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Paper Citation Record · LEDGER

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation

As of 7 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2507.01255.

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

pith.paper-citation-record.v1
2507.01255 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:03:04.659589Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T05:17:30.010064Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T05:21:28.590658Z

Reference resolution

64 of 64 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved61
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fbbd563e-ec74-4f37-8317-4799641f3826 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 1

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Observation ae55ebc0-a6f1-4d91-989a-2cd303e97666 · outbound

This paper cites Qwen2.5-VL Technical Report.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Qwen2.5-VL Technical Report

Reference 2

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source=arxiv_source observed=2026-08-06T21:02:59.696652Z digest=sha256:1e7b2bb69c8726cf4fc615eaaf7af8e5a9b2eb05bf68bfa8c1e128238a0edc82

Observation 0d94dda2-73b6-48a9-bdc4-86314dda94a2 · outbound

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

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation VideoPhy: Evaluating Physical Commonsense for Video Generation

Reference 3

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Observation 4890cf75-ef80-4461-a0a5-40f9dd2c9e98 · outbound

This paper cites A Note on the Inception Score.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation A Note on the Inception Score

Reference 4

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source=arxiv_source observed=2026-08-06T21:02:59.863704Z digest=sha256:8777dc1246be5d4106c9702377e2a6247598b67c5fe28702887f497c8870ef56

Observation 0be5a196-af79-4a4c-8de7-e80c95fa093b · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 5

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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.

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Observation b2607711-8902-49cc-ac9b-90d0be7f7152 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 6

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source=arxiv_source observed=2026-08-06T21:03:00.067911Z digest=sha256:a44c14e82d185739c71ce859d1f7edd73e15be26c0adff4bcd7fdd02f73c2187

Observation 95f6ea13-cb89-43c9-b5c1-0b6d1f81f769 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 7

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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.

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Observation df99ce7b-85a4-4500-8458-02206b779973 · outbound

This paper cites FingER: Content Aware Fine-grained Evaluation with Reasoning for AI-Generated Videos.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation FingER: Content Aware Fine-grained Evaluation with Reasoning for AI-Generated Videos

Reference 8

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Observation aed5999e-88d2-43a9-91ed-6fdd9febd152 · outbound

This paper cites GAIA: Rethinking Action Quality Assessment for AI-Generated Videos.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation GAIA: Rethinking Action Quality Assessment for AI-Generated Videos

Reference 9

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Observation 4375910f-de56-4c2b-a6fa-eaeae78e9265 · outbound

This paper cites SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models

Reference 10

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Observation 3f23ee12-5280-418d-a9f6-20e8a8ca6a1e · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 11

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Observation 276afe5c-c528-48c8-b47b-90da8af4beae · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 12

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Observation 41265d1b-7404-45c9-9211-d0360f309b33 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 13

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Observation 402c126e-f787-4653-afe9-1576a29eff35 · outbound

This paper cites VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation

Reference 14

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Observation 2f88634e-8ec3-407f-b77e-e2a0ef87cf73 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 15

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source=arxiv_source observed=2026-08-06T21:03:00.730865Z digest=sha256:189c24bbab1109ce928f5ada1d06c15647a748d4acbab4d928ee5d839820ea51

Observation c8ef9538-5c74-4061-85f6-e1fd67e29035 · outbound

This paper cites Video Diffusion Models.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Video Diffusion Models

Reference 16

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Observation ea392ca7-4baf-476d-9aa9-5cd84cd6d310 · outbound

This paper cites TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering

Reference 17

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Observation b26e608d-5d8e-415d-9b8f-a33390aec125 · outbound

This paper cites VBench: Comprehensive Benchmark Suite for Video Generative Models.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation VBench: Comprehensive Benchmark Suite for Video Generative Models

Reference 18

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Observation 7b4d0a9c-8265-4f79-ba94-393d6ca46d76 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 19

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 7f4fd653-6375-4729-b254-52c723f24a50 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 20

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Observation c1ac0209-aed8-4f51-be51-7006c8f71698 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 21

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Observation 005fcb5e-13c4-450f-acd2-ae63d1b1e282 · outbound

This paper cites Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessment.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessment

Reference 22

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Observation 684a9b40-bdc4-4bf7-b58e-43dff17d0759 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 23

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Observation ef2fe87d-4d27-4650-80b5-8d47954eb964 · outbound

This paper cites VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation

Reference 24

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Observation fc9471a3-dbe4-41d4-a0e3-bc57dd498b85 · outbound

This paper cites OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents

Reference 25

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Observation 8ab71448-17df-4dc7-9fb0-76f42293e516 · outbound

This paper cites What matters when building vision-language models?.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation What matters when building vision-language models?

