SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers | Paper Citation Record

Observation 3e9b1c09-c96d-42e8-98f6-df087a3955de · inbound

EventFlow: Forecasting Temporal Point Processes with Flow Matching cites this paper.

EventFlow: Forecasting Temporal Point Processes with Flow Matching SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:05:46.729873Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89eefafc-08b0-4b2e-8262-315ed8ac284a · inbound

Flow Matching Guide and Code cites this paper.

Flow Matching Guide and Code SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:28:14.058157Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9a20d62d-9009-4557-aff3-c80dee8b1c87 · inbound

Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps cites this paper.

Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:45:17.633903Z

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Observation a0957f55-e720-4c4d-8c9e-0928a8d7310c · inbound

Exploring Representation-Aligned Latent Space for Better Generation cites this paper.

Exploring Representation-Aligned Latent Space for Better Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T19:22:41.690401Z

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Observation 179c48d2-9fd3-4fcb-a9ab-d0ea682be35b · inbound

MotionLab: Unified Human Motion Generation and Editing via the Motion-Condition-Motion Paradigm cites this paper.

MotionLab: Unified Human Motion Generation and Editing via the Motion-Condition-Motion Paradigm SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-09T12:31:22.654723Z

Source-reported events for the cited work

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Observation 7a95c3cd-3a25-4e98-a7a1-e6a11eefd6d4 · inbound

Masked Autoencoders Are Effective Tokenizers for Diffusion Models cites this paper.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.381159Z

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Observation 9630ec21-3b95-42cb-b24f-e3c0d9cb9ee5 · inbound

Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images? cites this paper.

Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images? SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T21:50:24.536245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a4e9cf1-df24-48f6-82cd-72e82ad71836 · inbound

Variational Rectified Flow Matching cites this paper.

Variational Rectified Flow Matching SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T20:54:49.818051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54812bf1-195d-4fae-a86f-16e537ac48b0 · inbound

Seedream 3.0 Technical Report cites this paper.

Seedream 3.0 Technical Report SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:55:38.782457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6916ee39-6ee4-4587-9ac3-2b40d4af4381 · inbound

REPA Works Until It Doesn't: Early-Stopped, Holistic Alignment Supercharges Diffusion Training cites this paper.

REPA Works Until It Doesn't: Early-Stopped, Holistic Alignment Supercharges Diffusion Training SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T15:00:38.912442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bd4b991-25a1-4dde-b530-37e98a6c2a04 · inbound

Applications of Modular Co-Design for De Novo 3D Molecule Generation cites this paper.

Applications of Modular Co-Design for De Novo 3D Molecule Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:01.058699Z

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Unavailable: canonical work link unavailable.

Observation 1ae142b6-0adf-407d-9f4a-fb8be86f9d50 · inbound

Differentiable Solver Search for Fast Diffusion Sampling cites this paper.

Differentiable Solver Search for Fast Diffusion Sampling SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:46:45.076890Z

Source-reported events for the cited work

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Observation fd4c6d52-7a06-46d3-a29b-333bc1ac5793 · inbound

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment cites this paper.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T11:34:02.216529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c7ee035-06ae-454e-b0ec-dc99ee5045b9 · inbound

Native-Resolution Image Synthesis cites this paper.

Native-Resolution Image Synthesis SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:25.626014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a24c084-5581-42df-b4c4-88c3679f0997 · inbound

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis cites this paper.

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T06:02:59.653070Z

Source-reported events for the cited work

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Observation 8b242ca2-ef67-4c57-a9a8-d9dda2a33e65 · inbound

UniMC: Taming Diffusion Transformer for Unified Keypoint-Guided Multi-Class Image Generation cites this paper.

UniMC: Taming Diffusion Transformer for Unified Keypoint-Guided Multi-Class Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T20:26:37.885766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 504b9f5b-010f-495c-bb85-89dc6a8fe572 · inbound

La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching cites this paper.

La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T18:00:53.132231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78920582-22b7-4b4f-b488-e3cb1af4ce87 · inbound

PixNerd: Pixel Neural Field Diffusion cites this paper.

