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Paper Citation Record · LEDGER

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model

As of 8 August 2026, this Paper Citation Record lists 100 of 120 outbound references and 0 inbound Pith citation observations for arXiv:2607.16742.

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

pith.paper-citation-record.v1
2607.16742 v1

Coverage vector

measured 100 of 120 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T20:07:51.766473Z

measured 100 of 100 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

100 of 120 outbound references displayed

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Outbound references

Observation 6913f94e-cc42-4c57-9f9a-ebd6f2342038 · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 1

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Observation db2d7b52-7204-43d4-b73b-c2257b3d159c · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Wan: Open and Advanced Large-Scale Video Generative Models

Reference 2

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Observation da9cd4ea-0a95-4435-8e99-d7e00284a9be · outbound

This paper cites MAGI-1: Autoregressive Video Generation at Scale.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model MAGI-1: Autoregressive Video Generation at Scale

Reference 3

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Observation eff9db93-98d0-4cf5-ad12-adf927d58038 · outbound

This paper cites Team, “Sora,” https://openai.com/sora/, 2025.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Team, “Sora,” https://openai.com/sora/, 2025

Reference 4

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Observation 7db36a13-01ce-46ef-acbb-8c44d04cea73 · outbound

This paper cites Pixverse,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Pixverse,

Reference 5

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Observation 121d0b56-b8a8-4ac3-ab94-1637289e9c3c · outbound

This paper cites I, II, III-B, VI.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model I, II, III-B, VI

Reference 6

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Observation 124a0845-e9f6-4277-bbb2-12600de34933 · outbound

This paper cites Openhumanvid: A large-scale high-quality dataset for enhancing human-centric video generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Openhumanvid: A large-scale high-quality dataset for enhancing human-centric video generation,

Reference 7

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Observation d47f81cc-cea3-4ad9-a62b-73d38c8f2d38 · outbound

This paper cites HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding

Reference 8

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Observation b9fa9b14-3f7e-4ff9-8826-25469eb0266d · outbound

This paper cites Singinghead: A large-scale 4d dataset for singing head animation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Singinghead: A large-scale 4d dataset for singing head animation,

Reference 9

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Observation 2d7fea19-71f1-42ed-83bb-051cbfed79c1 · outbound

This paper cites Human-activity agv quality assessment: A benchmark dataset and an objective evaluation metric,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Human-activity agv quality assessment: A benchmark dataset and an objective evaluation metric,

Reference 10

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Observation c5e1c6af-0bc9-4eeb-a378-fb8074604df7 · outbound

This paper cites Hveval: Towards unified evaluation of human-centric video generation and understand- ing,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Hveval: Towards unified evaluation of human-centric video generation and understand- ing,

Reference 11

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Observation 7b045d5c-ee11-49a1-949c-a027abf37e0e · outbound

This paper cites Is this Generated Person Existed in Real-world? Fine-grained Detecting and Calibrating Abnormal Human-body.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Is this Generated Person Existed in Real-world? Fine-grained Detecting and Calibrating Abnormal Human-body

Reference 12

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Observation 05fe4fb3-ca6a-4971-bb00-48004fc0d777 · outbound

This paper cites Improved techniques for training gans,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Improved techniques for training gans,

Reference 13

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Observation 4b6e176b-a41c-4d4e-ac7d-c8bed74dab28 · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 14

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Observation c7fbea01-07a6-4062-ad2a-2fa40565143c · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 15

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Observation 67353350-c58d-4e35-8c78-9b5f0e3d2dc3 · outbound

This paper cites Vbench: Comprehensive benchmark suite for video generative models,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Vbench: Comprehensive benchmark suite for video generative models,

Reference 16

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Observation 49755b21-b2a4-403e-940a-a0a36eda2e28 · outbound

This paper cites VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

Reference 17

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source=pdf_text observed=2026-08-01T20:07:42.360182Z digest=sha256:dd81543288fd00151a23cf686c94987da838c25f36e3bd583d9f5dd7ed3c9ec4

Observation 2a76ccff-3e84-469b-ac40-77cb35f8d457 · outbound

This paper cites T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation

Reference 18

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Observation c69b63ca-d484-4655-b8f6-989930d81051 · outbound

This paper cites Subjective-aligned dataset and metric for text-to-video quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Subjective-aligned dataset and metric for text-to-video quality assessment,

