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Paper Citation Record · LEDGER

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

As of 19 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 6 inbound Pith citation observations for arXiv:2506.10975.

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

pith.paper-citation-record.v1
2506.10975 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:17:42.172650Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:24:37.596688Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:56:20.995621Z

Reference resolution

48 of 48 outbound references displayed

  • verified exact0
  • verified fuzzy20
  • unresolved28
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a44c70fe-cd75-438e-a387-3856a4d3e1bf · outbound

This paper cites 3, 4, 5, 7, 8.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos 3, 4, 5, 7, 8

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation af912b8c-c277-4bba-8716-c5e84ead5243 · outbound

This paper cites 2, 3, 4, 5.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos 2, 3, 4, 5

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2c9d0627-ec58-446f-bd33-3bbd218ec092 · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Cosmos World Foundation Model Platform for Physical AI

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 10e312bb-70ff-41e9-809a-9de0576a4a7e · outbound

This paper cites Ai-generated video detection via spatial-temporal anomaly learning.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Ai-generated video detection via spatial-temporal anomaly learning

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d481a0af-1860-47b6-96e3-822e819ad5e6 · outbound

This paper cites Navigation World Models.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Navigation World Models

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:17:41.920370Z digest=sha256:32a6a64042bdb82448ac2cf55e15442a84acb80f3193f0dbaecbe0a2dc0928a6

Observation 1ee3ef62-76de-477e-9a32-ca161555c739 · outbound

This paper cites Identify- ing and mitigating the security risks of generative ai.Founda- tions and Trends® in Privacy and Security, 6(1):1–52, 2023.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Identify- ing and mitigating the security risks of generative ai.Founda- tions and Trends® in Privacy and Security, 6(1):1–52, 2023

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3df54776-3cd6-4bcc-93ef-5d0ced48702b · outbound

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

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:17:41.931310Z digest=sha256:7a925d33a3878c43ec146a67323302740aab3359980159c863b06eeef0b1a5a6

Observation 2ba9fb8c-16b6-48c3-8e13-0f0d9554b8ad · outbound

This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos RT-1: Robotics Transformer for Real-World Control at Scale

Reference 8

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source=pdf_text observed=2026-08-07T04:17:41.936454Z digest=sha256:0b68eaa51e153971d6a221900d7440839834cc25900839bbef33b22f7bb48759

Observation 62f22291-57e7-490c-a756-68b1734f4cc0 · outbound

This paper cites Video generation models as world simulators.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Video generation models as world simulators

Reference 9

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T04:17:41.952416Z digest=sha256:5709f904112c1dc456e177f87bcbbf2f612e21b8995443564bc805fe70c11275

Observation 8a10be31-4f04-4640-9004-7309a2995cdd · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos nuscenes: A multi- modal dataset for autonomous driving

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:17:41.956806Z digest=sha256:b11d205adc5467dbc72c8181ec580aa498eba1ac519ac4214c3b85376077cf1b

Observation 0d4a039f-c3bf-4d1a-8cd5-f0f881efa6c5 · outbound

This paper cites DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark

Reference 11

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Observation 5097c0bc-7d99-47ec-9c4f-7c63f369dd8f · outbound

This paper cites VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0b3dbac5-9c9f-470f-a398-59d49d187ef6 · outbound

This paper cites DreamCinema: Cinematic Transfer with Free Camera and 3D Character.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos DreamCinema: Cinematic Transfer with Free Camera and 3D Character

Reference 13

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Source-reported events for the cited work

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Observation cfc041b9-0df3-4b4d-8074-20e92a39259f · outbound

This paper cites Seine: Short-to-long video diffu- sion model for generative transition and prediction.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Seine: Short-to-long video diffu- sion model for generative transition and prediction

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-07T04:17:42.910386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 91ec8817-e423-4b7a-ab9f-9416e76d952a · outbound

This paper cites The DeepFake Detection Challenge (DFDC) Dataset.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos The DeepFake Detection Challenge (DFDC) Dataset

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:17:41.979281Z digest=sha256:0acf8a0c83b642d4b4760e599930a133617651501b52beb3873bc052c74ff331

Observation d747dd56-e24b-47ca-9c7b-1a1d22eaaa1b · outbound

This paper cites Privacy and security concerns in generative ai: a compre- hensive survey.IEEE Access, 2024.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Privacy and security concerns in generative ai: a compre- hensive survey.IEEE Access, 2024

Reference 16

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:17:41.984018Z digest=sha256:42c29e70b6b948924bfca17529fb912958efa08f2409365f261839170801a09d

Observation 9997377b-ab32-4595-9160-b6570e6a899e · outbound

This paper cites Generative adversarial networks.Commu- nications of the ACM, 63(11):139–144, 2020.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Generative adversarial networks.Commu- nications of the ACM, 63(11):139–144, 2020

Reference 17

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Unavailable: canonical work link unavailable.

