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Paper Citation Record · LEDGER

A Trustworthy Method for Multimodal Emotion Recognition

As of 17 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2508.07625.

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

pith.paper-citation-record.v1
2508.07625 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:03:27.052890Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

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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

52 of 52 outbound references displayed

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  • verified fuzzy48
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ec7bf88d-5fd5-4187-b5c4-eac41c1f2863 · outbound

This paper cites EEG emotion recognition using dynamical graph convolutional neural networks,.

A Trustworthy Method for Multimodal Emotion Recognition EEG emotion recognition using dynamical graph convolutional neural networks,

Reference 1

Resolution
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Observation c08c4cff-c4f5-4fa2-b2fd-3a23b2187b4b · outbound

This paper cites A comparison of the affectiva imotions facial expression analysis software with EMG for identifying facial expressions of emotion,.

A Trustworthy Method for Multimodal Emotion Recognition A comparison of the affectiva imotions facial expression analysis software with EMG for identifying facial expressions of emotion,

Reference 2

Resolution
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Observation 123e93b3-bf24-4cd3-b0c9-22d104c8c064 · outbound

This paper cites Utilizing deep learning towards multi- 14Big Data Mining and Analytics,xxxxxxx20xx, x(x): xxx-xxx modal bio-sensing and vision-based affective computing,.

A Trustworthy Method for Multimodal Emotion Recognition Utilizing deep learning towards multi- 14Big Data Mining and Analytics,xxxxxxx20xx, x(x): xxx-xxx modal bio-sensing and vision-based affective computing,

Reference 3

Resolution
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Observation 1d889911-974e-494e-9ba5-014719526c4a · outbound

This paper cites Emotion recognition using facial expressions,.

A Trustworthy Method for Multimodal Emotion Recognition Emotion recognition using facial expressions,

Reference 4

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Observation e2788c83-5642-4507-8c17-f417aa5a61e7 · outbound

This paper cites Ease: Robust facial expression recognition via emotion ambiguity-sensitive cooperative networks,.

A Trustworthy Method for Multimodal Emotion Recognition Ease: Robust facial expression recognition via emotion ambiguity-sensitive cooperative networks,

Reference 5

Resolution
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Source-reported events for the cited work

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Observation 5b15495b-ce2a-4f11-9fa2-5908cac1ddec · outbound

This paper cites Deep facial expression recognition: A survey,.

A Trustworthy Method for Multimodal Emotion Recognition Deep facial expression recognition: A survey,

Reference 6

Resolution
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Observation cf49c8cf-ad9b-438a-86ea-711f571c0364 · outbound

This paper cites D 2S: Dynamic distribution supervision for multi-label facial expression recognition,.

A Trustworthy Method for Multimodal Emotion Recognition D 2S: Dynamic distribution supervision for multi-label facial expression recognition,

Reference 7

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Source-reported events for the cited work

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Observation e72f2d5d-1c15-4c93-8d1b-f8f0f1f9e1af · outbound

This paper cites Survey on emotional body gesture recognition,.

A Trustworthy Method for Multimodal Emotion Recognition Survey on emotional body gesture recognition,

Reference 8

Resolution
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Source-reported events for the cited work

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Observation a428c25f-a939-49b2-bc73-6e06dbd5a332 · outbound

This paper cites Self supervised adversarial domain adaptation for cross-corpus and cross- language speech emotion recognition,.

A Trustworthy Method for Multimodal Emotion Recognition Self supervised adversarial domain adaptation for cross-corpus and cross- language speech emotion recognition,

Reference 9

Resolution
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Observation 6d6daf2a-b206-4e9c-8309-4e77a083225c · outbound

This paper cites M2fnet: Multi-modal fusion network for emotion recognition in conversation,.

A Trustworthy Method for Multimodal Emotion Recognition M2fnet: Multi-modal fusion network for emotion recognition in conversation,

Reference 10

Resolution
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Source-reported events for the cited work

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Observation ef6d21c1-ca4b-4a85-a5a7-244f03f95b96 · outbound

This paper cites Facial expression recognition with visual transformers and attentional selective fusion,.