Reference 19

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Observation c46b2bba-f5ae-4eb7-bf41-b43d8f6aff0e · outbound

This paper cites Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model

Reference 20

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Observation d635b28d-20fd-4bb8-97ad-b90732fa605f · outbound

This paper cites Aigv-assessor: benchmarking and evaluating the perceptual quality of text-to-video generation with lmm,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Aigv-assessor: benchmarking and evaluating the perceptual quality of text-to-video generation with lmm,

Reference 21

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Observation d4416fad-852e-40fc-b175-4c586efe37da · outbound

This paper cites Evalcrafter: Benchmarking and evaluating large video generation models,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Evalcrafter: Benchmarking and evaluating large video generation models,

Reference 22

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Observation 80e0f8db-78f2-4e1c-afec-c1be2f766408 · outbound

This paper cites Fetv: A benchmark for fine-grained evaluation of open-domain text-to- video generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Fetv: A benchmark for fine-grained evaluation of open-domain text-to- video generation,

Reference 23

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Observation e29d969f-7e50-4c15-867b-3fcb57aee99b · outbound

This paper cites Evaluating and improving compositional text-to-visual generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Evaluating and improving compositional text-to-visual generation,

Reference 24

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source=pdf_text observed=2026-08-01T20:07:43.338652Z digest=sha256:4896c4ba7dbfd6803ede0f0fcad8ffa810da9137d2583882cfdc6c7594d0746f

Observation a34fc10b-835d-43a7-8461-aaabaf1773ab · outbound

This paper cites F-bench: Rethinking human preference evaluation metrics for benchmarking face generation, customization, and restoration,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model F-bench: Rethinking human preference evaluation metrics for benchmarking face generation, customization, and restoration,

Reference 25

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Observation 6fd5be7f-55bd-4d85-a880-1192da18e7c9 · outbound

This paper cites Multi- dimensional text-to-face image quality assessment using llm: Database and method,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Multi- dimensional text-to-face image quality assessment using llm: Database and method,

Reference 26

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Observation d4c9ef6c-175f-4292-aab7-8cf6ae755bc2 · outbound

This paper cites Aghi-qa: A subjective-aligned dataset and metric for ai- generated human images,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Aghi-qa: A subjective-aligned dataset and metric for ai- generated human images,

Reference 27

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Observation 410ad504-2ca2-450a-badf-f170fdf88de5 · outbound

This paper cites DreamBench++: A Human-Aligned Benchmark for Personalized Image Generation.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model DreamBench++: A Human-Aligned Benchmark for Personalized Image Generation

Reference 28

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Observation 89909fa7-d27b-4efd-8e9d-c15c492f1342 · outbound

This paper cites Chatgpt-4o,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Chatgpt-4o,

Reference 29

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Observation ac266fc1-5846-4747-9c9d-b757e6d53171 · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model AnimateDiff-Lightning: Cross-Model Diffusion Distillation

Reference 30

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Observation 33668e07-dc6a-4f66-8cb2-187688634869 · outbound

This paper cites Animatelcm: Computation-efficient personalized style video generation without personalized video data,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Animatelcm: Computation-efficient personalized style video generation without personalized video data,

Reference 31

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Observation 209db5c1-0a16-47af-9159-a2d228aa5b7a · outbound

This paper cites Magictime: Time-lapse video generation models as metamorphic simulators,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Magictime: Time-lapse video generation models as metamorphic simulators,

Reference 32

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Observation 0a7f2ce3-9112-427c-8e33-719f98abfeeb · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model ModelScope Text-to-Video Technical Report

Reference 33

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Observation 4cbf430d-1329-48e0-adc9-e1d54b2cffd8 · outbound

This paper cites Show-1: Marrying pixel and latent diffusion models for text-to-video generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Show-1: Marrying pixel and latent diffusion models for text-to-video generation,

Reference 34

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Observation b55e2fbd-faa7-443a-b3cf-aee1cf842015 · outbound

This paper cites T2v-turbo-v2: Enhancing video generation model post-training through data, reward, and conditional guidance design,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model T2v-turbo-v2: Enhancing video generation model post-training through data, reward, and conditional guidance design,

Reference 35

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source=pdf_text observed=2026-08-01T20:07:44.084673Z digest=sha256:f86a847130120dede9c8e3d253a3e778ce4e6741726859d0bbbd1d90ad97b871

