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Paper Citation Record · LEDGER

Supervised Contrastive Learning for Ordinal Engagement Measurement

As of 7 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 1 inbound Pith citation observation for arXiv:2505.20676.

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

pith.paper-citation-record.v1
2505.20676 v1

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:53:46.122920Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-07T17:52:38.238603Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T11:01:31.719902Z

Reference resolution

66 of 66 outbound references displayed

  • verified exact2
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  • unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f707d09b-c0b8-4f64-a4d9-143a0ef3a76b · outbound

This paper cites Covid-19 pandemic–online education in the new normal and the next normal,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Covid-19 pandemic–online education in the new normal and the next normal,

Reference 1

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Observation 82603aa7-b16b-49ac-b737-b2de7ab456a6 · outbound

This paper cites Perceptions and behaviors of learner engagement with virtual educational platforms,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Perceptions and behaviors of learner engagement with virtual educational platforms,

Reference 2

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Source-reported events for the cited work

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Observation 5639f126-3bcf-432c-b689-6bd4a751c6c9 · outbound

This paper cites Engagement in online learning: student attitudes and behavior during covid-19,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Engagement in online learning: student attitudes and behavior during covid-19,

Reference 3

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Observation fb7c8c60-d51f-4c00-8a03-945a2503ef12 · outbound

This paper cites Student engagement, academic self-efficacy, and academic motivation as predictors of academic performance,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Student engagement, academic self-efficacy, and academic motivation as predictors of academic performance,

Reference 4

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Source-reported events for the cited work

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Observation 80c3b27d-0655-4570-90cd-148ca22a493c · outbound

This paper cites Automatic prediction of presentation style and student engagement from videos,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Automatic prediction of presentation style and student engagement from videos,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 41d63282-b3a0-418d-a937-ff30a9720c01 · outbound

This paper cites Inconsistencies in measuring student engagement in virtual learning-a critical review,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Inconsistencies in measuring student engagement in virtual learning-a critical review,

Reference 6

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Observation c0871732-43f9-4864-9b50-2aec32fd1130 · outbound

This paper cites Automatic engagement estimation in smart education/learning settings: a systematic review of engage- ment definitions, datasets, and methods,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Automatic engagement estimation in smart education/learning settings: a systematic review of engage- ment definitions, datasets, and methods,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9d6c7585-89a5-4934-b50c-a20b8c0e8a0a · outbound

This paper cites The challenges of defining and measuring student engagement in science,.

Supervised Contrastive Learning for Ordinal Engagement Measurement The challenges of defining and measuring student engagement in science,

Reference 8

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Source-reported events for the cited work

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Observation 9c0e8325-7a52-4445-bc7b-7b605ea5254a · outbound

This paper cites Advanced, analytic, auto- mated (aaa) measurement of engagement during learning,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Advanced, analytic, auto- mated (aaa) measurement of engagement during learning,

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2f77d325-5539-4bb0-8ff7-a157cf9231bb · outbound

This paper cites Improving state-of-the-art in detecting student engagement with resnet and tcn hybrid network,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Improving state-of-the-art in detecting student engagement with resnet and tcn hybrid network,

Reference 10

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Source-reported events for the cited work

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Observation b7b98afc-0d8e-4347-8445-f70a92fd4454 · outbound

This paper cites Detecting disengagement in virtual learning as an anomaly using temporal convolutional network autoencoder,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Detecting disengagement in virtual learning as an anomaly using temporal convolutional network autoencoder,

Reference 11

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Source-reported events for the cited work

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Observation 8113bdbf-27db-42a0-b975-a7380d1bf3f4 · outbound

This paper cites Affect-driven ordinal engagement measure- ment from videos,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Affect-driven ordinal engagement measure- ment from videos,

Reference 12

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Source-reported events for the cited work

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Observation cc9077bd-e930-4b4c-867c-eba4c717ad02 · outbound

This paper cites Tclr: Temporal con- trastive learning for video representation,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Tclr: Temporal con- trastive learning for video representation,

