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Paper Citation Record · LEDGER

Accelerating Video Diffusion Models via Distribution Matching

As of 14 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 3 inbound Pith citation observations for arXiv:2412.05899.

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

pith.paper-citation-record.v1
2412.05899 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:17:52.720444Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T09:28:00.597160Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T09:32:16.742169Z

Reference resolution

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved37
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 00ba17f1-02ea-49b0-a750-75b230db7426 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Accelerating Video Diffusion Models via Distribution Matching Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

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source=pdf_text observed=2026-08-11T20:17:52.569364Z digest=sha256:e3d574fd90d71f4bba5a6e632d74a3fafd4ae5c736e50a206ba048aad75eac94

Observation 99b70d1f-08b6-4f48-9473-b1957323020d · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

Accelerating Video Diffusion Models via Distribution Matching CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 6

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source=pdf_text observed=2026-08-11T20:17:52.587933Z digest=sha256:b3a69d29ef19458173240f04f6e6c8405a219467da35c564c1cfe28b05c0319a

Observation 165f577a-0526-4bed-815e-c2b037285702 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Accelerating Video Diffusion Models via Distribution Matching Imagen Video: High Definition Video Generation with Diffusion Models

Reference 7

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source=pdf_text observed=2026-08-11T20:17:52.592293Z digest=sha256:b50e032df32dc165d943380adb1c45588c9c8f5b3bb020b2a222c712e5cb3d3b

Observation fd9a3ce0-92c2-4d66-8039-12a71439e3b2 · outbound

This paper cites Auto-Encoding Variational Bayes.

Accelerating Video Diffusion Models via Distribution Matching Auto-Encoding Variational Bayes

Reference 9

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source=pdf_text observed=2026-08-11T20:17:52.600892Z digest=sha256:3d03466ae9706f5f7ed67ee335ca178cc6b97c4de50f21de776ac4f464943d6c

Observation a1d2cba3-1372-4fc1-b384-2dfab8141452 · outbound

This paper cites DiffWave: A Versatile Diffusion Model for Audio Synthesis.

Accelerating Video Diffusion Models via Distribution Matching DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 11

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source=pdf_text observed=2026-08-11T20:17:52.609046Z digest=sha256:45276da3c570b5757cc264107a5f691087980f1879ba726c4c498886c065990c

Observation 9cc7045f-8204-4314-bff3-e01eeb5b52e5 · outbound

This paper cites T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback.

Accelerating Video Diffusion Models via Distribution Matching T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 12

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source=pdf_text observed=2026-08-11T20:17:52.613147Z digest=sha256:ec7673fed95bf89183889f32036d23c68b5081b51600a8949273a07bac26225c

Observation 1c2d17f6-f75d-4bfb-8c5e-97193f61a611 · outbound

This paper cites AnimateDiff-Lightning: Cross-Model Diffusion Distillation.

Accelerating Video Diffusion Models via Distribution Matching AnimateDiff-Lightning: Cross-Model Diffusion Distillation

Reference 13

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source=pdf_text observed=2026-08-11T20:17:52.616564Z digest=sha256:435e73a1bb3991c395e3dd670059491d121a2a3322ade3cdbdf9ba7e64b3b30f

Observation 67f420c4-124b-4da0-950f-6f991788a89c · outbound

This paper cites SDXL-Lightning: Progressive Adversarial Diffusion Distillation.

Accelerating Video Diffusion Models via Distribution Matching SDXL-Lightning: Progressive Adversarial Diffusion Distillation

Reference 14

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source=pdf_text observed=2026-08-11T20:17:52.619824Z digest=sha256:b1e1bbf642f77b9fad3a1078f902a8aaa7f4ec95978a10c473bcdc4235559e13

Observation abca3990-1a5e-4f94-b291-b250589e03d8 · outbound

This paper cites Rectified Flow: A Marginal Preserving Approach to Optimal Transport.

Accelerating Video Diffusion Models via Distribution Matching Rectified Flow: A Marginal Preserving Approach to Optimal Transport

Reference 15

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source=pdf_text observed=2026-08-11T20:17:52.624155Z digest=sha256:e477d91220a715269dd89efa076ab9954d91feafce9f308ee305264b771d72d6

Observation 0d1cc96f-343e-461b-b48d-222ec1540f44 · outbound

This paper cites Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed.