Observation 7e2b4fcf-9bc6-433f-a0c2-3a41c1e11dbf · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Videocrafter2: Overcoming data limitations for high-quality video diffusion models,

Reference 36

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Observation c1d0153f-83e1-4e29-a4a4-9ba26f433cb6 · outbound

This paper cites Zeroscope,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Zeroscope,

Reference 37

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Observation dbc6229f-a4e2-408f-9716-e5f5cbb8dd87 · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 38

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Observation 1da898d9-ed78-44a9-9493-32ae5fb29ce9 · outbound

This paper cites LTX-Video: Realtime Video Latent Diffusion.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model LTX-Video: Realtime Video Latent Diffusion

Reference 39

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Observation 0778bbfd-74b0-4a4e-9415-a7989816067d · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Latte: Latent Diffusion Transformer for Video Generation

Reference 40

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source=pdf_text observed=2026-08-01T20:07:44.413824Z digest=sha256:21df54d48634130be8ed51ffedefd6c0aa59849b1defaca67121325900210971

Observation 377abb5b-dc37-4e3c-acf3-546a995b061c · outbound

This paper cites Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model

Reference 41

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source=pdf_text observed=2026-08-01T20:07:44.492273Z digest=sha256:48368afc08fc6bd11bcdf91bfbf0a07edff58100a3e0a425d117817e9271d795

Observation 15d28b0d-dd6c-4cbb-b4f6-220b2e94587b · outbound

This paper cites Mochi 1,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Mochi 1,

Reference 42

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source=pdf_text observed=2026-08-01T20:07:44.556844Z digest=sha256:75c59d52743ea72698ce43aad504c55ad06fed76287eca826d7efe88e437ae85

Observation 337113b9-1194-460a-b059-bcced000c07f · outbound

This paper cites SkyReels-V2: Infinite-length Film Generative Model.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model SkyReels-V2: Infinite-length Film Generative Model

Reference 43

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source=pdf_text observed=2026-08-01T20:07:44.655356Z digest=sha256:47f10ba7a9de0dc34e2a4a5adec4ea2cd9a7be1cda0ca735d658f4959e551435

Observation 0aca61c8-4211-4c88-9b87-fcc5766588d1 · outbound

This paper cites Cofnet: contrastive object-aware fusion using box-level masks for multispectral object detection,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Cofnet: contrastive object-aware fusion using box-level masks for multispectral object detection,

Reference 44

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source=pdf_text observed=2026-08-01T20:07:44.791196Z digest=sha256:e86cae78ffc56978fb2f5828c82f7cc4bad9beea8f6b938898b72a92d43611a8

Observation b11b7509-e703-4c65-8777-daf7362c9530 · outbound

This paper cites Afes: Attention-based feature excitation and sorting for action recognition,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Afes: Attention-based feature excitation and sorting for action recognition,

Reference 45

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source=pdf_text observed=2026-08-01T20:07:44.905458Z digest=sha256:fb060db87bb968e85a7deedc1f3dcdd84321481ae947775e34ac3a3fc3e90684

Observation 2f7a453f-a23e-4f88-aed6-b42695e21b20 · outbound

This paper cites An end-to-end blind image quality assessment method using a recurrent network and self-attention,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model An end-to-end blind image quality assessment method using a recurrent network and self-attention,

Reference 46

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source=pdf_text observed=2026-08-01T20:07:44.959358Z digest=sha256:638e66fa79115272d8930805b9ac29db05dc7d2007734a24b3a26c9270a96683

Observation e4309af7-1e14-49fa-abed-6c4cd6aa2c35 · outbound

This paper cites Attentional feature fusion for end-to-end blind image quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Attentional feature fusion for end-to-end blind image quality assessment,

Reference 47

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source=pdf_text observed=2026-08-01T20:07:45.032742Z digest=sha256:c6731c8ea2f0fdb649d22cdfa0897da480ccc37616230ccb9a6cb7a98665a69e

Observation 0bdda225-a928-4174-a6f4-48662cc51a40 · outbound

This paper cites Multilevel feature fusion for end-to-end blind image quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Multilevel feature fusion for end-to-end blind image quality assessment,

Reference 48

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source=pdf_text observed=2026-08-01T20:07:45.083371Z digest=sha256:29d35f6d793fab92a57807e28fc8555501551982591ac94aeefe1bd3bc6e4e4e