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 83965dba-99b6-4755-a608-0c49877eb549 · outbound

This paper cites Deep learning based engagement recognition in highly imbalanced data,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Deep learning based engagement recognition in highly imbalanced data,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9fecb6be-8ea4-4ec9-8afc-6fd498b5b7ab · outbound

This paper cites Deep facial spatiotemporal network for engagement prediction in online learning,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Deep facial spatiotemporal network for engagement prediction in online learning,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6272eec6-6a2a-4691-8326-1ba220db650f · outbound

This paper cites Class-attention Video Transformer for Engagement Intensity Prediction.

Supervised Contrastive Learning for Ordinal Engagement Measurement Class-attention Video Transformer for Engagement Intensity Prediction

Reference 16

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Source-reported events for the cited work

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Observation 3a382c54-799b-4a1d-b863-e95cff580b65 · outbound

This paper cites Fine-grained engagement recognition in online learning environment,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Fine-grained engagement recognition in online learning environment,

Reference 17

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Source-reported events for the cited work

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Observation 1872cf92-1a54-45fe-9e5f-8a386b91aff7 · outbound

This paper cites The faces of engagement: Automatic recognition of student engagement from facial expressions,.

Supervised Contrastive Learning for Ordinal Engagement Measurement The faces of engagement: Automatic recognition of student engagement from facial expressions,

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c95b0a7b-2667-4dcc-97dd-f635381d2337 · outbound

This paper cites Toward active and unobtrusive engagement assessment of distance learners,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Toward active and unobtrusive engagement assessment of distance learners,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5edcad15-028e-4fd9-9f2c-91b1dc61f8fb · outbound

This paper cites Prediction and lo- calization of student engagement in the wild,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Prediction and lo- calization of student engagement in the wild,

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 72c9571b-c035-440c-816a-0b1cd98581b5 · outbound

This paper cites Automatic engagement prediction with gap feature,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Automatic engagement prediction with gap feature,

Reference 21

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 159d185a-5083-41c0-97cb-6a8dc34ccfa0 · outbound

This paper cites Multimodal approach to engagement and disengagement detection with highly imbalanced in-the-wild data,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Multimodal approach to engagement and disengagement detection with highly imbalanced in-the-wild data,

Reference 22

Resolution
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Source-reported events for the cited work

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Observation 417f3597-4cc2-4dc8-aa96-ffeeb3404235 · outbound

This paper cites Predicting engagement intensity in the wild using temporal convolutional network,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Predicting engagement intensity in the wild using temporal convolutional network,

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 6c03429b-9df4-4675-9cc1-66f8eee36d13 · outbound

This paper cites Faceen- gage: robust estimation of gameplay engagement from user-contributed (youtube) videos,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Faceen- gage: robust estimation of gameplay engagement from user-contributed (youtube) videos,

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 13c5f8db-9d01-497a-ae39-1e5a5ce5d423 · outbound

This paper cites Advanced multi-instance learning method with multi-features engineering and conservative opti- mization for engagement intensity prediction,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Advanced multi-instance learning method with multi-features engineering and conservative opti- mization for engagement intensity prediction,

Reference 25

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Source-reported events for the cited work

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Observation 80ec9b56-cc99-4d6f-88ab-4f6a41a84d81 · outbound

This paper cites Automatic student engagement in online learning environment based on neural turing machine,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Automatic student engagement in online learning environment based on neural turing machine,

Reference 26

Resolution
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Source-reported events for the cited work

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Observation 08622ea1-fa67-41a8-8748-fe2c52b48162 · outbound

This paper cites Engagement detection with multi-task training in e-learning environments,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Engagement detection with multi-task training in e-learning environments,

Reference 27

Resolution
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Observation 76e89753-4dc5-4366-a95c-e00e7ab02568 · outbound

This paper cites Automatic student engagement measurement using machine learning techniques: A literature study of data and methods,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Automatic student engagement measurement using machine learning techniques: A literature study of data and methods,

