Paper Citation Record · LEDGER

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment

As of 21 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2506.09795.

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

pith.paper-citation-record.v1
2506.09795 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:44:35.957397Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:44:32.834619Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:44:36.881065Z

Reference resolution

33 of 33 outbound references displayed

verified exact1
verified fuzzy26
unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 386a9657-825b-4ff5-997c-792e1f59a80d · outbound

This paper cites Ensuring a consistent and satisfactory user experience requires accurate and scalable Video Qual- ity Assessment (VQA) models in such heterogeneous envi- ronments.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Ensuring a consistent and satisfactory user experience requires accurate and scalable Video Qual- ity Assessment (VQA) models in such heterogeneous envi- ronments

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:43.600355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2b165956-61b5-49aa-b76b-51df1c1375ea · outbound

This paper cites Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment

Reference 2

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Observation 9888ee56-c0e8-4980-affc-a75f635dfc52 · outbound

This paper cites an unresolved cited work.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:44:43.390995Z

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Observation 932508cf-3498-4a9a-9da5-a30bb96b877a · outbound

This paper cites Dataset The Image and Video Engineering (LIVE) lab at the Univer- sity of Texas at Austin (sponsored by Amazon Prime Video) created the dataset provided for this challenge.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Dataset The Image and Video Engineering (LIVE) lab at the Univer- sity of Texas at Austin (sponsored by Amazon Prime Video) created the dataset provided for this challenge

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:43.167553Z

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Observation 85ea9da4-f49d-4864-aa06-692eb45b9323 · outbound

This paper cites The proposed method fuses handcrafted low-level complexity fea- tures extracted via VCA with structural quality cues obtained from SSIM statistics.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment The proposed method fuses handcrafted low-level complexity fea- tures extracted via VCA with structural quality cues obtained from SSIM statistics

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:42.921476Z

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Observation 98c6bb39-38f5-4e4f-991a-8794c77301a1 · outbound

This paper cites Cisco visual networking index: Forecast and methodology, 2017–2022 (White Paper),.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Cisco visual networking index: Forecast and methodology, 2017–2022 (White Paper),

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:42.676946Z

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Observation 212fd414-40af-464f-9780-40a5ed6a7606 · outbound

This paper cites Transcoding Quality Prediction for Adaptive Video Streaming,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Transcoding Quality Prediction for Adaptive Video Streaming,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:42.499806Z

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Observation 1b8c5bb6-43cf-46d8-8b27-73244bc01487 · outbound

This paper cites On the Computation of PSNR for a Set of Images or Video,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment On the Computation of PSNR for a Set of Images or Video,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:42.240519Z

Source-reported events for the cited work

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Observation 52237d6a-fd22-43a6-ac48-10e907ca506a · outbound

This paper cites Image Quality Metrics: PSNR vs. SSIM,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Image Quality Metrics: PSNR vs. SSIM,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:42.009435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8b2214ef-b23b-4fe7-ba28-4c6bcc8dc829 · outbound

This paper cites Visual quality assessment: recent devel- opments, coding applications and future trends,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Visual quality assessment: recent devel- opments, coding applications and future trends,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:41.705565Z

Source-reported events for the cited work

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Observation dfbe078b-ab40-4f27-b1cc-c4145297a522 · outbound

This paper cites Quality-Aware Dynamic Resolu- tion Adaptation Framework for Adaptive Video Stream- ing,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Quality-Aware Dynamic Resolu- tion Adaptation Framework for Adaptive Video Stream- ing,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:41.509689Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4bbb805c-0012-406a-9eea-f065ddfcfee9 · outbound

This paper cites Green Video Complexity Analysis for Efficient Encoding in Adaptive Video Streaming,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Green Video Complexity Analysis for Efficient Encoding in Adaptive Video Streaming,

Reference 12

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Observation ae01dd83-4d69-43be-a45e-81eb85a30ad9 · outbound

This paper cites XGBoost: A Scalable Tree Boosting System,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment XGBoost: A Scalable Tree Boosting System,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:41.280554Z

Source-reported events for the cited work

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Observation 85343f72-a5a7-4b55-9a87-d218e9c5b072 · outbound

This paper cites Perceptual visual quality metrics: A survey,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Perceptual visual quality metrics: A survey,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:41.070694Z

Source-reported events for the cited work

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Observation f2909341-bb6c-43ad-9e72-b2a9c9fe2acf · outbound

This paper cites FUNQUE: Fusion of Unified Quality Evaluators,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment FUNQUE: Fusion of Unified Quality Evaluators,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:39.276998Z

Source-reported events for the cited work

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Observation 8852755d-8e70-4545-bf4c-a02d38979db2 · outbound

