Paper Citation Record · LEDGER

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering

As of 18 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2606.29166.

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

pith.paper-citation-record.v1
2606.29166 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T02:48:08.925030Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact3
verified fuzzy0
unresolved32
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ba2c0ae1-2747-4f13-9024-048875729a28 · outbound

This paper cites an unresolved cited work.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation bbd6cd7d-2828-46c5-a1b3-a6e97f19ebee · outbound

This paper cites an unresolved cited work.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 7d8f0c62-15b3-4ef0-9e52-fa6ff451da07 · outbound

This paper cites an unresolved cited work.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 8752dd72-f4fa-43a6-addb-dd7b35561b00 · outbound

This paper cites Bjontegaard metric.https://github.com/ Anserw/Bjontegaard_metric, 2016.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Bjontegaard metric.https://github.com/ Anserw/Bjontegaard_metric, 2016

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 44ffddcb-2252-40d1-8640-171ef7ca8071 · outbound

This paper cites Revisiting feature prediction for learning visual representations from video, 2024.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Revisiting feature prediction for learning visual representations from video, 2024

Reference 5

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Observation a9dae005-039d-4c43-87e8-8015554c3624 · outbound

This paper cites A simple framework for contrastive learning of visual representations, 2020.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering A simple framework for contrastive learning of visual representations, 2020

Reference 6

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Observation 8d7a4a8b-ef5e-4353-a963-0aee6196330a · outbound

This paper cites An empirical study of training self-supervised vision transformers.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering An empirical study of training self-supervised vision transformers

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 6cc7dca4-019d-4c4f-9bf5-f3130a23884f · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering An image is worth 16x16 words: Transformers for image recognition at scale

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 149fc991-bc22-499a-a55e-7dbb9686c8e6 · outbound

This paper cites an unresolved cited work.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 6bbb0d3d-930b-469c-9337-6ceb2b02871e · outbound

This paper cites Leveraging compres- sion to construct transferable bitrate ladders.arXiv preprint arXiv:2512.12952, 2025.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Leveraging compres- sion to construct transferable bitrate ladders.arXiv preprint arXiv:2512.12952, 2025

Reference 10

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Observation 0504f604-dbc4-4281-870a-69a77e8bdee1 · outbound

This paper cites Omnimae: Single model masked pretraining on images and videos.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Omnimae: Single model masked pretraining on images and videos

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation be5b1ca0-99cb-4a1b-aee4-d9e8b82b0692 · outbound

This paper cites Richemond, Elena Buchatskaya, Carl Do- ersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Moham- mad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, R´emi Munos, and Michal Valko.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Richemond, Elena Buchatskaya, Carl Do- ersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Moham- mad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, R´emi Munos, and Michal Valko

Reference 12

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Source-reported events for the cited work

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Observation 8dfafef5-7b85-4628-b9fe-00d047af0f65 · outbound

This paper cites Momentum contrast for unsupervised visual rep- resentation learning, 2020.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Momentum contrast for unsupervised visual rep- resentation learning, 2020

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 41e4e577-552d-4ee5-a5aa-b7c6b0cfef7f · outbound

This paper cites Rate distor- tion optimization over large scale video corpus with machine learning.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Rate distor- tion optimization over large scale video corpus with machine learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

Source-reported events for the cited work

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Observation 0910338f-360a-41de-8c51-5cd79697150f · outbound

This paper cites Katsenou, Joel Sole, and David Bull.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Katsenou, Joel Sole, and David Bull

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 153e26d3-dc34-4a92-a001-32cb0a04ccd8 · outbound

This paper cites Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673,.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 01100f92-e355-477e-8c83-e9932e4fc14e · outbound

This paper cites Image quality assessment by separately evaluating detail losses and additive impairments.IEEE Transactions on Multimedia, 13 (5):935–949, 2011.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Image quality assessment by separately evaluating detail losses and additive impairments.IEEE Transactions on Multimedia, 13 (5):935–949, 2011

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation d82935d4-f34f-4956-9df0-c237cbed6d0c · outbound

This paper cites Towards perceptually-optimized compression of user generated content (ugc): Prediction of ugc rate-distortion category.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Towards perceptually-optimized compression of user generated content (ugc): Prediction of ugc rate-distortion category

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

Source-reported events for the cited work

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Observation 1974553b-af3b-4879-921b-366b9dad8b61 · outbound

