Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 44 inbound Pith citation observations for arXiv:2401.08740.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T06:02:59.653070Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation 3e9b1c09-c96d-42e8-98f6-df087a3955de · inbound
EventFlow: Forecasting Temporal Point Processes with Flow Matching SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 89eefafc-08b0-4b2e-8262-315ed8ac284a · inbound
Flow Matching Guide and Code SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 52
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9a20d62d-9009-4557-aff3-c80dee8b1c87 · inbound
Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 50
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 54812bf1-195d-4fae-a86f-16e537ac48b0 · inbound
Seedream 3.0 Technical Report SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3a24c084-5581-42df-b4c4-88c3679f0997 · inbound
STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 46
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b242ca2-ef67-4c57-a9a8-d9dda2a33e65 · inbound
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
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 45
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 78920582-22b7-4b4f-b488-e3cb1af4ce87 · inbound
PixNerd: Pixel Neural Field Diffusion SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 14
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 17
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 49
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 32
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d8cc6f4e-e343-4de9-8dbb-618ed047e943 · inbound
Flow marching for a generative PDE foundation model SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8cbfd164-1aaf-459e-8ecd-6fdb366bd89c · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 775d61ef-fa8c-40ee-8185-c4fffa423b47 · inbound
Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 23
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? SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 26
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0b5951ea-e949-44ab-ace6-c1a0022aea16 · inbound
Optimizing Few-Step Generation with Adaptive Matching Distillation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 12
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 9
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 33e5d802-3d2a-4651-b151-09629de6629c · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b7afc9d8-6de0-4291-a0a7-e00ec0b2aff4 · inbound
Discrete Meanflow Training Curriculum SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1fc9ff28-0fcf-4856-8cd0-b2152ba0335b · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f2607530-f1ff-4258-8e21-ba5f7bd97434 · inbound
Posterior Augmented Flow Matching SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation bdaccb71-9422-49c6-8e5a-9f0ad8dd9300 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f897c324-07b3-4bdc-9c55-35ffd910e7a6 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 76188e4d-3b26-48ae-a29d-7e21ba5d75f5 · inbound
FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5ba13344-c8b5-4227-bb73-ab17a96bad6e · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b83df877-b91c-4ffe-97eb-43e75d7e0363 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 01842dd2-230b-4768-8e71-0e08e07b1108 · inbound
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
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 91
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 91
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 37
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 387772a3-27e8-491b-a847-d27b6ea02328 · inbound
Balancing Image Compression and Generation with Bootstrapped Tokenization SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 80798ca6-a46a-486a-895f-f7cd2c7c48be · inbound
IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation cbf21d47-0c06-449f-aa2a-2023dbd965e1 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ba148561-f9e7-4894-9d16-79badf62f30f · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 76c39b9f-c1e0-4ae6-999c-306b27e47838 · inbound
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
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c095b750-6d29-4e92-9af0-4fce50520ab6 · inbound
Spatial Transport of Integration Error in Generative ODEs SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 42
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 17
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 27
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 60
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 SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
Reference 2024
Source-reported events for the cited work
Unavailable: canonical work link unavailable.