Reference 26

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Observation aee28718-be48-4b93-8c79-f36454f81bea · outbound

This paper cites Self-Correcting Text-to-Video Generation with Misalignment Detection and Localized Refinement.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Self-Correcting Text-to-Video Generation with Misalignment Detection and Localized Refinement

Reference 27

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Observation e00c755e-965c-4a5d-baba-242b3ce242be · outbound

This paper cites GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 28

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Observation 71e1d68b-15df-4b44-920d-feab10009b62 · outbound

This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Reference 29

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Observation 5a0efb79-cf21-439b-94b3-d8c0f7537392 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 30

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Observation 83d644ee-56e3-4b12-9cef-99ea843bc41a · outbound

This paper cites Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion Model.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion Model

Reference 31

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Observation cf322acd-ab3c-4a8b-8434-9c7e5e8b4c9f · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Improved Baselines with Visual Instruction Tuning

Reference 32

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Observation c1aaf6c7-900c-4bcd-9251-ee4bd76ed826 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 33

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Observation b9aabf74-faaa-499d-bfd1-46ecf2b681a4 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 34

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source=arxiv_source observed=2026-08-06T21:03:02.090324Z digest=sha256:f95d7de4f0c3d21f19957e56c5ff409bcecc5c1e4e3e300443e9e357b4f1a1fd

Observation f0119427-a65d-4a60-ac1a-ef8c87b01a66 · outbound

This paper cites G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

Reference 35

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source=arxiv_source observed=2026-08-06T21:03:02.143250Z digest=sha256:be7e114d9b0091bef15bb648586d85ad0048807307857f9d5e1db795d9d8577b

Observation 1cb6445a-274b-4862-9442-5bd5d34957b1 · outbound

This paper cites EvalCrafter: Benchmarking and Evaluating Large Video Generation Models.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation EvalCrafter: Benchmarking and Evaluating Large Video Generation Models

Reference 36

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Observation 197a4a08-7974-4cc0-9bec-5be62ce9cf83 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 37

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source=arxiv_source observed=2026-08-06T21:03:02.307328Z digest=sha256:f2cbeb41610e7c012a0f3a48b05e0c679754247924fdaa73f55096147645bee9

Observation 88984ed8-2776-40b8-8c93-0f2a2082dd99 · outbound

This paper cites T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models

Reference 38

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source=arxiv_source observed=2026-08-06T21:03:02.376272Z digest=sha256:d96f8d7f4a24b4e0e348d47d18c1f15a50e4fb04e1df38e6d9dd28fbbdc3b5cd

Observation c9831e71-282f-4231-8a5a-e7f13f0e4e19 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 39

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source=arxiv_source observed=2026-08-06T21:03:02.444756Z digest=sha256:9291e8d36f33a5963df9b1b1ba272248cb3602703d6d0ca3130eb28fd6b415f2

Observation 5ae1796e-7d05-4115-9155-0ff4916936bc · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 40

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source=arxiv_source observed=2026-08-06T21:03:02.509972Z digest=sha256:1ce4be56f5ad580edb8253e80bff08748fd973b21ac18c9870fda79f18c2fa72

Observation 6f096207-9ff4-4cac-acd4-25a259879528 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 41

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:03:02.574342Z digest=sha256:f561d3c47e4172724315b7ba370c74b32b95efbf9122de15fb63bca17b544e61

Observation 2ad4ba2b-9cb3-49c4-b641-82d5346db48e · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 42

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source=arxiv_source observed=2026-08-06T21:03:02.615800Z digest=sha256:1b263ed711e0f3839679a86a2ec1f6ef01f07cd3b0be953d825454efc30a9c99