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Observation 217f1321-4ff4-4ec4-be5d-8d77b4c0bf37 · outbound

This paper cites Deepfakes dataset by google, jigsaw.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Deepfakes dataset by google, jigsaw

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation db01c34a-12a8-44f0-844f-bfc397391bd9 · outbound

This paper cites Spatiotemporal incon- sistency learning for deepfake video detection.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Spatiotemporal incon- sistency learning for deepfake video detection

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 44801751-866d-4097-9e69-eaecbbed4cce · outbound

This paper cites Spatiotemporal incon- sistency learning for deepfake video detection.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Spatiotemporal incon- sistency learning for deepfake video detection

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:17:42.839584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:17:42.003889Z digest=sha256:bddf93114586ad92583ff0dc2c2466f1f4a7dd937f48a89f223d76ee692141d7

Observation 1c24380e-f19c-4707-aba8-4461d7118b4c · outbound

This paper cites Hierarchical contrastive inconsistency learn- ing for deepfake video detection.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Hierarchical contrastive inconsistency learn- ing for deepfake video detection

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-07T04:17:42.824234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:17:42.011881Z digest=sha256:7ba5c9b1675b19489ca1ea9541c9c68e0fabb7dda92410745d42de239146bfa9

Observation b23269a5-4af1-4ae6-8573-baa15c052b7f · outbound

This paper cites Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 22

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source=pdf_text observed=2026-08-07T04:17:42.021838Z digest=sha256:5aeacf509c42ebec4e54156b7f231bfa8bc5eed60b14bb330214e43a44d0bb95

Observation 53019d95-1830-4046-b19c-4a902945d0c1 · outbound

This paper cites Owl-1: Omni World Model for Consistent Long Video Generation.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Owl-1: Omni World Model for Consistent Long Video Generation

Reference 23

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Observation 122c220e-aad1-48f4-a7f8-2fc25d4ee31c · outbound

This paper cites The Kinetics Human Action Video Dataset.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos The Kinetics Human Action Video Dataset

Reference 24

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source=pdf_text observed=2026-08-07T04:17:42.037816Z digest=sha256:11abdc8c09137b2f4a33314fc1ed6f08b2784304d4adbc04b7e8cb8f39fb33a7

Observation a5b3a430-9ee5-4288-ab6a-3b5e0840037e · outbound

This paper cites Auto-encoding vari- ational bayes, 2013.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Auto-encoding vari- ational bayes, 2013

Reference 25

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:17:42.043458Z digest=sha256:b535c90faaaf4671e9f3f7d131a64a9ff77f1bd18abaf1663c31eba65688de17

Observation 4032dc96-b41c-4a69-9ba5-b00996e25629 · outbound

This paper cites Video-llava: Learning united visual repre- sentation by alignment before projection.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Video-llava: Learning united visual repre- sentation by alignment before projection

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d67da6ac-d673-44d5-a55a-d8da28f118c6 · outbound

This paper cites Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c03281c1-59d6-43c8-a99b-3a69d58794ea · outbound

This paper cites Detecting AI-Generated Video via Frame Consistency.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Detecting AI-Generated Video via Frame Consistency

Reference 28

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Observation 73fbee0a-7979-4c92-bfb9-96f554444ee0 · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Latte: Latent Diffusion Transformer for Video Generation

Reference 29

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Observation 4625ccb8-675b-4558-9dab-15909e3d01a1 · outbound

This paper cites Impacts and Risk of Generative AI Technology on Cyber Defense.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Impacts and Risk of Generative AI Technology on Cyber Defense

Reference 30

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Observation e1922ebf-3207-4bf0-99a8-f1795e9e459b · outbound

This paper cites Genvidbench: A challenging benchmark for detecting ai-generated video.arXiv preprint arXiv:2501.11340, 2025.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Genvidbench: A challenging benchmark for detecting ai-generated video.arXiv preprint arXiv:2501.11340, 2025

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 82804305-49ea-472e-9a33-fab8442661da · outbound

This paper cites Thinking in frequency: Face forgery detection by min- ing frequency-aware clues.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Thinking in frequency: Face forgery detection by min- ing frequency-aware clues

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d4e2c8ac-6257-489d-8dc8-07597a933afc · outbound

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

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos High-resolution image synthesis with latent diffusion models

Reference 33

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Source-reported events for the cited work

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Observation 9d631f4f-c043-4f43-80f6-6bb59f0910c9 · outbound

This paper cites Faceforen- sics++: Learning to detect manipulated facial images.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Faceforen- sics++: Learning to detect manipulated facial images

Reference 34

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Unavailable: canonical work link unavailable.