This paper cites Decoupled Weight Decay Regularization.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Decoupled Weight Decay Regularization

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-06-30T02:54:10.256581Z

Source-reported events for the cited work

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

Observation 796cb716-3560-4183-998f-047b25cdfb92 · outbound

This paper cites Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, and Alan C.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, and Alan C

Reference 20

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Observation 44df3e30-99da-4b19-aeb6-a01f66f7b5f1 · outbound

This paper cites Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, and Alan C.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, and Alan C

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation df7d3a66-750d-4858-af8d-f9a57f9982f9 · outbound

This paper cites Menon, Hadi Amirpour, Mohammad Ghanbari, and Christian Timmerer.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Menon, Hadi Amirpour, Mohammad Ghanbari, and Christian Timmerer

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation bfa42fa8-a90f-43a2-bf22-61243f0c8084 · outbound

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

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering OpenVid-1M: A Large-Scale High-Quality Dataset for Text- to-video Generation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

Source-reported events for the cited work

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Observation 66fd415d-efc3-4b06-8940-da9b8d01a5ac · outbound

This paper cites Dinov2: Learning robust visual features with- out supervision, 2024.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Dinov2: Learning robust visual features with- out supervision, 2024

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

Source-reported events for the cited work

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Observation f04d189c-ddd0-41a5-ad7d-7a76dbcd4ac6 · outbound

This paper cites Learning transferable visual models from natural language supervision, 2021.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Learning transferable visual models from natural language supervision, 2021

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 30ea0e62-d6a4-4b1c-9280-0b80692912e6 · outbound

This paper cites Sheikh and A.C.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Sheikh and A.C

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation b01155ba-bfb0-46db-9aed-e11167e6f3db · outbound

This paper cites Video quality as- sessment by reduced reference spatio-temporal entropic dif- ferencing.IEEE Transactions on Circuits and Systems for Video Technology, 23(4):684–694, 2012.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Video quality as- sessment by reduced reference spatio-temporal entropic dif- ferencing.IEEE Transactions on Circuits and Systems for Video Technology, 23(4):684–694, 2012

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 53866355-fe9c-4142-a94d-a40ce4900241 · outbound

This paper cites LAVIB: A Large-scale Video Interpolation Benchmark.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering LAVIB: A Large-scale Video Interpolation Benchmark

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-30T02:54:10.252437Z

Source-reported events for the cited work

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

Observation 13611432-71d1-45ed-8622-650ff86eccc2 · outbound

This paper cites AdaPool: Exponen- tial Adaptive Pooling for Information-Retaining Downsam- pling.arXiv preprint, 2021.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering AdaPool: Exponen- tial Adaptive Pooling for Information-Retaining Downsam- pling.arXiv preprint, 2021

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

Source-reported events for the cited work

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Observation 511a79be-e353-4865-931f-71839b142dbe · outbound

This paper cites Benchmarking learning-based bitrate ladder prediction methods for adaptive video streaming.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Benchmarking learning-based bitrate ladder prediction methods for adaptive video streaming

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation a680029c-01b8-45f6-9467-44d6e2ab4cc4 · outbound

This paper cites VideoMAE: Masked Autoencoders are data-efficient learn- ers for self-supervised video pre-training.Advances in Neu- ral Information Processing Systems, 35:10078–10093, 2022.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering VideoMAE: Masked Autoencoders are data-efficient learn- ers for self-supervised video pre-training.Advances in Neu- ral Information Processing Systems, 35:10078–10093, 2022

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 273d79cc-0560-4425-83b9-8a31a80a7d9a · outbound

This paper cites YouTube UGC Dataset for Video Compression Research.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering YouTube UGC Dataset for Video Compression Research

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 2a514b4c-63d2-4df7-9690-336d5f13780c · outbound

This paper cites Bovik, H.R.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Bovik, H.R

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation cce4b4d9-fd2b-4802-8367-53a44ed99a16 · outbound

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

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Exploring video quality assessment on user generated contents from aesthetic and technical perspectives

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Observation 9c9c2e2d-7060-4766-a6e6-36b5a78e600a · outbound

This paper cites Fast encoding parameter selection for convex hull video encoding.

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering Fast encoding parameter selection for convex hull video encoding

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-30T02:48:08.925030Z

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Pith citing papers

No inbound Pith citation observations are available.