Paper Citation Record · LEDGER

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction

As of 9 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2502.05503.

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

pith.paper-citation-record.v1
2502.05503 v3

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:07:58.535598Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T04:39:22.400458Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T04:40:23.162451Z

Reference resolution

52 of 52 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aacfe9df-39c6-452c-b5e1-be52c6c51e9d · outbound

This paper cites Keling1.5.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Keling1.5

Reference 1

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Observation ac4dd7b1-0c23-4aae-a005-a6d13101170e · outbound

This paper cites Dream machine.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Dream machine

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:59.070167Z

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Observation ebda91a0-3626-43f6-b6b0-1c102d52d5e9 · outbound

This paper cites VideoPhy: Evaluating Physical Commonsense for Video Generation.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction VideoPhy: Evaluating Physical Commonsense for Video Generation

Reference 3

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Observation 1ff5507f-4e73-4feb-a4b0-afa44b692e63 · outbound

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

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 4

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Observation 798ff80a-2cd3-4354-9295-160645abd189 · outbound

This paper cites Align your latents: High-resolution video synthesis with la- tent diffusion models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Align your latents: High-resolution video synthesis with la- tent diffusion models

Reference 5

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Observation c440b295-9d94-4df7-9a64-df2c877c113f · outbound

This paper cites VideoCrafter1: Open Diffusion Models for High-Quality Video Generation.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T19:07:58.357975Z

Source-reported events for the cited work

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Observation 14b9ae6f-d62c-4202-91ae-3efb178e7bc9 · outbound

This paper cites Videocrafter2: Overcoming data limitations for high-quality video diffusion models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Videocrafter2: Overcoming data limitations for high-quality video diffusion models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:59.054343Z

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Observation 64f19260-1f72-4b51-be90-1074ea98a5a3 · outbound

This paper cites Motion-Conditioned Diffusion Model for Controllable Video Synthesis.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Motion-Conditioned Diffusion Model for Controllable Video Synthesis

Reference 8

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Observation c3fe1dba-0b35-4c5f-92eb-5d952da7792c · outbound

This paper cites Haa500: Human-centric atomic action dataset with curated videos.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Haa500: Human-centric atomic action dataset with curated videos

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:59.044283Z

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Observation 26206c47-5205-47c1-902b-e11ee92308d9 · outbound

This paper cites Flownet: Learning optical flow with convolutional networks.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Flownet: Learning optical flow with convolutional networks

Reference 10

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Observation 2ee13d42-b45f-48ce-b2c0-b1086aff403a · outbound

This paper cites Generative adversarial nets.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Generative adversarial nets

Reference 11

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Observation 6b3e5c32-8e82-4621-8ec0-7c55200786c7 · outbound

This paper cites Seer: Language instructed video prediction with latent diffusion models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Seer: Language instructed video prediction with latent diffusion models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:59.021871Z

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Observation b671a80c-858d-4972-a793-055171c7fc59 · outbound

This paper cites Animatediff: Animate your personalized text-to- image diffusion models without specific tuning.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Animatediff: Animate your personalized text-to- image diffusion models without specific tuning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:59.011921Z

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Observation 986d7164-f394-4f8e-84c3-6235e1844c9d · outbound

This paper cites Flexible diffusion modeling of long videos.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Flexible diffusion modeling of long videos

Reference 14

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Observation 72201789-ecd8-4991-884a-e568932fc65a · outbound

This paper cites Latent Video Diffusion Models for High-Fidelity Long Video Generation.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Latent Video Diffusion Models for High-Fidelity Long Video Generation

Reference 15

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Observation b7b007f1-8ca3-4ef6-92ea-d60006a5144d · outbound

This paper cites CLIPScore: A reference-free evaluation metric for image captioning.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction CLIPScore: A reference-free evaluation metric for image captioning

Reference 16

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Observation d72a3536-7862-4bf4-882f-b53258223c92 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T19:07:58.399178Z

Source-reported events for the cited work

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Observation 6223fdd1-b4f0-4227-addb-9a575b2461f6 · outbound

This paper cites Denoising dif- fusion probabilistic models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Denoising dif- fusion probabilistic models