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Observation 1cbb889d-4093-44cc-852d-436d577bdc1d · outbound

This paper cites Rethinking the up-sampling operations in cnn-based generative network for generalizable deepfake detection.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Rethinking the up-sampling operations in cnn-based generative network for generalizable deepfake detection

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f394ef41-17e8-4996-82c1-4028c6da88cc · outbound

This paper cites VideoMAE: Masked autoencoders are data-efficient learners for self-supervised video pre-training.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos VideoMAE: Masked autoencoders are data-efficient learners for self-supervised video pre-training

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 94294cc9-23b7-4eca-bf2e-5247c73cf7e5 · outbound

This paper cites 3D Reconstruction with Spatial Memory.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos 3D Reconstruction with Spatial Memory

Reference 37

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Observation 273664e0-8e9f-4f43-8590-e30863d2d4aa · outbound

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

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos ModelScope Text-to-Video Technical Report

Reference 38

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source=pdf_text observed=2026-08-07T04:17:42.111825Z digest=sha256:ff825cba58cf336c71135969ff20d4178f6cf21cbefa958e17281aa5dc6cc914

Observation 04f6b387-d6e3-4898-84fc-f8916006a24b · outbound

This paper cites Dust3r: Geometric 3d vi- sion made easy.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Dust3r: Geometric 3d vi- sion made easy

Reference 39

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:17:42.116646Z digest=sha256:28c4cb155fce31995cea5218f9afdcd7566b743bf87be674b97e0c1f22290849

Observation 863bd697-50f0-425d-8161-a85089500c3e · outbound

This paper cites Drivedreamer: Towards real-world- drive world models for autonomous driving.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Drivedreamer: Towards real-world- drive world models for autonomous driving

Reference 40

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source=pdf_text observed=2026-08-07T04:17:42.123128Z digest=sha256:0a8b392696ba432650592a218f61582b7963af61f19ba69d2f158731b5ffdec6

Observation 7ccd6b54-0578-4dde-93d6-f14f6a7ced4b · outbound

This paper cites LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

Reference 41

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source=pdf_text observed=2026-08-07T04:17:42.131292Z digest=sha256:1fd0ad9432ccb8a4f98d2ff9d14423d69ca2c777a8683f31917aac7cdd34ffdb

Observation e454a20b-8fe6-47c8-a76a-d85ca0b1a36d · outbound

This paper cites The emergence of deepfake technology: A review.Technology innovation management review, 9(11),.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos The emergence of deepfake technology: A review.Technology innovation management review, 9(11),

Reference 42

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:17:42.136571Z digest=sha256:b78cf561cc55ac3c7c249cb28c23e39398cc1945f93e8befb188ba25c3f1b1fd

Observation 60273e96-5b3e-4da7-828d-9f31b51ea010 · outbound

This paper cites Pandora: Towards General World Model with Natural Language Actions and Video States.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Pandora: Towards General World Model with Natural Language Actions and Video States

Reference 43

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source=pdf_text observed=2026-08-07T04:17:42.142859Z digest=sha256:9cbe350c34969fbef738eeb2da326506070903de3160058ada0621315c0f9e82

Observation d0ab5bab-b1fb-4047-a5fc-4dc9203236eb · outbound

This paper cites Tall: Thumbnail layout for deepfake video detection.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Tall: Thumbnail layout for deepfake video detection

Reference 44

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raw_fallback, observed 2026-08-07T04:17:42.651329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:17:42.147650Z digest=sha256:630a42917be0105253dead3a681d343a3bcb2feb9da3125486a607588982279b

Observation 87ad5ba1-6221-4ab1-8f9a-5d6080d98a66 · outbound

This paper cites A survey on deepfake video detection.Iet Biometrics, 10(6): 607–624, 2021.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos A survey on deepfake video detection.Iet Biometrics, 10(6): 607–624, 2021