Accelerating Video Diffusion Models via Distribution Matching Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed

Reference 17

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source=pdf_text observed=2026-08-11T20:17:52.632916Z digest=sha256:505aefd64dfbc14816d435388b06a9f660fdf1ff75b67a957c1a5355475f25f4

Observation c1c86cb6-3403-4336-97ad-11b0075f55f3 · outbound

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

Accelerating Video Diffusion Models via Distribution Matching Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Reference 18

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source=pdf_text observed=2026-08-11T20:17:52.637688Z digest=sha256:af6ddda8e1e34bde278584432ca9f454c2f5ffe98f326cd2bcb1545d36268ad4

Observation 892dc76a-5cd4-4f07-a4eb-883c4d4f0727 · outbound

This paper cites OSV: One Step is Enough for High-Quality Image to Video Generation.

Accelerating Video Diffusion Models via Distribution Matching OSV: One Step is Enough for High-Quality Image to Video Generation

Reference 19

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source=pdf_text observed=2026-08-11T20:17:52.642322Z digest=sha256:449c7f17154ee451212bc453ceb46b1853bf75e9a94619ce51e56cd8191b2736

Observation bf3e4f3a-0959-4be6-b286-5c982c35e617 · outbound

This paper cites OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation.

Accelerating Video Diffusion Models via Distribution Matching OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation

Reference 20

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Observation 8b957deb-7705-404c-8059-42a66cb75333 · outbound

This paper cites Open-sora-plan.

Accelerating Video Diffusion Models via Distribution Matching Open-sora-plan

Reference 21

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source=pdf_text observed=2026-08-11T20:17:52.651491Z digest=sha256:fd525327b08018a3d9439c0aa706c9849d787fcddde70a3a229867578c172aef

Observation 55170175-2ff6-4491-9e4f-b8c9597f0fac · outbound

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

Accelerating Video Diffusion Models via Distribution Matching SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 22

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source=pdf_text observed=2026-08-11T20:17:52.655287Z digest=sha256:23cbf5eaf5453738d3fc0e40c5f03f19cb81cbfdb735f14e638854cd35d04569

Observation 14cd3c75-0101-4e00-bbc6-1024d2dc026c · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

Accelerating Video Diffusion Models via Distribution Matching DreamFusion: Text-to-3D using 2D Diffusion

Reference 23

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source=pdf_text observed=2026-08-11T20:17:52.659634Z digest=sha256:e9c7c819e55d93e19aff4081a1c05559f3ac06990f6fe78dbf8b374683ca4276

Observation 0323e8a7-b640-4bfb-b366-a1429fc68191 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Accelerating Video Diffusion Models via Distribution Matching Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 24

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source=pdf_text observed=2026-08-11T20:17:52.664112Z digest=sha256:460e78cfff246050c4c2723d77ae4dce814c0e97153da1ea89d1c2493a5d8d46

Observation ebc67f10-f04a-4565-800f-e9b06e36a698 · outbound

This paper cites Make-A-Video: Text-to-Video Generation without Text-Video Data.

Accelerating Video Diffusion Models via Distribution Matching Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 26

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source=pdf_text observed=2026-08-11T20:17:52.670713Z digest=sha256:7ba8d2d867cd5f831373dc1d7e2071a479aab1731c51933c1efb7465f7b6c2e1

Observation 3003471f-85c9-4394-af42-5fec51985426 · outbound

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

Accelerating Video Diffusion Models via Distribution Matching Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 28

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source=pdf_text observed=2026-08-11T20:17:52.677853Z digest=sha256:af2606d42e35d68fe78defab96eefe5ab01ad6ffc464c1004802e987277c3135

Observation fe1bd1c6-43fb-466d-846f-a7c0ab5720e8 · outbound

This paper cites LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models.

Accelerating Video Diffusion Models via Distribution Matching LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models

Reference 30

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source=pdf_text observed=2026-08-11T20:17:52.686270Z digest=sha256:6f2a22ceb4e549b4e21e6500f6e238a35e77046c3f49d7de5060d86731763b69

Observation a17098ee-e2bb-460e-96da-408f81852423 · outbound

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

Accelerating Video Diffusion Models via Distribution Matching CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 31

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source=pdf_text observed=2026-08-11T20:17:52.690238Z digest=sha256:9aaba085907f64f7d8327cb9f16014f095781056be1bcf2b020b7dc5b8b38c8c

Observation e2822956-26e9-4ef9-b4ac-8c30c0fe3fb8 · outbound

This paper cites SE(3) diffusion model with application to protein backbone generation.

