Paper Citation Record · LEDGER

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification

As of 19 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.12585.

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

pith.paper-citation-record.v1
2506.12585 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:51:56.884183Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

39 of 39 outbound references displayed

verified exact0
verified fuzzy29
unresolved9
parse uncertain1
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b67e59df-72e3-4759-8e5a-2bb81e2eef98 · outbound

This paper cites YouTube-8M: A Large-Scale Video Classification Benchmark.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification YouTube-8M: A Large-Scale Video Classification Benchmark

Reference 1

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Source-reported events for the cited work

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Observation 8ab1f47e-37e1-492d-ba82-f1c039c19797 · outbound

This paper cites Timesformer-base-finetuned-ssv2.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Timesformer-base-finetuned-ssv2

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.525211Z

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Observation 658d9a26-9c3b-4d8d-aab3-e2817319650d · outbound

This paper cites Vivit: A video vision transformer.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Vivit: A video vision transformer

Reference 3

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Observation 0e6c9a0d-4b2b-4063-b9ca-347ec6f49e00 · outbound

This paper cites The UEA multivariate time series classification archive, 2018.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification The UEA multivariate time series classification archive, 2018

Reference 4

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Observation 5bbfc546-cf26-442b-a620-80a9224747a0 · outbound

This paper cites Using dynamic time warping to find patterns in time series.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Using dynamic time warping to find patterns in time series

Reference 5

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Observation 1d43921f-e6c8-4bf0-80f9-0808086775e4 · outbound

This paper cites Is space-time attention all you need for video understanding? In International Conference on Machine Learning , pages 813–824.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Is space-time attention all you need for video understanding? In International Conference on Machine Learning , pages 813–824

Reference 6

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cf12174a-9605-4cc6-94ec-25092be3717a · outbound

This paper cites Dtwnet: a dynamic time warping network.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Dtwnet: a dynamic time warping network

Reference 7

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Observation b4090e4c-e43c-4145-bfb2-a4b89ad4c28f · outbound

This paper cites Few-shot video classification via tem- poral alignment.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Few-shot video classification via tem- poral alignment

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.453503Z

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Observation 09578d25-841b-4bdb-bc52-a50e17681f84 · outbound

This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Quo vadis, action recognition? a new model and the kinetics dataset

Reference 9

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Observation 315ad924-60b3-4429-8890-1adac7358998 · outbound

This paper cites D3tw: Discriminative differentiable dy- namic time warping for weakly supervised action alignment and segmentation.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification D3tw: Discriminative differentiable dy- namic time warping for weakly supervised action alignment and segmentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.421567Z

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Observation 72fb712a-6387-4227-928a-1b4aa814a023 · outbound

This paper cites Soft-dtw: a differen- tiable loss function for time-series.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Soft-dtw: a differen- tiable loss function for time-series

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.405107Z

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Observation 49b76c07-5636-4dec-89ea-cc453d97ef29 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 12

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Observation 459a09dc-828e-4b8a-b759-e4ff64da2bcb · outbound

This paper cites Slowfast networks for video recognition.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Slowfast networks for video recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.388333Z

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Observation 7f00da72-1183-46ff-a8af-06f48485d2fe · outbound

This paper cites Fine- grained temporal contrastive learning for weakly-supervised temporal action localization.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Fine- grained temporal contrastive learning for weakly-supervised temporal action localization

Reference 14

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Observation bfe652ce-9907-4a39-815b-03c21ce5086d · outbound

This paper cites Video action transformer network.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Video action transformer network

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.355791Z

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Observation 5b31ee90-1947-4b84-ad02-bb3848c92ffa · outbound

This paper cites The” something something” video database for learning and evaluating visual common sense.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification The” something something” video database for learning and evaluating visual common sense

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.340875Z

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Observation d22e2b74-cc59-435e-b28f-a9c623386500 · outbound

This paper cites Large-scale video classification with convolutional neural networks.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Large-scale video classification with convolutional neural networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.325267Z

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Observation 9f767076-8961-46d2-b541-d5fefcb44829 · outbound

This paper cites The Kinetics Human Action Video Dataset.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification The Kinetics Human Action Video Dataset

Reference 18

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Observation 10b678ad-36a8-44d2-9eda-b472ec2b4779 · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Imagenet classification with deep convolutional neural net- works

Reference 19

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Observation aca566b0-fae4-45de-9ee6-402a446ed581 · outbound

