:58.117550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cd6007da-c62b-4d38-bbfb-a5191ef0fccf · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Improving Progressive Generation with Decomposable Flow Matching Imagenet: A large-scale hierarchical image database

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:58.101622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ae0beb05-6625-4a6d-8c00-0399c7b9544b · outbound

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

Improving Progressive Generation with Decomposable Flow Matching Taming transformers for high-resolution image synthesis

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.015645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab74c359-4d1e-49b9-8bc9-83a0c7c2d403 · outbound

This paper cites Scaling rectified flow transform- ers for high-resolution image synthesis.

Improving Progressive Generation with Decomposable Flow Matching Scaling rectified flow transform- ers for high-resolution image synthesis

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.021914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63422430-e58f-4d79-9455-d0a54e741d41 · outbound

This paper cites Spectral Image Tokenizer.

Improving Progressive Generation with Decomposable Flow Matching Spectral Image Tokenizer

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.026439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c2aa72b-9e84-4c6e-86f7-a871cbac9721 · outbound

This paper cites f-dm: A multi-stage diffusion model via progressive signal transformation.ICLR (ICLR), 2023.

Improving Progressive Generation with Decomposable Flow Matching f-dm: A multi-stage diffusion model via progressive signal transformation.ICLR (ICLR), 2023

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:58.066096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation beb4a8c2-5086-4b20-85eb-32b9e6a48fb9 · outbound

This paper cites Matryoshka diffusion models.

Improving Progressive Generation with Decomposable Flow Matching Matryoshka diffusion models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.035358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 321d7a2d-e585-44a4-bd9f-82502eff3789 · outbound

This paper cites AV-Link: Temporally-Aligned Diffusion Features for Cross-Modal Audio-Video Generation.

Improving Progressive Generation with Decomposable Flow Matching AV-Link: Temporally-Aligned Diffusion Features for Cross-Modal Audio-Video Generation

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:32:57.680180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 827d8c92-cff2-43de-b9c1-7aaf3b68c927 · outbound

This paper cites Classifier-free diffusion guidance.NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications, 2022.

Improving Progressive Generation with Decomposable Flow Matching Classifier-free diffusion guidance.NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications, 2022

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.044260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b8a301d-b8d9-4481-94d9-1b4189f05718 · outbound

This paper cites Cascaded diffusion models for high fidelity image generation.Journal of Machine Learning Research, 23(47):1–33, 2022.

Improving Progressive Generation with Decomposable Flow Matching Cascaded diffusion models for high fidelity image generation.Journal of Machine Learning Research, 23(47):1–33, 2022

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.048404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f01922da-97c3-4330-b200-daefbfce9029 · outbound

This paper cites Video diffusion models.Advances in Neural Information Processing Systems, 35:8633–8646, 2022.

Improving Progressive Generation with Decomposable Flow Matching Video diffusion models.Advances in Neural Information Processing Systems, 35:8633–8646, 2022

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.052675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 324fcbd3-175b-4113-be38-e980f0f0e562 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1 (2):3, 2022.

Improving Progressive Generation with Decomposable Flow Matching Lora: Low-rank adaptation of large language models.ICLR, 1 (2):3, 2022

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.057309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 467ebf16-6166-430b-b999-5711f04ecf75 · outbound

This paper cites Nfig: Autoregressive image generation with next-frequency prediction.arXiv preprint arXiv:2503.07076, 2025.

Improving Progressive Generation with Decomposable Flow Matching Nfig: Autoregressive image generation with next-frequency prediction.arXiv preprint arXiv:2503.07076, 2025

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.061393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03cf70ee-1924-4c73-bafa-2fb07c8a51e1 · outbound

This paper cites Flexvar: Flexible visual autoregressive modeling without residual prediction.arXiv preprint arXiv:2502.20313, 2025.

Improving Progressive Generation with Decomposable Flow Matching Flexvar: Flexible visual autoregressive modeling without residual prediction.arXiv preprint arXiv:2502.20313, 2025

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.065580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4b71623-8da1-4312-a6f5-6e9bdad2a10c · outbound

This paper cites Pyramidal flow matching for efficient video generative modeling.arXiv preprint arXiv:2410.05954, 2024.