Accelerating Video Diffusion Models via Distribution Matching SE(3) diffusion model with application to protein backbone generation

Reference 32

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source=pdf_text observed=2026-08-11T20:17:52.694287Z digest=sha256:a48d39aec0b020a64b0080d2eff5dd5d8c686ed0cec454c1452d963cef4e562c

Observation 9298ae2e-65c6-4720-ac8c-60c61805a41a · outbound

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

Accelerating Video Diffusion Models via Distribution Matching Improved Distribution Matching Distillation for Fast Image Synthesis

Reference 33

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source=pdf_text observed=2026-08-11T20:17:52.698987Z digest=sha256:d7b75286c135e04510d3b1089cbe80fe969f67570fccc637f35e6468edb49442

Observation 4afc7c36-2533-4f1a-b610-eb1483b10d9d · outbound

This paper cites Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation.

Accelerating Video Diffusion Models via Distribution Matching Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation

Reference 34

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source=pdf_text observed=2026-08-11T20:17:52.703606Z digest=sha256:31e8a4da786e04b7d666a64df578634df7ed07dde433dd30341f8ba396d12294

Observation 4e8b2b34-974c-4447-a9a0-da6155950680 · outbound

This paper cites Fast Sampling of Diffusion Models with Exponential Integrator.

Accelerating Video Diffusion Models via Distribution Matching Fast Sampling of Diffusion Models with Exponential Integrator

Reference 35

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source=pdf_text observed=2026-08-11T20:17:52.707980Z digest=sha256:5bd9e05770f36d6b0b056587cbb5eda119dde3d061f57b64eae1d5b7780d70d2

Observation 054f2700-8e02-4ad1-b8c7-07915b1f2285 · outbound

This paper cites I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models.

Accelerating Video Diffusion Models via Distribution Matching I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models

Reference 36

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source=pdf_text observed=2026-08-11T20:17:52.712254Z digest=sha256:9f63ee3c1f2ae021c2d213c52ad1ff1dce5843c961b2bbe72de4933298c4f02c

Observation 152781fe-1807-4f93-aa15-a6473e5e4d17 · outbound

This paper cites SF-V: Single Forward Video Generation Model.

Accelerating Video Diffusion Models via Distribution Matching SF-V: Single Forward Video Generation Model

Reference 37

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source=pdf_text observed=2026-08-11T20:17:52.716615Z digest=sha256:6d3dbe9e06e58e98eef5b42c569887a77f06a09897e919878e155dc158f51dc9

Observation 1736984f-f17f-4538-bffb-f6464c5e5c00 · outbound

This paper cites Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation.

Accelerating Video Diffusion Models via Distribution Matching Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation

Reference 38

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source=pdf_text observed=2026-08-11T20:17:52.720444Z digest=sha256:2ecf5c4203cb8bcbc39d43e00786d5f4ea9f1f281d9e44511a56aed8f926e4bc

Observation 494e74dc-c3ab-4519-b4a6-8ab9852f8d19 · outbound

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

Accelerating Video Diffusion Models via Distribution Matching Progressive Distillation for Fast Sampling of Diffusion Models

Reference 1992

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source=pdf_text observed=2026-08-11T20:17:52.667878Z digest=sha256:597cc720452aa7f882339cd07bda4f60e56ebb5d0bca1d67eecdbe05d94d8d82

Observation f2d89756-59c5-4924-9460-b3e83d5c95f1 · outbound

This paper cites Imagine Flash: Accelerating Emu Diffusion Models with Backward Distillation.

Accelerating Video Diffusion Models via Distribution Matching Imagine Flash: Accelerating Emu Diffusion Models with Backward Distillation

Reference 2013

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source=pdf_text observed=2026-08-11T20:17:52.604806Z digest=sha256:e36b5685113fde829ff9b7407ba6ce350069f8c1a49b361688afa1c19ca21c20

Observation 29fd787a-61f4-44c6-b3ca-e77d1e6a389b · outbound

This paper cites Denoising Diffusion Implicit Models.