Observation f8d1a3d9-6c82-4519-bedc-20c48601248a · outbound

This paper cites Blind image quality assessment based on perceptual comparison,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Blind image quality assessment based on perceptual comparison,

Reference 49

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source=pdf_text observed=2026-08-01T20:07:45.219678Z digest=sha256:de840b2262de6d66776f4ec222f4793dfe2c7654cde5f9297602ff8d54eda623

Observation a122fc58-a548-4086-98d7-411ac872b101 · outbound

This paper cites Graph-represented distribution similarity index for full-reference image quality assess- ment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Graph-represented distribution similarity index for full-reference image quality assess- ment,

Reference 50

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source=pdf_text observed=2026-08-01T20:07:45.354310Z digest=sha256:af75c5763fc2898f8257cde290ca661e169997075ecc903a0bb2985173ede22e

Observation 6ba4ec52-15dd-469b-ad5b-820de183e68a · outbound

This paper cites Bridging the synthetic-to-authentic gap: Distortion-guided unsupervised domain adaptation for blind image quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Bridging the synthetic-to-authentic gap: Distortion-guided unsupervised domain adaptation for blind image quality assessment,

Reference 51

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source=pdf_text observed=2026-08-01T20:07:45.431594Z digest=sha256:e29c2c4eb20fcbe2f2b7e2fd953b659224a7c2a9ad71a4cffbfa0d4404988a53

Observation f50bba8c-f557-4ea0-b354-07dc1f2a5ee3 · outbound

This paper cites Blind image quality assessment: Exploring content fidelity perceptibility via quality adversarial learning,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Blind image quality assessment: Exploring content fidelity perceptibility via quality adversarial learning,

Reference 52

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source=pdf_text observed=2026-08-01T20:07:45.555280Z digest=sha256:13c1eff7e76fb8e50b0ecfd37eb83e29eb080624f64ef707a9bcb7bdaa1767c5

Observation 93d17d93-22fa-471f-8658-59250e0246e6 · outbound

This paper cites Image quality assessment: Investigating causal perceptual effects with abductive counterfactual inference,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Image quality assessment: Investigating causal perceptual effects with abductive counterfactual inference,

Reference 53

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source=pdf_text observed=2026-08-01T20:07:45.684998Z digest=sha256:f399643c81c6e34e2901b96361871941902d0c50817872e59f5da0789b06db61

Observation cb65c0c8-b4cd-4464-8d54-f841f7b82b40 · outbound

This paper cites No-reference image quality assessment: Exploring intrinsic distortion characteristics via generative noise estimation with mamba,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model No-reference image quality assessment: Exploring intrinsic distortion characteristics via generative noise estimation with mamba,

Reference 54

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source=pdf_text observed=2026-08-01T20:07:45.821908Z digest=sha256:1be5b6569faf0e0fd1798ee83ce06fdc582a730c7e9908ab0fc4f72ac2ae1d5c

Observation ba6091cb-b598-450c-91d8-5474ad673829 · outbound

This paper cites Towards syn-to-real iqa: A novel perspective on reshaping synthetic data distributions,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Towards syn-to-real iqa: A novel perspective on reshaping synthetic data distributions,

Reference 55

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source=pdf_text observed=2026-08-01T20:07:45.962261Z digest=sha256:c54edb93def6ee8532ffe616049821f78ba7807067e322ab312261a32ebf42f4

Observation 0f7e6c68-7abf-4a54-8d4d-d48ac2cac99a · outbound

This paper cites Uni-iqa: A unified approach for mutual promotion of natural and screen content image quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Uni-iqa: A unified approach for mutual promotion of natural and screen content image quality assessment,

Reference 56

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source=pdf_text observed=2026-08-01T20:07:46.089593Z digest=sha256:9f308b28cb14b8a8977d8d6f1e00b3cdda2586fe683b32b34c985d4caddc3dbf

Observation c9d37514-f0e5-48ea-88f6-ad327f5a4791 · outbound

This paper cites Beyond pixels: text-guided deep insights into graphic design image aesthetics,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Beyond pixels: text-guided deep insights into graphic design image aesthetics,

Reference 57

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source=pdf_text observed=2026-08-01T20:07:46.277249Z digest=sha256:60a277317abe7d750eeac16c832cd68dd8b734970635517ac1c019f70f98b186