Improving Progressive Generation with Decomposable Flow Matching Pyramidal flow matching for efficient video generative modeling.arXiv preprint arXiv:2410.05954, 2024

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.069526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd7622b2-cc74-49ae-891f-14c59d2e4b2d · outbound

This paper cites Elucidating the design space of diffusion-based generative models.Advances in neural information processing systems, 35: 26565–26577, 2022.

Improving Progressive Generation with Decomposable Flow Matching Elucidating the design space of diffusion-based generative models.Advances in neural information processing systems, 35: 26565–26577, 2022

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.073386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3041425-a009-4364-a0b0-e092bcdbeb4e · outbound

This paper cites Analyzing and improving the training dynamics of diffusion models.

Improving Progressive Generation with Decomposable Flow Matching Analyzing and improving the training dynamics of diffusion models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.077420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d0215cf-fa69-4730-8aa9-94e8ad35483a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Improving Progressive Generation with Decomposable Flow Matching Adam: A Method for Stochastic Optimization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.081414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd5e9a2a-7a40-4abb-afe2-c15c61c7db04 · outbound

This paper cites EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling.

Improving Progressive Generation with Decomposable Flow Matching EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.085748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9728076-8894-4d73-b079-c4df2714a276 · outbound

This paper cites Flux, 2024.

Improving Progressive Generation with Decomposable Flow Matching Flux, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.987095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 11a24554-036d-4552-9eed-1bb4f775a401 · outbound

This paper cites Autoregressive image generation using residual quantization.

Improving Progressive Generation with Decomposable Flow Matching Autoregressive image generation using residual quantization

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.971137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 54517409-e266-4d65-b666-f94d14429921 · outbound

This paper cites Hunyuan-dit: A powerful multi-resolution diffusion transformer with fine-grained chinese understanding.arXiv, 2024.

Improving Progressive Generation with Decomposable Flow Matching Hunyuan-dit: A powerful multi-resolution diffusion transformer with fine-grained chinese understanding.arXiv, 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.955318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c889456e-e7bb-4ec3-99ee-9e93c1031988 · outbound

This paper cites Flow Matching for Generative Modeling.

Improving Progressive Generation with Decomposable Flow Matching Flow Matching for Generative Modeling

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.102678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5368331-6b3e-4ecc-82f7-cf7233d811ee · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.

Improving Progressive Generation with Decomposable Flow Matching Flow straight and fast: Learning to generate and transfer data with rectified flow

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.107067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8ffa6ef-3d40-482b-8dff-5e2e8b44bf7a · outbound

This paper cites Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model.

Improving Progressive Generation with Decomposable Flow Matching Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.111395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf53f5aa-b1de-431d-b5db-413e23d6932b · outbound

This paper cites Snap video: Scaled spatiotemporal transformers for text-to-video synthesis.

Improving Progressive Generation with Decomposable Flow Matching Snap video: Scaled spatiotemporal transformers for text-to-video synthesis

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.115872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c00816a-fb28-4768-b2d8-bb3b869ee74c · outbound

This paper cites DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space.

Improving Progressive Generation with Decomposable Flow Matching DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.120265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e180eb4-c101-4b95-8517-630bbd06e670 · outbound

This paper cites Conditional image generation with pixelcnn decoders.

Improving Progressive Generation with Decomposable Flow Matching Conditional image generation with pixelcnn decoders

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.918798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5f79c774-4ede-4aa5-9542-0e9816714683 · outbound

This paper cites an unresolved cited work.

Improving Progressive Generation with Decomposable Flow Matching Unresolved cited work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.129277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b3ad019-2fe4-41f0-923c-ffd65766b6f9 · outbound

This paper cites Scalable diffusion models with transformers.

Improving Progressive Generation with Decomposable Flow Matching Scalable diffusion models with transformers

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.893228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e71df1af-e322-428f-ba18-55b13fafc346 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Improving Progressive Generation with Decomposable Flow Matching Learning transferable visual models from natural language supervision

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.138011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fbf6280-c071-4239-97e4-8b09eb5ad9f9 · outbound

This paper cites Generating diverse high-fidelity images with vq-vae-2.Advances in neural information processing systems, 32, 2019.