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ae94ee46-5ff6-409f-bd8d-d7d955e0d04e · outbound

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

Supervised Contrastive Learning for Ordinal Engagement Measurement A simple framework for contrastive learning of visual representations,

Reference 29

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Source-reported events for the cited work

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Observation 438e66df-9a1f-4717-83e9-9bf125c1be5d · outbound

This paper cites Supervised contrastive learning for detecting anomalous driving behaviours from multimodal videos,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Supervised contrastive learning for detecting anomalous driving behaviours from multimodal videos,

Reference 30

Resolution
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Source-reported events for the cited work

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Observation e24f2c18-42ae-4db8-a918-932c723ad8e6 · outbound

This paper cites Supervised Contrastive Learning.

Supervised Contrastive Learning for Ordinal Engagement Measurement Supervised Contrastive Learning

Reference 31

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Source-reported events for the cited work

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Observation 3f62318f-7524-4436-9125-ecf323ec88d5 · outbound

This paper cites Time series contrastive learning with information-aware augmentations,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Time series contrastive learning with information-aware augmentations,

Reference 32

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Source-reported events for the cited work

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Observation 8011e5fa-304e-4e18-8fd4-b899c411909b · outbound

This paper cites Rank-N-Contrast: Learning Continuous Representations for Regression.

Supervised Contrastive Learning for Ordinal Engagement Measurement Rank-N-Contrast: Learning Continuous Representations for Regression

Reference 33

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Source-reported events for the cited work

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Observation 5cad6be6-d70d-4745-8a86-76b481f9d4a3 · outbound

This paper cites Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification.

Supervised Contrastive Learning for Ordinal Engagement Measurement Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification

Reference 34

Resolution
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Source-reported events for the cited work

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Observation bfebb228-fb76-487d-be10-933f798833e1 · outbound

This paper cites Improving contrastive learning on imbalanced data via open-world sampling,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Improving contrastive learning on imbalanced data via open-world sampling,

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T13:53:51.039919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:41.397192Z digest=sha256:fc3713d586e8d7834f177844de52548e8b8442435dcdcce0caa84077c6cf58f4

Observation 8f7542e0-74fb-41bf-86d6-716cce68ece8 · outbound

This paper cites A circumplex model of affect.

Supervised Contrastive Learning for Ordinal Engagement Measurement A circumplex model of affect

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:41.497804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:41.497804Z digest=sha256:6399677aa41ded11e67cf95207d1d176e79144153083b9d2d6ba6ab15904864b

Observation 307a0872-325b-41a9-8f97-17ee5e60d32e · outbound

This paper cites Engagement detection in online learning: a review,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Engagement detection in online learning: a review,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:41.674694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:41.674694Z digest=sha256:0c00796f5a7ee7fcfa8d41e08684a5f434e07400a524b50ac0709860dae01799

Observation 2f6177fd-3758-4977-aad6-f09088e4ce4c · outbound

This paper cites An empirical survey of data augmentation for time series classification with neural networks,.

Supervised Contrastive Learning for Ordinal Engagement Measurement An empirical survey of data augmentation for time series classification with neural networks,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:50.878560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:41.796077Z digest=sha256:e16342669c5476d2bf4be40151609f8c9361f1fcc7a40304dfa01bb96bf3e4d9

Observation 5fd5c35f-9645-4e79-b3f4-6ca787370e58 · outbound

This paper cites A simple approach to ordinal classification,.

Supervised Contrastive Learning for Ordinal Engagement Measurement A simple approach to ordinal classification,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:50.701674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:41.903077Z digest=sha256:5a0a7c1d6f6d017f4546b868534267119dca83d32d0a6fa55e868f35265f2bdd

Observation 88c28f91-e285-4304-9b92-6484b0aed348 · outbound

This paper cites DAiSEE: Towards User Engagement Recognition in the Wild.