Observation 68d87028-8249-4130-afaa-5bc505c0eddb · outbound

This paper cites A deep learning based no- reference quality assessment model for ugc videos,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model A deep learning based no- reference quality assessment model for ugc videos,

Reference 58

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source=pdf_text observed=2026-08-01T20:07:46.412737Z digest=sha256:84ccaed014040957943395a5acf235ef62e521552ea97aa9384d4db6daa2e0ad

Observation 1f51d02e-2cb1-48f1-8fa7-6de7f7a45f9a · outbound

This paper cites Analysis of video quality datasets via design of minimalistic video quality models,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Analysis of video quality datasets via design of minimalistic video quality models,

Reference 59

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source=pdf_text observed=2026-08-01T20:07:46.609547Z digest=sha256:75149029522d897867ec7308c56e4c2b740081fb637c0e7a572f3fc082fa1408

Observation 103ef23e-55bc-4ed5-b516-103dbac657be · outbound

This paper cites Fast-vqa: Efficient end-to-end video quality assessment with fragment sampling,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Fast-vqa: Efficient end-to-end video quality assessment with fragment sampling,

Reference 60

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source=pdf_text observed=2026-08-01T20:07:46.747952Z digest=sha256:7b7012648502a4c5dd82e419d41693ef35e85cfe953525c04ce1a36043f53595

Observation 61cb87fd-c174-43c5-b5cd-ce1b8ec5ac38 · outbound

This paper cites Dynamic expert- knowledge ensemble for generalizable video quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Dynamic expert- knowledge ensemble for generalizable video quality assessment,

Reference 61

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source=pdf_text observed=2026-08-01T20:07:46.905602Z digest=sha256:da0b23d3c831d6ca89b8dbb657cfd8eb677f1983209f3bdaaa54ecc4c21c6e3d

Observation 1cff413d-2296-4f63-9626-842bc1abf5be · outbound

This paper cites Exploring video quality assessment on user generated contents from aesthetic and technical perspectives,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Exploring video quality assessment on user generated contents from aesthetic and technical perspectives,

Reference 62

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source=pdf_text observed=2026-08-01T20:07:47.056630Z digest=sha256:352288280dcea901c757a7eec13a196d9b6397dd09feb978c4110094d7c4122b

Observation 30338aed-d3e4-4875-bef8-c148556d2bbb · outbound

This paper cites Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

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source=pdf_text observed=2026-08-01T20:07:47.248839Z digest=sha256:e0b15bbda6ecdb81245af4bd69ed79fed03bbb48311a9ead7a5f7d3a8d8e3486

Observation 49227d85-476f-47bd-80f6-7ee07af442cb · outbound

This paper cites Kvq: Kwai video quality assessment for short-form videos,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Kvq: Kwai video quality assessment for short-form videos,

Reference 64

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source=pdf_text observed=2026-08-01T20:07:47.447240Z digest=sha256:4c0276b6f19ddc7571f33fb494f9d4432ad5ec4d448a4accd306701a7e293fdf

Observation d39b3937-810d-4121-b096-97048c8f39a8 · outbound

This paper cites Scaling and masking: A new paradigm of data sampling for image and video quality assess- ment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Scaling and masking: A new paradigm of data sampling for image and video quality assess- ment,

Reference 65

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source=pdf_text observed=2026-08-01T20:07:47.615618Z digest=sha256:e13db310b31fbd97c61155deffcac38280336d25c8cc8a93e94202b05d873d3a

Observation 85737e07-2040-46c2-86ec-ff427df5a447 · outbound

This paper cites Video quality assessment for online processing: From spatial to temporal sampling,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Video quality assessment for online processing: From spatial to temporal sampling,

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source=pdf_text observed=2026-08-01T20:07:47.820145Z digest=sha256:119bb6613cfd05f5d08c1f39075a805b45b27141fe9cb8152f5c4a9162ce4784

Observation b9bfa9d2-694d-4130-9fc5-47a4b131fa6d · outbound

This paper cites Pea265: Perceptual assessment of video compression artifacts,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Pea265: Perceptual assessment of video compression artifacts,

Reference 67

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source=pdf_text observed=2026-08-01T20:07:47.921016Z digest=sha256:d5096619c2047de59fe32cdc5f2eae163fd7b0711f8d4ab7c1c8f44cc594bef1

Observation 9261cc25-7432-4c29-8877-9f35c53234d2 · outbound

This paper cites Patch- vq:’patching up’the video quality problem,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Patch- vq:’patching up’the video quality problem,