Observation 9800e58b-903b-4ec2-8bb2-99db716bc8c2 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 43

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source=arxiv_source observed=2026-08-06T21:03:02.699594Z digest=sha256:6c3c7868484fd5392434a56cbf4b872f94ba07666aae9773f2dfef5df7413deb

Observation 749b3c3d-405d-4546-a277-829ef3b6a30b · outbound

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

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 44

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source=arxiv_source observed=2026-08-06T21:03:02.741253Z digest=sha256:f69bec840d5d521dd05b9c67bc38f2e9e5e349d1e175b754fbc494a169d72582

Observation 465bd3f7-dd1d-4c73-9991-8d7d4f5a850e · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 45

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source=arxiv_source observed=2026-08-06T21:03:02.803398Z digest=sha256:a953dfd6f93121f38d3a81029aa17af090f51288d51212dfb426ae66de4c923b

Observation 67a944d5-e12d-423f-96f6-e404ac5fa602 · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 46

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raw_fallback, observed 2026-08-06T21:03:05.834772Z

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.

source=arxiv_source observed=2026-08-06T21:03:02.864880Z digest=sha256:093ac2517e8eb511393b6089b84789bb120174627a8445d0ce4f9148a65ee6f5

Observation 1b692500-3b07-44f6-be35-25c637913c84 · outbound

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

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 47

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source=arxiv_source observed=2026-08-06T21:03:02.927886Z digest=sha256:8bcca250b300e29fee13cd4e465861fe7a92f49537cbd70b845462e6b29a1ad6

Observation b1fcb948-71e6-4194-a8cc-64e9f8e633ee · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 48

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raw_fallback, observed 2026-08-06T21:03:05.827083Z

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.

source=arxiv_source observed=2026-08-06T21:03:02.986625Z digest=sha256:dce67841e990f96675ab3649b5e0d954b9b1837f4c107feba3e51679fda943e5

Observation 94630df9-446d-492e-a6b0-4e91e9d30551 · outbound

This paper cites Comparing the effectiveness between human-generated videos and ai-generated videos on learning.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Comparing the effectiveness between human-generated videos and ai-generated videos on learning

Reference 49

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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.

source=arxiv_source observed=2026-08-06T21:03:03.095589Z digest=sha256:ee752849177064592844377a8ecacb320ca4d49e58c86eb7c714ad876fa1b19c

Observation ef2d80cd-76fa-422a-bc34-722d45da77ae · outbound

This paper cites an unresolved cited work.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Unresolved cited work

Reference 50

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:03:03.211797Z digest=sha256:60f99ac0fdf0a130c2bdd92acc844562e351921eaab19d48581527882a253c70

Observation 23c7abd2-44bb-4298-a134-8be16ec21e58 · outbound

This paper cites Bovik, H.R.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Bovik, H.R

Reference 51

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source=arxiv_source observed=2026-08-06T21:03:03.274397Z digest=sha256:c5b3c3a50bed39828539904f4658ad2b007ed87de0556cb70094a051acfe4de6

Observation 0a260f00-d68f-45bf-a610-f9dc01f934ab · outbound

This paper cites Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessment.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessment

Reference 52

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source=arxiv_source observed=2026-08-06T21:03:03.344353Z digest=sha256:fb62bcb3db35941e396736e54b6b521351d9ddaa59eb15befa148251cbb13eb5

Observation 30387dab-cdb1-473f-a0c6-fbf29b217873 · outbound

This paper cites Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives

Reference 53

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source=arxiv_source observed=2026-08-06T21:03:03.431138Z digest=sha256:ae914976fa2643d3fea3425f8cc096dad9a2cd34d844da2b6a3f31d8026c68a7

Observation 62cef726-4193-4cd0-a4dc-b2ea19b8a9bb · outbound

This paper cites AIGVE-Tool: AI-Generated Video Evaluation Toolkit with Multifaceted Benchmark.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation AIGVE-Tool: AI-Generated Video Evaluation Toolkit with Multifaceted Benchmark

Reference 54

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local_arxiv, observed 2026-08-06T21:03:04.999468Z

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.

source=arxiv_source observed=2026-08-06T21:03:03.503375Z digest=sha256:d1b5dc7e35c14433631a4e883e98201f262eb4808e7065f63051c0fad70fff49