Supervised Contrastive Learning for Ordinal Engagement Measurement DAiSEE: Towards User Engagement Recognition in the Wild

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:42.053796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:42.053796Z digest=sha256:a0fadb802fce0e1fe83d50003266f57e42bb6897e7434c30c4f2abf88ea98a71

Observation 1d1525e1-abd3-4180-8c65-2c02cb94cb75 · outbound

This paper cites Learning deep spatiotemporal feature for engagement recognition of online courses,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Learning deep spatiotemporal feature for engagement recognition of online courses,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:50.545131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:42.182693Z digest=sha256:9ec96a9c1dcf2583b3c915a57c81b900430096c5f9e5a19034e01e342fb24cad

Observation 127f5ddf-aff7-45fd-b039-890b3e09bddf · outbound

This paper cites An novel end-toend network for automatic student engagement recognition,.

Supervised Contrastive Learning for Ordinal Engagement Measurement An novel end-toend network for automatic student engagement recognition,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:50.381639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:42.552763Z digest=sha256:aa01256446079174be453bca243801d101726de60321cdb5744d2bec05f9624e

Observation 0e786453-a5d9-4771-bce7-39458633937a · outbound

This paper cites An optimized cnn model for engagement recognition in an e-learning environment,.

Supervised Contrastive Learning for Ordinal Engagement Measurement An optimized cnn model for engagement recognition in an e-learning environment,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:50.230652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:42.738210Z digest=sha256:0e286d2dc0674f557d45513a509bae37425f77396cdde26285d83e227232a9d3

Observation c8b22267-0993-4f7c-85cc-c5732877eabd · outbound

This paper cites Threedimen- sional densenet self-attention neural network for automatic detection of student’s engagement,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Threedimen- sional densenet self-attention neural network for automatic detection of student’s engagement,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:50.072149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:42.888885Z digest=sha256:d42a1f3773db053365f56df07a6b17a3bafcc7666568ab2ae3bdad05d2d88e72

Observation e763972d-7e28-496d-aae8-2c10a099467a · outbound

This paper cites Students engagement level detection in online e-learning using hybrid efficientnetb7 together with tcn, lstm, and bi-lstm,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Students engagement level detection in online e-learning using hybrid efficientnetb7 together with tcn, lstm, and bi-lstm,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:49.878041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:42.994728Z digest=sha256:cd359068fc9949228b84e290f7f6a071bf45f0baddba4b145a682f79af7d43e5

Observation 0076a47a-da71-4972-a4da-169d51a33eac · outbound

This paper cites Do I Have Your Attention: A Large Scale Engagement Prediction Dataset and Baselines.

Supervised Contrastive Learning for Ordinal Engagement Measurement Do I Have Your Attention: A Large Scale Engagement Prediction Dataset and Baselines

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:53:46.629125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:43.108723Z digest=sha256:c1838dee97042faa398366813cec9a8bb51b95109e88733d53d05da201e55ac0

Observation 09ea5bd5-2c58-4f1d-b3f5-ea0b7e331432 · outbound

This paper cites Recognition of student engagement and affective states using convnextlarge and ensemble gru in e-learning,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Recognition of student engagement and affective states using convnextlarge and ensemble gru in e-learning,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:49.708427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:43.279839Z digest=sha256:01869976e138896aac53c0d9e041f26af93d8d3c9c0c8a51812e531c3e07bf63

Observation f60a91f8-bfdb-49aa-b90a-e46f6b462031 · outbound

This paper cites Multimodal graph learning based on 3d haar semi-tight framelet for student engagement prediction,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Multimodal graph learning based on 3d haar semi-tight framelet for student engagement prediction,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:49.551628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:43.501429Z digest=sha256:ec557a45459ac2834514c1b715d63c0b82350f81de5e1745b5d6d88bf6ac73b5