Reference 18

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Observation 3a5afeaa-0a9e-4650-980a-8e0523f45d91 · outbound

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

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Imagen Video: High Definition Video Generation with Diffusion Models

Reference 19

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Source-reported events for the cited work

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Observation 8afc2389-46a0-4e76-bf98-656e9d2f75e6 · outbound

This paper cites Video dif- fusion models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Video dif- fusion models

Reference 20

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Observation 0c714bc0-a28f-4aa7-9615-12c6b8845cbf · outbound

This paper cites Vbench: Comprehensive bench- mark suite for video generative models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Vbench: Comprehensive bench- mark suite for video generative models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.962116Z

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Observation 3fe6320b-88ad-4825-8377-c3406790a430 · outbound

This paper cites T2vbench: Benchmarking temporal dynamics for text-to- video generation.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction T2vbench: Benchmarking temporal dynamics for text-to- video generation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.951655Z

Source-reported events for the cited work

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Observation aa4652ee-d295-4a5f-b6c8-3a22b2d993d0 · outbound

This paper cites Text2performer: Text- driven human video generation.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Text2performer: Text- driven human video generation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.941907Z

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Observation 7941c066-3b2c-4ed5-a730-85ba33d1374d · outbound

This paper cites Text2video-zero: Text- to-image diffusion models are zero-shot video generators.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Text2video-zero: Text- to-image diffusion models are zero-shot video generators

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.931873Z

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Observation 217e425d-fe78-4f18-8ab1-25d69403966a · outbound

This paper cites Fu- ture frame prediction for anomaly detection–a new baseline.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Fu- ture frame prediction for anomaly detection–a new baseline

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.922207Z

Source-reported events for the cited work

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Observation dd920b3e-31b5-4301-9e8a-12b94d5b5970 · outbound

This paper cites Evalcrafter: Benchmarking and evalu- ating large video generation models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Evalcrafter: Benchmarking and evalu- ating large video generation models

Reference 26

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Observation 9e8b2b9e-6a69-49ba-ba44-134adaf51296 · outbound

This paper cites Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

Reference 27

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Source-reported events for the cited work

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Observation 838d67dc-4286-41c8-aec5-d3fed257a187 · outbound

This paper cites A hybrid video anomaly detection framework via memory-augmented flow reconstruction and flow-guided frame prediction.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction A hybrid video anomaly detection framework via memory-augmented flow reconstruction and flow-guided frame prediction

Reference 28

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Observation a13e4214-535c-4e0e-833e-07f69f9abf1f · outbound

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

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation

Reference 29

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Source-reported events for the cited work

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Observation 7720d487-6810-4223-82e4-78b4030889a0 · outbound

This paper cites Anomaly detec- tion in video sequence with appearance-motion correspon- dence.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Anomaly detec- tion in video sequence with appearance-motion correspon- dence

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.893328Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4a515592-1148-40bd-a624-61e167a8afec · outbound

This paper cites Conditional image-to-video gener- ation with latent flow diffusion models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Conditional image-to-video gener- ation with latent flow diffusion models

Reference 31

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Observation 57ebd623-431f-4304-ac8a-565380684eec · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction High-resolution image syn- thesis with latent diffusion models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.872850Z

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Observation a1923c1d-32ea-49fc-94b7-cadfaee4c4e9 · outbound

This paper cites Gen-3 alpha.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Gen-3 alpha

Reference 33

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Observation 0d0e1072-f738-4ce8-8764-d828ea64158f · outbound

This paper cites Improved techniques for training gans.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Improved techniques for training gans

Reference 34

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Observation 8af7054e-578d-49ab-8bab-cf2cc931b67e · outbound

This paper cites Flowformer++: Masked cost volume autoen- coding for pretraining optical flow estimation.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Flowformer++: Masked cost volume autoen- coding for pretraining optical flow estimation

Reference 35

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Observation 40e2eef0-db38-4197-8c5b-49b3c8ad3160 · outbound

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

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 36

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Observation 8dc8c0aa-e6b9-47a5-8613-26ba16df7514 · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 37

