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Paper Citation Record · LEDGER

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives

As of 23 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2504.14927.

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

pith.paper-citation-record.v1
2504.14927 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:40:52.576787Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy27
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7b2b0f1f-c596-49b4-8fbc-fcf5df76b591 · outbound

This paper cites Abstractive video lecture summarization: applications and future prospects.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Abstractive video lecture summarization: applications and future prospects

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 4336c2e0-7ebf-415f-b810-5b638aad8524 · outbound

This paper cites Video-based learning (VBL)—past, present and future.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Video-based learning (VBL)—past, present and future

Reference 2

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raw_fallback, observed 2026-08-16T11:40:53.076488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 445da0aa-5d46-4215-93a1-eb7d5ca4844a · outbound

This paper cites Video Summarization Techniques: A Comprehensive Review.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Video Summarization Techniques: A Comprehensive Review

Reference 3

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no resolver link, observed 2026-08-16T11:40:52.442989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d43f8b13-37a0-422a-ae17-25822027c466 · outbound

This paper cites A review of deep learning models for time series prediction.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives A review of deep learning models for time series prediction

Reference 4

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raw_fallback, observed 2026-08-16T11:40:53.061277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 47269bdc-d590-4b88-a18a-6cf86d6d48cb · outbound

This paper cites Bayesian fuzzy clustering and deep CNN-based automatic video summarization.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Bayesian fuzzy clustering and deep CNN-based automatic video summarization

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 3687a79e-311c-432d-a1d5-0c23a9214a2b · outbound

This paper cites Large Model based Sequential Keyframe Extraction for Video Summarization.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Large Model based Sequential Keyframe Extraction for Video Summarization

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation da0158f3-96bd-4f1e-b9d1-80e0fa198503 · outbound

This paper cites Deep multi-scale pyrami- dal features network for supervised video summarization.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Deep multi-scale pyrami- dal features network for supervised video summarization

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:53.015136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 68c45653-c51f-4ab5-a1f2-026f53887666 · outbound

This paper cites Distance education: Definitions, generations and key concepts and future directions.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Distance education: Definitions, generations and key concepts and future directions

Reference 8

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raw_fallback, observed 2026-08-16T11:40:53.000151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ce03e700-3f8a-4176-94e1-5a7fa4c43a37 · outbound

This paper cites Promoting student engagement in online education: Online learning experiences of Dutch university students.Technology, Knowledge and Learning, 29(2):941–961, 2024.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Promoting student engagement in online education: Online learning experiences of Dutch university students.Technology, Knowledge and Learning, 29(2):941–961, 2024

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation aecfb1d2-5f61-41fb-9404-00a366051781 · outbound

This paper cites Effects of embedded questions in pre-class videos on learner perceptions, video engagement, and learning performance.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Effects of embedded questions in pre-class videos on learner perceptions, video engagement, and learning performance

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.968658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 20973e5a-5370-4f10-9116-90347f4fe671 · outbound

This paper cites Understanding in-video dropouts and interaction peaks in online lecture videos.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Understanding in-video dropouts and interaction peaks in online lecture videos

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.953552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 87f9ba7d-9d0e-434b-a28e-c20841160565 · outbound

This paper cites How video production affects student engagement: An em- pirical study of MOOC videos.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives How video production affects student engagement: An em- pirical study of MOOC videos

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.938278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T11:40:52.485799Z digest=sha256:ab9cecfb4a6ef040114bd4b93eaff45a15fbce8b85aeed604518841d57068ab1

Observation db74988f-4991-43b0-9332-70dfcc077093 · outbound

This paper cites VLEngagement: A Dataset of Scientific Video Lectures for Evaluating Population-based Engagement.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives VLEngagement: A Dataset of Scientific Video Lectures for Evaluating Population-based Engagement

Reference 13

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no resolver link, observed 2026-08-16T11:40:52.490518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 09563f02-50ea-446e-ad01-c55d6df1a2c1 · outbound

This paper cites Context and memory in multimedia content analysis.IEEE Multimedia, 11(3):7– 11, 2004.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Context and memory in multimedia content analysis.IEEE Multimedia, 11(3):7– 11, 2004

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.922511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation fba2a950-963b-49f0-901c-6289fc9565a4 · outbound

This paper cites Soccer video summarization using deep learning.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Soccer video summarization using deep learning

Reference 15

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raw_fallback, observed 2026-08-16T11:40:52.907051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T11:40:52.500020Z digest=sha256:0365a40182e01e60b35d3e63981adb40e24777d09a6993d94d194d74c7085cfa