Observation a8be962a-0657-49f1-8cca-d6d990cb6e70 · outbound

This paper cites Re-distributing facial features for engagement prediction with moderntcn,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Re-distributing facial features for engagement prediction with moderntcn,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:49.380318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:43.670618Z digest=sha256:e67d52b299b5b9806009d25a4030125159d97446cdd264be734d6bf4c454e797

Observation 85a12668-4209-44e5-9005-cb16032c644d · outbound

This paper cites Msc-trans: A multi-feature-fusion network with encoding structure for student engagement detection,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Msc-trans: A multi-feature-fusion network with encoding structure for student engagement detection,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:49.221388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:43.770690Z digest=sha256:04b17c244e6fa1d4aed0ec39645af9e2a66cd6ccec724c0a493ee1c6ca5aaf45

Observation 0811a5f5-ba1c-49ec-8d47-546e7fd0e426 · outbound

This paper cites Detection of student engagement in e-learning environments using efficientnetv2- l together with rnn-based models,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Detection of student engagement in e-learning environments using efficientnetv2- l together with rnn-based models,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:49.064629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:43.840116Z digest=sha256:fb6cae42862bf48c11d4f5b0326973f2db7d8a927b328432efdd38aa45d56b3a

Observation e573eecf-922b-40bb-b3fa-1dd74e5a99b4 · outbound

This paper cites Enhancing frame-level student engagement clas- sification through knowledge transfer techniques,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Enhancing frame-level student engagement clas- sification through knowledge transfer techniques,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:48.862192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:43.930669Z digest=sha256:d94555fa2d3720e9f4b559d6c00b5b366606b092b614da0cfc0d6dde91acfce4

Observation 7675c534-43cd-4a24-a7df-4dc3ad45f575 · outbound

This paper cites A self- supervised learning network for student engagement recognition from facial expressions,.

Supervised Contrastive Learning for Ordinal Engagement Measurement A self- supervised learning network for student engagement recognition from facial expressions,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:48.705468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:44.045515Z digest=sha256:0113bf1f220c675a01b39d839b718ba87bc39424d79645a12c6b19ff97579422

Observation 0dcfd781-8c82-4881-bf0b-2f455b61c49d · outbound

This paper cites Engagement measurement based on facial landmarks and spatial-temporal graph convolutional networks,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Engagement measurement based on facial landmarks and spatial-temporal graph convolutional networks,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:48.536794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:44.201959Z digest=sha256:9b9fe53c936a0ca3cce2b0909f1269cdc057514aa92d13a261eca9d2a5f9c7ee

Observation 76b9fa77-19ec-41f0-a87f-ad2534c05d27 · outbound

This paper cites Bag of States: A Non-sequential Approach to Video-based Engagement Measurement.

Supervised Contrastive Learning for Ordinal Engagement Measurement Bag of States: A Non-sequential Approach to Video-based Engagement Measurement

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:44.344779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:44.344779Z digest=sha256:d208d692aeeef8529ba47af15ba4daaa3704ff551b22b7a151b5b78a5a9a926b

Observation 317e8a53-c2ac-4ee2-9583-1cf1d2748ffa · outbound

This paper cites Blink rate patterns provide a reliable measure of individual engagement with scene content,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Blink rate patterns provide a reliable measure of individual engagement with scene content,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:48.404471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:44.469755Z digest=sha256:0aa4ff77edd9b02d21fc90649586f2737a3d94002bee0f1fec5444148318705d

Observation 8956b785-a4d5-4287-8080-bb33697168f3 · outbound

This paper cites Openface 2.0: Facial behavior analysis toolkit,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Openface 2.0: Facial behavior analysis toolkit,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:48.227012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:44.626225Z digest=sha256:cd002bca67b5dcaa19db258608255546f14f0a84e6f7cd63eec8247d02f364f8

Observation c6abcaa5-9ef3-49b8-9c79-8492a5eeb6ae · outbound

This paper cites Understanding the behaviour of contrastive loss,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Understanding the behaviour of contrastive loss,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:48.027659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:44.821297Z digest=sha256:6626f205a7f10b20b7de5150d8cc1a21f878723f039612ee32e438648500e4c5

Observation 91021f1e-9283-41f6-83a8-f6657dec08e1 · outbound

This paper cites The ordinal nature of emotions: An emerging approach,.