Reference 45

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raw_fallback, observed 2026-08-07T04:17:42.635356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:17:42.156846Z digest=sha256:259b8f857c179527a3397d37322bfab5479d028f7ab980d98300a507b6ffce4a

Observation 1c6ad25f-1b79-48d4-b56d-c4363dd37cbb · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Adding conditional control to text-to-image diffusion models

Reference 46

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source=pdf_text observed=2026-08-07T04:17:42.162606Z digest=sha256:a0f619edb9f282bbe151b770271dba08bad671d5d139c6a40ee7ea81a8deee00

Observation 11531cb5-7d6e-48f9-9fa2-b2952922cd55 · outbound

This paper cites Occworld: Learning a 3d occupancy world model for autonomous driving.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Occworld: Learning a 3d occupancy world model for autonomous driving

Reference 47

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source=pdf_text observed=2026-08-07T04:17:42.167306Z digest=sha256:d9447bff2d1558c6afba7ba707fb3787e7a95a4fed63b048d64720c4e524fa9b

Observation 77d1fd57-4292-4a96-9e7f-bda07b876d1c · outbound

This paper cites Open-Sora: Democratizing Efficient Video Production for All.

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos Open-Sora: Democratizing Efficient Video Production for All

Reference 48

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source=pdf_text observed=2026-08-07T04:17:42.172650Z digest=sha256:e44d7b0b6b1ce0a7e37fd9480d4eef2c14a86dd791e24951091507e858026a06

Pith citing papers

Observation 6b415433-1011-4cb0-91c8-4ba9b555151f · inbound

MVAD: A Benchmark Dataset for Multimodal AI-Generated Video-Audio Detection cites this paper.

MVAD: A Benchmark Dataset for Multimodal AI-Generated Video-Audio Detection GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

Reference 14

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arxiv_id, observed 2026-05-17T03:48:58.508275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-17T03:48:26.807495Z digest=sha256:5337dccc710e8880be2206dc302613aea088a4d747d8bf57a253ed7477b52773

Observation b28ff347-5946-4733-b747-f05c853661ae · inbound

Skyra: AI-Generated Video Detection via Grounded Artifact Reasoning cites this paper.

Skyra: AI-Generated Video Detection via Grounded Artifact Reasoning GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

Reference 7

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arxiv_id, observed 2026-05-21T16:44:15.970706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-21T16:43:11.995960Z digest=sha256:6dfa5276d42f292ac988af8ea6d2b0a178386eebc058ef829392ef012b3a401d

Observation c5df0bd5-2b94-431c-95f4-fdb402dd6a8e · inbound

Measuring 3D Spatial Geometric Consistency in Dynamic Video Generation cites this paper.

Measuring 3D Spatial Geometric Consistency in Dynamic Video Generation GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

Reference 15

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source=pdf_text observed=2026-07-13T22:13:53.383917Z digest=sha256:97ab3697a63baa5b6fbbe7ce0dca998f2a8612d7abda326f93c428fef46c8ec4

Observation 5b7cbd48-deee-45a1-b3c2-769c29c9a0a9 · inbound

Explainable Forensics of Manipulated Segments in Untrimmed Long Videos cites this paper.

Explainable Forensics of Manipulated Segments in Untrimmed Long Videos GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

Reference 4

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verified exact
arxiv_id, observed 2026-07-01T22:56:20.997983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T14:49:11.015838Z digest=sha256:99f5f10ab756b71fa414d88971798c265e95b736890c721a8dcb2a5f55819405

Observation a88d2e43-dde9-412b-a84a-9ec738e7f5f6 · inbound

SafeGuard: A Multi-Agent Perception-Reasoning Framework for Social-Risk AI-Generated Video Detection cites this paper.

SafeGuard: A Multi-Agent Perception-Reasoning Framework for Social-Risk AI-Generated Video Detection GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

Reference 7

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source=pdf_text observed=2026-07-12T05:07:18.364787Z digest=sha256:70a885aeaecc98d63fa81e976a4a8649ea6ea585301738933347d4fd79cc31c1

Observation abe96b28-009f-467f-ab4f-34e0ff48eaef · inbound

SphereVideo: Prototype-anchored Hyperspherical Boundary for Continual AI-generated Video Detection cites this paper.

SphereVideo: Prototype-anchored Hyperspherical Boundary for Continual AI-generated Video Detection GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

Reference 6

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source=pdf_text observed=2026-08-06T00:24:37.596688Z digest=sha256:4fd7dddcabbff7fdaaa2ef7a01eb43f8359dc81c8eca25c22170bc296e57875c