Observation 0c2e0241-053e-4bf9-8802-8caf48c6851a · outbound

This paper cites Automatic lecture video content summarization with attention- based recurrent neural network.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Automatic lecture video content summarization with attention- based recurrent neural network

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 28fa2311-b86e-466f-9357-35eee05b3100 · outbound

This paper cites Effects of different video lecture types on attention, emotion, cognitive load, and learning performance.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Effects of different video lecture types on attention, emotion, cognitive load, and learning performance

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 833ee053-f349-489f-9852-72aa7acd8b36 · outbound

This paper cites Effects of video instructor’s body language on students’ visual attention: An eye-tracking study.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Effects of video instructor’s body language on students’ visual attention: An eye-tracking study

Reference 18

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raw_fallback, observed 2026-08-16T11:40:52.861020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 3915ec64-43e4-47fe-829c-41c224abea78 · outbound

This paper cites Thinking in Perspective: Critical Essays in the Study of Thought Processes.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Thinking in Perspective: Critical Essays in the Study of Thought Processes

Reference 19

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raw_fallback, observed 2026-08-16T11:40:52.845407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 4b7ef9bd-e1e9-4e57-8e57-073a649509bb · outbound

This paper cites OpenPose: Real-time multi-person 2D pose estimation using Part Affinity Fields.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives OpenPose: Real-time multi-person 2D pose estimation using Part Affinity Fields

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.829455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 9c6e8eab-35f9-49a5-b6dd-60b798d01192 · outbound

This paper cites An iterative image registration technique with an application to stereo vision.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives An iterative image registration technique with an application to stereo vision

Reference 21

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 7a615e09-a08c-4b84-be9e-e8d1fc38552d · outbound

This paper cites Audio Spectrogram Representations for Processing with Convolutional Neural Networks.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Audio Spectrogram Representations for Processing with Convolutional Neural Networks

Reference 22

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no resolver link, observed 2026-08-16T11:40:52.533668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 037bb036-ccc1-48e8-9c7c-320a15dacca3 · outbound

This paper cites Speech synthesis.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Speech synthesis

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.796360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation e1f53ccf-de00-4fd9-85c8-c642663a4f26 · outbound

This paper cites Eye-tracking students’ attention to Pow- erPoint photographs in science education.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Eye-tracking students’ attention to Pow- erPoint photographs in science education

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.781049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 28fa639e-b8cd-4109-9160-9900201dfc0c · outbound

This paper cites Importance of input data normalization for neural networks in industrial problems.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Importance of input data normalization for neural networks in industrial problems

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.764015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation c5f86d90-7c13-4dfe-b95a-c41012c748f3 · outbound

This paper cites Smoothing and differentiation of data by simplified least squares procedures.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Smoothing and differentiation of data by simplified least squares procedures

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.746355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation dada3020-cb32-4d6c-a80c-32af5a2667cd · outbound

This paper cites Barriers to distance learning during the COVID-19 outbreak: A qualitative review.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Barriers to distance learning during the COVID-19 outbreak: A qualitative review

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.729632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 5685632b-bca1-4b33-9926-fa169efa0cd3 · outbound

This paper cites Case studies for self- directed learning using lecture archives.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Case studies for self- directed learning using lecture archives

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.713145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T11:40:52.561736Z digest=sha256:ec97941a54f78e1952615abb870440b026d38e4e3c68bd3d53c6c4df4ec3c55b

Observation 0031d30b-450f-450f-9cd7-de67ac19ae39 · outbound

This paper cites Automated summarization of lecture videos.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Automated summarization of lecture videos

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.697620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T11:40:52.566446Z digest=sha256:f8adaa5a71730e84e96bc1b0dba0c58ec0d158e30cc36b0b7bedc2bf6ec76bab

Observation 41738b64-96da-4364-8aad-ce8103f1c330 · outbound

This paper cites The impacts of instructor’s visual attention and lecture type on learning performance.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives The impacts of instructor’s visual attention and lecture type on learning performance

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:40:52.681293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T11:40:52.571089Z digest=sha256:f6d3875e2d1b0da4dac2a6bbbab4c70bab0eb581932ceaf12a3b62d81b522722

Observation 307fbbeb-1613-4202-bd7a-d683a8eba2f3 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Multimodal Non-Semantic Feature Fusion for Predicting Segment Access Frequency in Lecture Archives Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 31

Resolution
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no resolver link, observed 2026-08-16T11:40:52.576787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.