Supervised Contrastive Learning for Ordinal Engagement Measurement The ordinal nature of emotions: An emerging approach,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:47.837059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:44.979557Z digest=sha256:1629539bcd710eb24dfb9a72e5c4a22353d125603402367ce7b0df03de0ae7ec

Observation 462ae4f6-2df2-4c5f-8606-47f6c639cca1 · outbound

This paper cites Estimation of continuous valence and arousal levels from faces in naturalistic conditions,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Estimation of continuous valence and arousal levels from faces in naturalistic conditions,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:47.631267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:45.185171Z digest=sha256:9ca5eca4890b24b7bb81395f305323ec38672222c0c7255d8d0a3a8912f4f864

Observation 17baff15-cb7b-45bd-9420-cf3677d1d1b0 · outbound

This paper cites Affectnet: A database for facial expression, valence, and arousal computing in the wild,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Affectnet: A database for facial expression, valence, and arousal computing in the wild,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:47.428744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:45.466519Z digest=sha256:7e63778bd8d8344dee5e40686060f890b864bba9ecf71daeb42d07c55fc255bc

Observation 764865f9-7aaa-4cd4-bdb0-f2e3ec478d86 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Pytorch: An imperative style, high-performance deep learning library,

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:45.643667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:45.643667Z digest=sha256:9bd4b8b2afe4f088bcc41bafd3c00656e325f7c15c0a017204e65542de9da885

Observation 2976e7fd-00cc-434e-b26f-74cc4206d205 · outbound

This paper cites Scikit-learn: Machine learning in python,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Scikit-learn: Machine learning in python,

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:45.796873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:45.796873Z digest=sha256:3601fcd45510c0c4e56dc491e1fc66101e760c9b8945a8f1ea78b452903a5803

Observation e3914b61-4134-4c90-b972-c61ac60c35fb · outbound

This paper cites Facial Expression Recognition in Video Using 3D-CNN Deep Features Discrimination,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Facial Expression Recognition in Video Using 3D-CNN Deep Features Discrimination,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:47.235954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:45.982619Z digest=sha256:c5071216cb36a1c711d266af1c751ea1e0a841c11629c4a2d770d2ebca40fbec

Observation 4eeed171-2013-46c7-ac93-cd6fc33a1d0e · outbound

This paper cites Leveraging part-and-sensitive attention network and transformer for learner engagement detection,.

Supervised Contrastive Learning for Ordinal Engagement Measurement Leveraging part-and-sensitive attention network and transformer for learner engagement detection,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:53:47.035781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:46.122920Z digest=sha256:cdd496e47bdf022aaa99ae5bc77f6e778fd04610e6541e6d3e672e23bdf4703e

Observation a07ab651-cfaf-4a7f-ba2d-6df8d8b77ba2 · outbound

This paper cites Available: https://doi.org/10.1038/s42256-020-00285-2.

Supervised Contrastive Learning for Ordinal Engagement Measurement Available: https://doi.org/10.1038/s42256-020-00285-2

Reference 2021

Resolution
verified exact
doi, observed 2026-08-07T13:53:46.398621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:53:45.335443Z digest=sha256:0ce5eddcf759d49aebb32082186778b43eab26cbb53a9054bfcc2040b6b224cd

Pith citing papers

Observation 7af6443b-9a4c-44a7-b040-8241ae804828 · inbound

PriorNet: Prior-Guided Engagement Estimation from Face Video cites this paper.

PriorNet: Prior-Guided Engagement Estimation from Face Video Supervised Contrastive Learning for Ordinal Engagement Measurement

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-12T11:01:31.721845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T17:52:38.238603Z digest=sha256:f8b4f18b1be753e578a5c049df602aae7742973f8f1a40370552b33cfe7c8835