Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 43 inbound Pith citation observations for arXiv:2401.08740.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:16:55.622484Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
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- unresolved0
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- malformed identifier0
- metadata mismatch0
External citation measurements
3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
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 2026-08-06T06:34:29.942622+00:00.
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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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
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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 2026-08-06T06:34:29.942622+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
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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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
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.