PixNerd: Pixel Neural Field Diffusion SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T10:59:53.556391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 842c7831-ed8c-4c9e-a6f8-455a40a3507f · inbound

FlowBack-Adjoint: Physics-Aware and Energy-Guided Conditional Flow-Matching for All-Atom Protein Backmapping cites this paper.

FlowBack-Adjoint: Physics-Aware and Energy-Guided Conditional Flow-Matching for All-Atom Protein Backmapping SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T04:25:45.514699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a71851bf-e54f-47f8-b1b3-bee9b0b9ca7e · inbound

Transition Models: Rethinking the Generative Learning Objective cites this paper.

Transition Models: Rethinking the Generative Learning Objective SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T10:19:54.415886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d80c86a-da79-4959-84e7-75b3fbeef456 · inbound

Missing Fine Details in Images: Last Seen in High Frequencies cites this paper.

Missing Fine Details in Images: Last Seen in High Frequencies SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:34.270506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e76ca54a-100b-43b2-ad76-195846a3b043 · inbound

Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CT cites this paper.

Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CT SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-18T16:31:37.309739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d8cc6f4e-e343-4de9-8dbb-618ed047e943 · inbound

Flow marching for a generative PDE foundation model cites this paper.

Flow marching for a generative PDE foundation model SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:51:25.634942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8cbfd164-1aaf-459e-8ecd-6fdb366bd89c · inbound

DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation cites this paper.

DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:49:08.304126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 775d61ef-fa8c-40ee-8185-c4fffa423b47 · inbound

Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers cites this paper.

Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T15:35:15.656310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26443260-9a7e-468a-b8c5-2868fd8a3965 · inbound

Self-transcendence: Is External Feature Guidance Indispensable for Accelerating Diffusion Transformer Training? cites this paper.

Self-transcendence: Is External Feature Guidance Indispensable for Accelerating Diffusion Transformer Training? SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T11:04:32.319958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41cd81f8-34b6-4e08-be3f-f63e5f5484da · inbound

PixelGen: Improving Pixel Diffusion with Perceptual Supervision cites this paper.

PixelGen: Improving Pixel Diffusion with Perceptual Supervision SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:57:33.188969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0b5951ea-e949-44ab-ace6-c1a0022aea16 · inbound

Optimizing Few-Step Generation with Adaptive Matching Distillation cites this paper.

Optimizing Few-Step Generation with Adaptive Matching Distillation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T03:42:45.300743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 398437ea-3233-4fa9-aa93-bab49c0a1f1f · inbound

Generative Modeling via Kernelized Stochastic Interpolants cites this paper.

Generative Modeling via Kernelized Stochastic Interpolants SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T21:32:19.617512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d46eeabf-11b0-46c5-8af6-8e35b6f939ba · inbound

Setting-Matched and Semantics-Scaled Benchmarking of One-Step Generative Models Against Multistep Diffusion and Flow Models cites this paper.

Setting-Matched and Semantics-Scaled Benchmarking of One-Step Generative Models Against Multistep Diffusion and Flow Models SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T12:20:00.819268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 33e5d802-3d2a-4651-b151-09629de6629c · inbound

GVCC: Zero-Shot Video Compression via Codebook-Driven Stochastic Rectified Flow cites this paper.

GVCC: Zero-Shot Video Compression via Codebook-Driven Stochastic Rectified Flow SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T23:33:16.253198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b7afc9d8-6de0-4291-a0a7-e00ec0b2aff4 · inbound

Discrete Meanflow Training Curriculum cites this paper.

Discrete Meanflow Training Curriculum SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T05:10:55.570947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1fc9ff28-0fcf-4856-8cd0-b2152ba0335b · inbound

Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation cites this paper.

Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-10T03:08:59.190290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f2607530-f1ff-4258-8e21-ba5f7bd97434 · inbound

Posterior Augmented Flow Matching cites this paper.