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Observation e8bf2cdb-1fb7-4c40-8265-1da70dd2b5e3 · outbound

This paper cites Fvd: A new metric for video generation.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Fvd: A new metric for video generation

Reference 38

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Observation 969b66bb-f100-427d-8c42-7dd76cd86847 · outbound

This paper cites ModelScope Text-to-Video Technical Report.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction ModelScope Text-to-Video Technical Report

Reference 39

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Observation c0849c7b-f4ac-474d-a11a-5c8d5921ca20 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Image quality assessment: from error visibility to structural similarity

Reference 40

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Observation 252d19db-03ee-4e5a-87e4-57a7b091b105 · outbound

This paper cites Physics 101: Learning phys- ical object properties from unlabeled videos.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Physics 101: Learning phys- ical object properties from unlabeled videos

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.816422Z

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Observation 18aa7581-19b7-4363-9cd9-bc4c7d889d10 · outbound

This paper cites Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.805369Z

Source-reported events for the cited work

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Observation 7ba1da60-6668-4085-acde-f8c7f2cdd3e0 · outbound

This paper cites Dynamicrafter: Animating open-domain images with video diffusion priors.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Dynamicrafter: Animating open-domain images with video diffusion priors

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.793865Z

Source-reported events for the cited work

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Observation 760dfc1b-dff9-4059-9ec1-ce7c0eb813d3 · outbound

This paper cites AID: Adapting Image2Video Diffusion Models for Instruction-guided Video Prediction.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction AID: Adapting Image2Video Diffusion Models for Instruction-guided Video Prediction

Reference 44

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Source-reported events for the cited work

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Observation 51d3eea7-44f7-4d0c-b1e3-7e6cb019ae1a · outbound

This paper cites Qwen2 Technical Report.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Qwen2 Technical Report

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T19:07:58.505717Z

Source-reported events for the cited work

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Observation 8d69ffdf-297a-4ffa-bcd2-28472ca2b2bc · outbound

This paper cites Video event restoration based on keyframes for video anomaly detection.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Video event restoration based on keyframes for video anomaly detection

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.781024Z

Source-reported events for the cited work

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Observation 9f965f28-18f7-4268-83d3-846089dbc865 · outbound

This paper cites Old is gold: Redefining the adversari- ally learned one-class classifier training paradigm.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Old is gold: Redefining the adversari- ally learned one-class classifier training paradigm

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.770133Z

Source-reported events for the cited work

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Observation 7bdc9441-8f93-4852-bb64-77aa9eac0ed0 · outbound

This paper cites From actemes to action: A strongly-supervised repre- sentation for detailed action understanding.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction From actemes to action: A strongly-supervised repre- sentation for detailed action understanding

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.759635Z

Source-reported events for the cited work

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Observation 6cbaa88b-b97b-4adf-a4a1-4cd48afd9b07 · outbound

This paper cites 3D Object Manipulation in a Single Image using Generative Models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction 3D Object Manipulation in a Single Image using Generative Models

Reference 49

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Source-reported events for the cited work

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Observation cbaae48b-53d0-41b8-bdd0-fa6c9046feac · outbound

This paper cites Open-sora: Democratizing efficient video production for all, 2024.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction Open-sora: Democratizing efficient video production for all, 2024

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.748383Z

Source-reported events for the cited work

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Observation cca730df-da82-4a9d-b7ec-7c967d999e6d · outbound

This paper cites MagicVideo: Efficient Video Generation With Latent Diffusion Models.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction MagicVideo: Efficient Video Generation With Latent Diffusion Models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-08T19:07:58.531238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0c941da-6f29-4d31-9bce-eef5b89bf89d · outbound

This paper cites 2 > 1 > 3 > 4,.

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction 2 > 1 > 3 > 4,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:07:58.735388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation 560fa5f9-410a-468d-a39f-088e8b0260b2 · inbound

CRONOS: Benchmarking Counterfactual Physical Consistency in Video Models cites this paper.

CRONOS: Benchmarking Counterfactual Physical Consistency in Video Models A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:40:23.166018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.