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source=pdf_text observed=2026-08-01T20:07:48.096049Z digest=sha256:6752fa5e692a714e63b9036d31e1a6a2adfeae016d68c1ff46b35b88fb25f1d8

Observation a106f764-035a-48f8-b2b2-453d4711a0c4 · outbound

This paper cites Fvq: A large-scale dataset and an lmm-based method for face video quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Fvq: A large-scale dataset and an lmm-based method for face video quality assessment,

Reference 69

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source=pdf_text observed=2026-08-01T20:07:48.222527Z digest=sha256:4fd8f694a31663b603a84b6b3ddcd897e6bfa9a7713f2c8317f7969cf1ffe20a

Observation 52da6e1f-bcd7-4864-9d4a-3c7bd70dad3f · outbound

This paper cites Rgc-vqa: An exploration database for robotic-generated video quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Rgc-vqa: An exploration database for robotic-generated video quality assessment,

Reference 70

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source=pdf_text observed=2026-08-01T20:07:48.345475Z digest=sha256:fd5d062d7c4b0974edd5d55fd0f8beac88bae807b9217243719ab481a9d39885

Observation 4ec6cbd0-de00-467f-a8eb-bc7f874599a5 · outbound

This paper cites Ges-qa: A multidimensional quality assessment dataset for audio-to-3d gesture generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Ges-qa: A multidimensional quality assessment dataset for audio-to-3d gesture generation,

Reference 71

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source=pdf_text observed=2026-08-01T20:07:48.453488Z digest=sha256:7b0dcae612a0bd66d749b178b29dddf06bdb23404878cdf327c553b31f87484a

Observation c039bd1e-2256-4e75-928f-6cb72552edd5 · outbound

This paper cites Sfqa: A comprehensive perceptual quality assessment dataset for singing face generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Sfqa: A comprehensive perceptual quality assessment dataset for singing face generation,

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source=pdf_text observed=2026-08-01T20:07:48.543125Z digest=sha256:ede1de81e1009cd739d2a31ead26dee10739f0cec52ff6674a963f8a4853568c

Observation ec0c0be6-4c34-4dc5-9508-a472bf6a7cd6 · outbound

This paper cites Two-level approach for no-reference consumer video quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Two-level approach for no-reference consumer video quality assessment,

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source=pdf_text observed=2026-08-01T20:07:48.648978Z digest=sha256:5b3b90e1cce8cb8d7828f896085713274fad37e6cb9cd01660ceb9dcf152a252

Observation 78e0828e-2c51-4a67-b531-1c0e78087587 · outbound

This paper cites Rapique: Rapid and accurate video quality prediction of user generated content,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Rapique: Rapid and accurate video quality prediction of user generated content,

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source=pdf_text observed=2026-08-01T20:07:48.812989Z digest=sha256:964f2f7402c5a3faebae08c24b390b711869213a01c5e7d47bd32a985a7e2c37

Observation 3de8e223-7ffd-4092-87cf-e3edefe64313 · outbound

This paper cites Ugc- vqa: Benchmarking blind video quality assessment for user generated content,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Ugc- vqa: Benchmarking blind video quality assessment for user generated content,

Reference 75

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source=pdf_text observed=2026-08-01T20:07:48.962214Z digest=sha256:5bbbeee151ce6d0edc7492c6a4b0f7319c542e03d521423a5b623ba1ed5b9fe6

Observation 93c809e0-d9ef-46aa-938f-31b964c57676 · outbound

This paper cites Learning gen- eralized spatial-temporal deep feature representation for no-reference video quality assessment,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Learning gen- eralized spatial-temporal deep feature representation for no-reference video quality assessment,

Reference 76

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source=pdf_text observed=2026-08-01T20:07:49.032237Z digest=sha256:b1c9c265c47fcb2fa9830dcd4686adc29192c06d61515060ecb5bd36868d14ca

Observation a133ff7d-0df7-45ac-a2e2-243cb9dfd632 · outbound

This paper cites An end-to-end no-reference video quality assessment method with hierarchical spatiotemporal feature representation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model An end-to-end no-reference video quality assessment method with hierarchical spatiotemporal feature representation,

Reference 77

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source=pdf_text observed=2026-08-01T20:07:49.108540Z digest=sha256:a28012eb26df492c85faa34b2ba61dbccdb5adbdbcaad04235024dbf4d1515c7