Improving Progressive Generation with Decomposable Flow Matching Generating diverse high-fidelity images with vq-vae-2.Advances in neural information processing systems, 32, 2019

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.142159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b6468a0-7689-4ff4-b6bb-66a0dd629e84 · outbound

This paper cites Generative modelling with inverse heat dissipation.

Improving Progressive Generation with Decomposable Flow Matching Generative modelling with inverse heat dissipation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.860523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0cbefecd-e130-4303-9018-5d4f114a8945 · outbound

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

Improving Progressive Generation with Decomposable Flow Matching Photorealistic text-to-image diffusion models with deep language understanding

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.150650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84b78ee1-4999-4275-a8e9-c3428c7320f1 · outbound

This paper cites Improving the diffusability of autoencoders.

Improving Progressive Generation with Decomposable Flow Matching Improving the diffusability of autoencoders

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.836837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5f0a95b2-3499-4807-9883-122f329c1ce1 · outbound

This paper cites Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models.Advances in Neural Information Processing Systems, 36:3732–3784, 2023.

Improving Progressive Generation with Decomposable Flow Matching Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models.Advances in Neural Information Processing Systems, 36:3732–3784, 2023

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.822502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 645223db-63eb-4e96-8b91-fbe655d3e366 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 2024.

Improving Progressive Generation with Decomposable Flow Matching Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 2024

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.163127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08f33979-62bd-47f8-aefd-a8a8f7f51191 · outbound

This paper cites Relay Diffusion: Unifying diffusion process across resolutions for image synthesis.

Improving Progressive Generation with Decomposable Flow Matching Relay Diffusion: Unifying diffusion process across resolutions for image synthesis

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.167306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac1d5e1a-3c16-444a-97fc-377825e65205 · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction.

Improving Progressive Generation with Decomposable Flow Matching Visual autoregressive modeling: Scalable image generation via next-scale prediction

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.796544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 22f6a24b-d1b5-462f-9d98-98c95ef72027 · outbound

This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.

Improving Progressive Generation with Decomposable Flow Matching Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.175906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51f8f1d7-a6ed-4855-8b17-99e24ef13919 · outbound

This paper cites One Rank at a Time: Cascading Error Dynamics in Sequential Learning.

Improving Progressive Generation with Decomposable Flow Matching One Rank at a Time: Cascading Error Dynamics in Sequential Learning

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.180087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c270579-9ed6-438e-b697-9fe6edb955cf · outbound

This paper cites Attention is all you need.

Improving Progressive Generation with Decomposable Flow Matching Attention is all you need

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.184428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b7624fa-d7a9-4234-90c5-949b1f56c403 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Improving Progressive Generation with Decomposable Flow Matching Wan: Open and Advanced Large-Scale Video Generative Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.188671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24b68f93-b10f-4be9-bb74-1ce55cc2f5f0 · outbound

This paper cites TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters.

Improving Progressive Generation with Decomposable Flow Matching TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.193463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9407877-cb03-4eaa-91d7-5ecbf4069d4e · outbound

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

Improving Progressive Generation with Decomposable Flow Matching CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.197756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84afaf40-02eb-4684-bfcc-b1b1535a02fc · outbound

This paper cites Vector-quantized image modeling with improved VQGAN.

Improving Progressive Generation with Decomposable Flow Matching Vector-quantized image modeling with improved VQGAN

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:57.201723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 768d8bb4-36de-4aff-bdb3-09293312488c · outbound

This paper cites Scaling autoregressive models for content-rich text-to-image generation.Transactions on Machine Learning Research, 2022.

Improving Progressive Generation with Decomposable Flow Matching Scaling autoregressive models for content-rich text-to-image generation.Transactions on Machine Learning Research, 2022

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.761731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7d132764-b7ba-4881-a995-b82871488a82 · outbound

This paper cites Please note that since FLUX-DEVis distilled and post-trained on highly aesthetic images, its distribution differs from that of our internal data.

Improving Progressive Generation with Decomposable Flow Matching Please note that since FLUX-DEVis distilled and post-trained on highly aesthetic images, its distribution differs from that of our internal data

Reference 192

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:32:57.744067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation dc160bd3-3077-4dba-b68d-dde99ece675c · inbound

SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers cites this paper.

SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers Improving Progressive Generation with Decomposable Flow Matching

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:11:09.048745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.