Posterior Augmented Flow Matching SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:36:07.414161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bdaccb71-9422-49c6-8e5a-9f0ad8dd9300 · inbound

What Time Is It? How Data Geometry Makes Time Conditioning Optional for Flow Matching cites this paper.

What Time Is It? How Data Geometry Makes Time Conditioning Optional for Flow Matching SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:36:24.812415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f897c324-07b3-4bdc-9c55-35ffd910e7a6 · inbound

The two clocks and the innovation window: When and how generative models learn rules cites this paper.

The two clocks and the innovation window: When and how generative models learn rules SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 55

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:16:18.047678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 76188e4d-3b26-48ae-a29d-7e21ba5d75f5 · inbound

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion cites this paper.

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:48:17.670588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5ba13344-c8b5-4227-bb73-ab17a96bad6e · inbound

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation cites this paper.

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:03:15.281509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b83df877-b91c-4ffe-97eb-43e75d7e0363 · inbound

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation cites this paper.

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:45:00.706079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 01842dd2-230b-4768-8e71-0e08e07b1108 · inbound

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation cites this paper.

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T13:49:19.939916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25f0f05d-4073-4b49-b8fa-facd3c2bdfa6 · inbound

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters cites this paper.

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 91

Resolution: verified exact; arxiv_id, observed 2026-07-02T06:06:41.246709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d6a09457-3d7d-4417-85ac-fd034b97fb3c · inbound

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters cites this paper.

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-02T12:30:44.601602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 812658fe-1966-4e2d-8a31-4ad3bacc63b2 · inbound

DSA: Dynamic Step Allocation for Fast Autoregressive Video Generation cites this paper.

DSA: Dynamic Step Allocation for Fast Autoregressive Video Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-02T06:16:43.694176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 387772a3-27e8-491b-a847-d27b6ea02328 · inbound

Balancing Image Compression and Generation with Bootstrapped Tokenization cites this paper.

Balancing Image Compression and Generation with Bootstrapped Tokenization SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:46:55.392724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 80798ca6-a46a-486a-895f-f7cd2c7c48be · inbound

IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder cites this paper.

IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-03T05:37:40.229595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cbf21d47-0c06-449f-aa2a-2023dbd965e1 · inbound

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation cites this paper.

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T20:50:11.391641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ba148561-f9e7-4894-9d16-79badf62f30f · inbound

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation cites this paper.

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T09:35:40.184655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 76c39b9f-c1e0-4ae6-999c-306b27e47838 · inbound

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation cites this paper.

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-12T12:07:02.175855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84fff43a-18a0-479c-b380-66f530f52449 · inbound

PixelU: A U-Shaped Transformer for Efficient End-to-End Pixel Diffusion cites this paper.

PixelU: A U-Shaped Transformer for Efficient End-to-End Pixel Diffusion SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T20:03:57.190864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c095b750-6d29-4e92-9af0-4fce50520ab6 · inbound

Spatial Transport of Integration Error in Generative ODEs cites this paper.

Spatial Transport of Integration Error in Generative ODEs SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-01T22:04:48.902642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66cdf29a-1ba9-4865-828f-2cdd887890bf · inbound

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models cites this paper.

HistoFID- Calibrating Frechet-distance evaluation across pathology foundation models SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T10:56:35.830674Z

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Observation e1c920c2-64bc-4dcc-86f4-7451d29b31b4 · inbound

WaiT for the Signal: Simple Frequency-Aware Flow-Matching cites this paper.

WaiT for the Signal: Simple Frequency-Aware Flow-Matching SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T00:34:35.484981Z

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Observation 3b7fc349-f4bc-4e61-94bc-6bdff6404539 · inbound

MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation cites this paper.

MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T12:14:41.609978Z

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Unavailable: canonical work link unavailable.

Observation 9a9afcdd-7c6f-4ffe-900f-e70d2b221952 · inbound

Beckmann Transport Models: From Autonomous Flows to One-Step Maps cites this paper.

Beckmann Transport Models: From Autonomous Flows to One-Step Maps SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T00:16:55.622484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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