This paper cites Encoder-Quantization-Motion-based Video Quality Metrics,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Encoder-Quantization-Motion-based Video Quality Metrics,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:40.561066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b100ae16-3bdd-44ef-a322-4c392c494361 · outbound

This paper cites Fourier Transform-Based Scalable Image Quality Measure,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Fourier Transform-Based Scalable Image Quality Measure,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:40.306431Z

Source-reported events for the cited work

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Observation 9b2f079a-c7af-4c9e-9cd8-888093c5e7ca · outbound

This paper cites Modern Image Quality Assessment,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Modern Image Quality Assessment,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:40.037832Z

Source-reported events for the cited work

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Observation 87807c2f-4bfc-4720-b5e0-ee35b2da3b0e · outbound

This paper cites Reduce-reference image quality assessment using a wavelet-domain natural im- age statistic model,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Reduce-reference image quality assessment using a wavelet-domain natural im- age statistic model,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:39.776349Z

Source-reported events for the cited work

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Observation fff71b63-af32-4240-8607-b7bd3c907c3d · outbound

This paper cites Bitstream-Based Model Standard for 4K/UHD: ITU-T P.1204.3 — Model Details, Evalu- ation, Analysis and Open Source Implementation,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Bitstream-Based Model Standard for 4K/UHD: ITU-T P.1204.3 — Model Details, Evalu- ation, Analysis and Open Source Implementation,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a0ff8592-3578-4e90-a176-beab54e25deb · outbound

This paper cites Image information and vi- sual quality,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Image information and vi- sual quality,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:38.047380Z

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Observation 1c79e051-ce3e-419e-856f-acc2da6e58b0 · outbound

This paper cites HDRSDR-VQA: A Subjective Video Quality Dataset for HDR and SDR Comparative Evaluation.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment HDRSDR-VQA: A Subjective Video Quality Dataset for HDR and SDR Comparative Evaluation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T04:44:35.440620Z

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Observation bf5247b0-0278-4641-9e4c-ad5eb7d14085 · outbound

This paper cites The Konstanz natural video database (KoNViD-1k),.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment The Konstanz natural video database (KoNViD-1k),

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:38.747765Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2d72273c-4789-492f-87ed-f296790e0039 · outbound

This paper cites YouTube UGC Dataset for Video Compression Research,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment YouTube UGC Dataset for Video Compression Research,

Reference 24

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Source-reported events for the cited work

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Observation a6895959-b9f3-4267-a62c-2a566482a96d · outbound

This paper cites Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:38.542438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eda6f6b2-1243-4912-9093-ed3419be024c · outbound

This paper cites JND-aware Two-pass Per- title Encoding Scheme for Adaptive Live Streaming,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment JND-aware Two-pass Per- title Encoding Scheme for Adaptive Live Streaming,

Reference 26

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T04:44:36.402956Z

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Observation ef050d8f-7e65-4ae7-82da-2cd803b8656b · outbound

This paper cites No- reference image quality assessment in the spatial do- main,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment No- reference image quality assessment in the spatial do- main,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:38.267356Z

Source-reported events for the cited work

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Observation 9e5ee664-8fb0-4f69-ab27-e08a2b799e25 · outbound

This paper cites Optuna: A Next-generation Hyperparameter Optimization Framework.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Optuna: A Next-generation Hyperparameter Optimization Framework

Reference 30

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Observation 9af0eeaa-267e-4d44-9a9d-eb7d8b91006d · outbound

This paper cites A review of fea- ture selection methods with applications,.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment A review of fea- ture selection methods with applications,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:37.788411Z

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Observation c5cce943-63cb-49ab-afef-4e9e738174e5 · outbound

This paper cites Statistical analysis, evaluation and reporting guidelines of quality measurements (ITU-T P.1401),.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Statistical analysis, evaluation and reporting guidelines of quality measurements (ITU-T P.1401),

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:37.531662Z

Source-reported events for the cited work

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Observation e9fceda9-2497-41c5-8129-0ff87e613edd · outbound

This paper cites Available: https://www.sciencedirect.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Available: https://www.sciencedirect

Reference 2011

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Observation b5135dce-cd31-4249-9445-a32cfb2378a4 · outbound

This paper cites Available: https://www.itu.int/rec/ T-REC-P.1401/en.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Available: https://www.itu.int/rec/ T-REC-P.1401/en

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:37.252009Z

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Observation b3c57144-f536-44a8-8ca4-2d4ce12df121 · outbound

This paper cites Available: https://arxiv.org/abs/2202.

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment Available: https://arxiv.org/abs/2202

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:44:39.044862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 2b165956-61b5-49aa-b76b-51df1c1375ea · inbound