This paper cites Hmdb: a large video database for human motion recognition.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Hmdb: a large video database for human motion recognition

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.299267Z

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Observation b22a03c0-d157-4d0d-a430-b76faa09ebf0 · outbound

This paper cites Tam: Temporal adaptive module for video recog- nition.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Tam: Temporal adaptive module for video recog- nition

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.283560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7b9f8c0d-00dc-4b12-90ab-d2b9395b7587 · outbound

This paper cites Action recognition on something-something v2 leaderboard.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Action recognition on something-something v2 leaderboard

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.267961Z

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Observation b2429d20-ce5a-4c9a-a0f7-4a670b37a1d8 · outbound

This paper cites A global averaging method for dynamic time warping, with ap- plications to clustering.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification A global averaging method for dynamic time warping, with ap- plications to clustering

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.235229Z

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Observation 7b01e21c-c369-4531-94f8-37af1feec1cf · outbound

This paper cites Re- thinking video vits: Sparse video tubes for joint image and video learning.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Re- thinking video vits: Sparse video tubes for joint image and video learning

Reference 24

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Observation d893f334-bfab-4f78-a694-2d4300b22767 · outbound

This paper cites Vivit-b-16x2-kinetics400.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Vivit-b-16x2-kinetics400

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.204661Z

Source-reported events for the cited work

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Observation 1d9f18c2-6219-4efa-8109-9b06d1675cbd · outbound

This paper cites Dynamic time warping algorithm review.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Dynamic time warping algorithm review

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.189675Z

Source-reported events for the cited work

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Observation d83b47c6-d347-44ad-bc5b-bf406b750fb4 · outbound

This paper cites The move-split-merge metric for time series.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification The move-split-merge metric for time series

Reference 27

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Source-reported events for the cited work

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Observation ae3fccc3-ab4b-497c-936e-f4bdbf6f40cc · outbound

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

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training

Reference 28

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Observation 4ca14107-601d-42f1-8128-b6e559cacf50 · outbound

This paper cites Learning spatiotemporal features with 3d convolutional networks.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Learning spatiotemporal features with 3d convolutional networks

Reference 29

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Observation a39310a2-bc76-415a-9f7a-b977ed6debc5 · outbound

This paper cites Implicit temporal modeling with learn- able alignment for video recognition.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Implicit temporal modeling with learn- able alignment for video recognition

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.132257Z

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Observation 9a368ee8-8e1b-4778-a037-9852857ffb9b · outbound

This paper cites Videomae v2: Scaling video masked autoencoders with dual masking.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Videomae v2: Scaling video masked autoencoders with dual masking

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.116076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5838d60d-65ef-43e8-9612-0def7432d396 · outbound

This paper cites Masked video distillation: Rethinking masked feature mod- eling for self-supervised video representation learning.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Masked video distillation: Rethinking masked feature mod- eling for self-supervised video representation learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.099790Z

Source-reported events for the cited work

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Observation 30471e61-9c6b-4718-a4bb-197fbf6e0fd0 · outbound

This paper cites InternVideo2: Scaling Foundation Models for Multimodal Video Understanding.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification InternVideo2: Scaling Foundation Models for Multimodal Video Understanding

Reference 33

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This paper cites What can simple arithmetic oper- ations do for temporal modeling? In Proceedings of the IEEE/CVF International Conference on Computer Vision , pages 13712–13722, 2023.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification What can simple arithmetic oper- ations do for temporal modeling? In Proceedings of the IEEE/CVF International Conference on Computer Vision , pages 13712–13722, 2023

Reference 34

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Observation f5639af5-dde6-4f43-9e8d-c87a9a7145d7 · outbound

This paper cites Multiview transformers for video recognition.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Multiview transformers for video recognition

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.068465Z

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Observation 253a879a-021b-469c-92db-e516a989b60c · outbound

This paper cites Scaling vision transformers.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Scaling vision transformers

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.053463Z

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Observation a61480f8-53da-4da3-a8c4-5ff66ee9bd86 · outbound

This paper cites We now describe our choice of the temporal sliding win- dow widths and strides.

DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification We now describe our choice of the temporal sliding win- dow widths and strides

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:51:57.038230Z

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Observation edd693eb-2acf-46f2-9be7-970f10af564f · outbound

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DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Unresolved cited work

Reference 39

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Observation 05b6330b-9b7a-4205-9ffd-8f9f28183805 · outbound

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DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification Unresolved cited work

Reference 2024

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.