Observation c77370c0-6e31-4cd5-819f-d099b97a535e · outbound

This paper cites Blind quality assessment of wide-angle videos based on deformation representation learning and multi-dimensional feature fusion,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Blind quality assessment of wide-angle videos based on deformation representation learning and multi-dimensional feature fusion,

Reference 78

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source=pdf_text observed=2026-08-01T20:07:49.194274Z digest=sha256:d8dc8e48d8521e49ec90ee6a9b8ea5726f3c72a5b1bc8a3f487d8ece686e3c03

Observation 5b227162-f6c5-44f2-a4d4-caa5a14446b9 · outbound

This paper cites Mi3s: a multimodal large language model assisted quality assessment framework for ai-generated talking heads,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Mi3s: a multimodal large language model assisted quality assessment framework for ai-generated talking heads,

Reference 79

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source=pdf_text observed=2026-08-01T20:07:49.256502Z digest=sha256:230f30ec9c22b8f3f1e39e5539f72afae76266684bab90eae91f70c9e8d1ad15

Observation 6d0d55de-35b4-41e2-9093-212dbffc86bf · outbound

This paper cites Objective quality assessment of ai- generated content videos with transformation consistency focus,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Objective quality assessment of ai- generated content videos with transformation consistency focus,

Reference 80

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source=pdf_text observed=2026-08-01T20:07:49.309647Z digest=sha256:04f6e8fd7c7ae0ca7791194d257c6f01b5cdd7a583c026eeef0595fcf24fc363

Observation 61a6baf0-9091-4c4f-8110-e29948e6e25a · outbound

This paper cites Dreamina,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Dreamina,

Reference 81

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source=pdf_text observed=2026-08-01T20:07:49.446299Z digest=sha256:2727ef5966ec03098411f7fbeb1cd7ef3a98c1165536b0e12354ffffefde2abb

Observation d4b66ca6-62c2-45ab-b3ed-1c9c75eea3ad · outbound

This paper cites Introducing gen-3 alpha: A new frontier for video gener- ation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Introducing gen-3 alpha: A new frontier for video gener- ation,

Reference 82

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source=pdf_text observed=2026-08-01T20:07:49.597533Z digest=sha256:02a972acf6ee31c5e1e7d512314401e669d99f1b2af80d90cfd6068de30a576c

Observation 206ffdf0-4da1-4946-a6fa-9ed6d4157012 · outbound

This paper cites II, III-B, VI.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model II, III-B, VI

Reference 83

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source=pdf_text observed=2026-08-01T20:07:49.794012Z digest=sha256:987920d85db05c5e0d51ab7f978b878608cd49f9e40f7256d1aed8b439d30be0

Observation 23021419-52aa-4251-a426-f44830f38abd · outbound

This paper cites Methodology for the subjective assessment of the quality of television pictures,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Methodology for the subjective assessment of the quality of television pictures,

Reference 84

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source=pdf_text observed=2026-08-01T20:07:49.947471Z digest=sha256:737469775a721d221adf966a26d7e626ea8951db4d0ff4105a7b12f142749490

Observation bec5484e-1e95-464c-ad2a-12d872c8c3e7 · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 85

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source=pdf_text observed=2026-08-01T20:07:50.079288Z digest=sha256:d623daf2ee8d9c3fb02bc1e226d4d51b776c3c47396cdd9f4cf37217a067ee9b

Observation 369bf5bd-c1fa-46d7-9af6-0b811b993fce · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 86

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source=pdf_text observed=2026-08-01T20:07:50.260800Z digest=sha256:b422e6f3108002f52cc0a54c4d7b50ed3a75746bcc5e6e89946b78674ced037c

Observation 1f50e640-dfdb-41a6-a1d0-526c9955a797 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Laion-5b: An open large-scale dataset for training next generation image-text models,

Reference 87

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source=pdf_text observed=2026-08-01T20:07:50.419203Z digest=sha256:ac64d07b0e1b5cb76c10f0422efbe2e4c71bde30cad1cd09995258b2c451715d

Observation b9ce64c7-7fd5-4011-9ab6-b6f1ca8e012f · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image gen- eration,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Pick-a-pic: An open dataset of user preferences for text-to-image gen- eration,