Accelerating Video Diffusion Models via Distribution Matching Denoising Diffusion Implicit Models

Reference 2015

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source=pdf_text observed=2026-08-11T20:17:52.674027Z digest=sha256:b3670fe42382aa8c744c82d06ac453c3a83acfb0db81c3502ae250352aa77ca7

Observation baa9419f-94f1-4fa3-a2cc-e0b0ffece0b5 · outbound

This paper cites AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data.

Accelerating Video Diffusion Models via Distribution Matching AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data

Reference 2018

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source=pdf_text observed=2026-08-11T20:17:52.681971Z digest=sha256:bbba163bdd553239807eac4845a13bc6360d221ddab8e7c12e9a943234cb75cd

Observation de0a4b24-b68d-47f2-a068-64c35b0d4d13 · outbound

This paper cites Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion.

Accelerating Video Diffusion Models via Distribution Matching Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

Reference 2019

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source=pdf_text observed=2026-08-11T20:17:52.597172Z digest=sha256:299c440834a3e68b01cc1bbf1352f0ed95c2035fb7667a7edc3f6cd7e7a151a6

Observation 29ec8558-161c-496a-afaf-acf6be504b7c · outbound

This paper cites an unresolved cited work.

Accelerating Video Diffusion Models via Distribution Matching Unresolved cited work

Reference 2020

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source=pdf_text observed=2026-08-11T20:17:52.578504Z digest=sha256:e5dd0450ae902a6d45cb0d733d66bd187011644bfcf79f3e49e963dbe0dd87a4

Observation 075cdb30-ac06-4452-b787-82ae6457fa05 · outbound

This paper cites Density estimation using Real NVP.

Accelerating Video Diffusion Models via Distribution Matching Density estimation using Real NVP

Reference 2021

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source=pdf_text observed=2026-08-11T20:17:52.573832Z digest=sha256:f6be9a9241181467a5eb6fd1c1b43822fb1e9a91f93b9c44c09a899ab55450b2

Observation 3f34be5c-f475-408a-9160-31c204d32e39 · outbound

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

Accelerating Video Diffusion Models via Distribution Matching InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation

Reference 2022

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source=pdf_text observed=2026-08-11T20:17:52.628143Z digest=sha256:00f3e9ac97eecfaa93286edcdea7f007d9277f87f2cc8c405817cd0198df78f7

Observation f9e2acc2-1985-4bc0-add9-163bd0f3a5a5 · outbound

This paper cites AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.

Accelerating Video Diffusion Models via Distribution Matching AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 2023

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source=pdf_text observed=2026-08-11T20:17:52.582750Z digest=sha256:20e2b842f484c0c449a84c7a8f3e0f6329506d6d58d96696b75dda68367d98ee

Observation f97b9e80-af35-4a27-91d3-8d8d4232dd74 · outbound

This paper cites Towards Principled Methods for Training Generative Adversarial Networks.

Accelerating Video Diffusion Models via Distribution Matching Towards Principled Methods for Training Generative Adversarial Networks

Reference 2024

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no resolver link, observed 2026-08-11T20:17:52.564536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:17:52.564536Z digest=sha256:fa4ead3dbd8eb23a0f0433f22c76cb5824c857f763588c736d3a4a24f7f8ac15

Pith citing papers

Observation 8e30cff3-32f0-4b77-aaf1-f2f31e7dc61c · inbound

ReSim: Reliable World Simulation for Autonomous Driving cites this paper.

ReSim: Reliable World Simulation for Autonomous Driving Accelerating Video Diffusion Models via Distribution Matching

Reference 119

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:32:16.745638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T09:28:00.597160Z digest=sha256:5472045b7e3f28688ac2ea017489f92f086ab04eb58354ce86c7e964ac59cd24

Observation 75e53e38-b6e0-4dd5-87b0-e9042a296272 · inbound

Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms cites this paper.

Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms Accelerating Video Diffusion Models via Distribution Matching

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-14T01:38:35.957678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-14T01:35:14.878069Z digest=sha256:da63289f12c331b094a896de08ee9e3ad7db11f1ed3c067add330e667be7c926

Observation 51cede1c-2868-488b-a9b5-f9c53624b4a6 · inbound

Efficient Video Diffusion Models: Advancements and Challenges cites this paper.

Efficient Video Diffusion Models: Advancements and Challenges Accelerating Video Diffusion Models via Distribution Matching

Reference 203

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:03:26.297060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T08:28:29.706249Z digest=sha256:ddc0cd8812b3b3364f19306b16295ad62d9b3149057934e3926a4257ba023f3e