Observation a96132bb-0367-4a74-963b-d3cb04851e82 · outbound

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

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 55

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:03.636600Z digest=sha256:09bf22a6fb121b4312381f929c836cff2fa67c657c7df406046413a9433e3766

Observation bda0e60a-fb2d-484a-aab5-43dbbdd86e7b · outbound

This paper cites VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Reference 56

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:03.727511Z digest=sha256:f095a3c19e6ec8378f3e6a2ebccc75847766a88eb8d7b63cb88c98a169efc806

Observation 11b1ca19-bb6c-4ff8-b3bf-9e08a21dc877 · outbound

This paper cites Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation

Reference 57

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:03.827609Z digest=sha256:02d2df566de5dc6b789fea628f8d818084195d8a60280b0a885f577df966a5fa

Observation 84ad0ace-64f3-4b31-b656-38abcaa84d36 · outbound

This paper cites Evaluation Agent: Efficient and Promptable Evaluation Framework for Visual Generative Models.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Evaluation Agent: Efficient and Promptable Evaluation Framework for Visual Generative Models

Reference 58

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:03.882209Z digest=sha256:596fc31b5d118496adae5646ce073efe643645a2e2cce8b27e4bb713efe49c77

Observation 3125f75b-ce9b-4841-8632-53cb65914a3b · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation BERTScore: Evaluating Text Generation with BERT

Reference 59

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:04.005794Z digest=sha256:568854b499e8748fb44a89b3c374172dae9a144e99e46eba6888a1f30294e4c0

Observation ea5347c5-f4d5-410c-ade0-014e2a74475c · outbound

This paper cites The Value of AI-Generated Metadata for UGC Platforms: Evidence from a Large-scale Field Experiment.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation The Value of AI-Generated Metadata for UGC Platforms: Evidence from a Large-scale Field Experiment

Reference 60

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no resolver link, observed 2026-08-06T21:03:04.200698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:04.200698Z digest=sha256:8de6017d6479e91427c0d0b0f85b2e54a99fe7d7e4ae824b7da934c5b698ca4d

Observation f98f101b-0ad5-4e3b-9867-9a0a144ccef5 · outbound

This paper cites Towards a Unified Multi-Dimensional Evaluator for Text Generation.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Towards a Unified Multi-Dimensional Evaluator for Text Generation

Reference 61

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no resolver link, observed 2026-08-06T21:03:04.315586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:04.315586Z digest=sha256:9c1e2132ca18417a612ae32f1697da9d18e99bd5910df2785fae29035e54d6e6

Observation 39a54ad9-c5ac-405e-a26a-56a07a7a03cc · outbound

This paper cites Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidance.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidance

Reference 62

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T21:03:04.390983Z digest=sha256:162631ee6d8196e61603addfd1f7ec4a282fbbd6bf985cc63dafededf8283f2a

Observation 373f1e6e-7892-49ad-ae22-daf001775a50 · outbound

This paper cites online" 'onlinestring :=.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation online" 'onlinestring :=

Reference 63

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no resolver link, observed 2026-08-06T21:03:04.519256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:04.519256Z digest=sha256:230179adca43f784f97c8e1c620985b67f17a7c681ce001621c473519204121a

Observation 6e8eb233-f85d-4a00-980a-95e30af07797 · outbound

This paper cites write newline.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation write newline

Reference 64

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source=arxiv_source observed=2026-08-06T21:03:04.659589Z digest=sha256:a7db21c81d882165edf7b332142ced0506dae79afed9b9d497ae64aa6d1cd1d3

Pith citing papers

Observation 89572dfe-b377-4713-9158-53ddd38754ba · inbound

PhyGround: Benchmarking Physical Reasoning in Generative World Models cites this paper.

PhyGround: Benchmarking Physical Reasoning in Generative World Models AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation

Reference 24

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verified exact
arxiv_id, observed 2026-05-12T05:21:28.617378Z

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.

source=pdf_text observed=2026-05-12T05:17:30.010064Z digest=sha256:2f9472ef21417f45c1aae71c398f33a9d8ded246610b6123db33de27233e0fc3