Reference 88

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source=pdf_text observed=2026-08-01T20:07:50.547295Z digest=sha256:34933374c0a374ce90a9e5a2707a46f354cae35026b50679af3ca02dae0038e8

Observation 81a2f375-c0eb-44b8-baa3-88a1281911fe · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text- to-image generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Imagereward: Learning and evaluating human preferences for text- to-image generation,

Reference 89

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source=pdf_text observed=2026-08-01T20:07:50.671684Z digest=sha256:787bbbd5676b1d058c253778c1b34d71d40bdca8550e5cbbe6d1059a6eddf5e8

Observation 28d58e01-229b-4106-b31b-1f9540f241d8 · outbound

This paper cites Evaluating text-to-visual generation with image-to-text generation,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Evaluating text-to-visual generation with image-to-text generation,

Reference 90

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source=pdf_text observed=2026-08-01T20:07:50.851257Z digest=sha256:3c67aac13f61a406b9f41b8fcd324c2c6f219923e4cbdac283c4fbf755f67a2c

Observation f84a5fc0-ad7a-43eb-bb32-e6fd1f3188fa · outbound

This paper cites Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 91

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source=pdf_text observed=2026-08-01T20:07:50.972763Z digest=sha256:9c0db3d3f7c1c8084b58182de9510e501a5268e893b4f49ae007a860551b733e

Observation c6317215-f3ab-48cf-9e5c-118936021b88 · outbound

This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 92

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source=pdf_text observed=2026-08-01T20:07:51.084614Z digest=sha256:b37fd3d71d1ddd9fd4b9d9197366b6e9375c01497860000e17a0b1af7c302fd1

Observation 8940fffe-875c-4155-86a4-586e305c2ee9 · outbound

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

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Reference 93

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source=pdf_text observed=2026-08-01T20:07:51.198128Z digest=sha256:5a033b9958f9e8124d0e21e0f8932a8ef9feb35d72e8be99895e10e3905da6ee

Observation 685218fd-ecf4-40bd-beec-536d1668f342 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 94

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source=pdf_text observed=2026-08-01T20:07:51.347110Z digest=sha256:ca0461aa0e8f90f4bacf95d3898e926367903dce54a32a6964ef2dbff80e68a5

Observation 0f3eda30-4d57-405b-8737-7e80c191224c · outbound

This paper cites Qwen2.5-VL Technical Report.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Qwen2.5-VL Technical Report

Reference 95

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source=pdf_text observed=2026-08-01T20:07:51.421243Z digest=sha256:0530c43758cb860e716863138495e1a0a140d5d497dafc4bc5d9f3e9672239be

Observation a5883d84-8488-4de6-bf6c-317ec05b201c · outbound

This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model DeepSeek-VL: Towards Real-World Vision-Language Understanding

Reference 96

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source=pdf_text observed=2026-08-01T20:07:51.470448Z digest=sha256:f826182bc797bd4a74f8104c77d1018c2eec9bd66478830b3637801f31890b11

Observation ead9baf6-4b65-48fc-b262-5b959053ea0a · outbound

This paper cites UI-TARS: Pioneering Automated GUI Interaction with Native Agents.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model UI-TARS: Pioneering Automated GUI Interaction with Native Agents

Reference 97

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source=pdf_text observed=2026-08-01T20:07:51.537525Z digest=sha256:b185bf5f686be7225f5adea5c716f6fcf8c0c193631d19bf63bca79d4a8b12e7

Observation 831ada82-5b4c-4b57-83b2-7c19ff2fa2f3 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 98

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source=pdf_text observed=2026-08-01T20:07:51.608279Z digest=sha256:705d35588837379e75732c6dd3bd7b193cd114abd940cbcc7ae3b6933984654b

Observation 459f84df-c024-4e13-9429-31c9e3716f2f · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 99

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source=pdf_text observed=2026-08-01T20:07:51.654949Z digest=sha256:a49acacbbd3157cd6b9a58d218c56c1a1b380bdaa040dc9e6e636e6aeb167c6b

Observation 0a688b26-52a6-4e87-b244-1ca2913263d1 · outbound

This paper cites Cogagent: A visual language model for gui agents,.

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model Cogagent: A visual language model for gui agents,

Reference 100

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source=pdf_text observed=2026-08-01T20:07:51.766473Z digest=sha256:e5de0f09fffbcb7166f942a616dd2f1c57b9ced833a6593a5a52d4814794bd63

Pith citing papers

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