A Trustworthy Method for Multimodal Emotion Recognition Facial expression recognition with visual transformers and attentional selective fusion,

Reference 11

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Observation 5c143a11-ea61-4dea-ad18-c5e80e488898 · outbound

This paper cites Trusted multi-view classification with dynamic evidential fusion,.

A Trustworthy Method for Multimodal Emotion Recognition Trusted multi-view classification with dynamic evidential fusion,

Reference 12

Resolution
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Source-reported events for the cited work

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Observation c4b0dcbf-da5d-4b47-a31b-f7d581021cda · outbound

This paper cites Facial expression recognition with identity and emotion joint learning,.

A Trustworthy Method for Multimodal Emotion Recognition Facial expression recognition with identity and emotion joint learning,

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 6e3092c8-9af1-4c87-9211-ee5d9017fc9f · outbound

This paper cites Eeg- based emotion recognition for multi channel fast empirical mode decomposition using vgg-16,.

A Trustworthy Method for Multimodal Emotion Recognition Eeg- based emotion recognition for multi channel fast empirical mode decomposition using vgg-16,

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 748b8d64-acae-4352-a437-83a16c3b7666 · outbound

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

A Trustworthy Method for Multimodal Emotion Recognition Quo vadis, action recognition? a new model and the kinetics dataset,

Reference 15

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Source-reported events for the cited work

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Observation 9141f9af-2443-4dda-bc17-b7e3595149ea · outbound

This paper cites Audio-visual emotion recognition in video clips,.

A Trustworthy Method for Multimodal Emotion Recognition Audio-visual emotion recognition in video clips,

Reference 16

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Source-reported events for the cited work

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Observation 33ee44cc-d740-4e56-b0ae-bdd382b71449 · outbound

This paper cites Attention driven fusion for multi-modal emotion recognition,.

A Trustworthy Method for Multimodal Emotion Recognition Attention driven fusion for multi-modal emotion recognition,

Reference 17

Resolution
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Source-reported events for the cited work

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Observation b4f1cc51-093b-45c9-954f-a3f7bf8be453 · outbound

This paper cites Facial Emotion Recognition: State of the Art Performance on FER2013.

A Trustworthy Method for Multimodal Emotion Recognition Facial Emotion Recognition: State of the Art Performance on FER2013

Reference 18

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Source-reported events for the cited work

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Observation 601c414d-3789-4583-8800-636341bc1f55 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

A Trustworthy Method for Multimodal Emotion Recognition Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 19

Resolution
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Source-reported events for the cited work

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Observation 6d581139-0269-4350-b258-1e7069a559a8 · outbound

This paper cites Two- level attention with two-stage multi-task learning for facial emotion recognition,.

A Trustworthy Method for Multimodal Emotion Recognition Two- level attention with two-stage multi-task learning for facial emotion recognition,

Reference 20

Resolution
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Source-reported events for the cited work

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Observation 96a6fce7-561c-4d76-a4b1-6c4157587477 · outbound

This paper cites Context-aware emotion recognition networks,.

A Trustworthy Method for Multimodal Emotion Recognition Context-aware emotion recognition networks,

Reference 21

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Source-reported events for the cited work

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Observation 74351c38-61ba-44ec-ad04-60b4e468aa58 · outbound

This paper cites An attention model for group-level emotion recognition,.

A Trustworthy Method for Multimodal Emotion Recognition An attention model for group-level emotion recognition,

Reference 22

Resolution
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Source-reported events for the cited work

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Observation 6e93bfcc-6bf4-4b42-a367-b01cde614be0 · outbound

This paper cites On calibration of modern neural networks,.

A Trustworthy Method for Multimodal Emotion Recognition On calibration of modern neural networks,

Reference 23

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Source-reported events for the cited work

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Observation 64f79ebd-30d2-499c-9adc-314b0dd37828 · outbound

This paper cites Calibrating deep neural networks using focal loss,.

A Trustworthy Method for Multimodal Emotion Recognition Calibrating deep neural networks using focal loss,

Reference 24

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Source-reported events for the cited work

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Observation eed1825d-0cf1-4e48-8992-0a388a87fa0b · outbound

This paper cites Don’t just blame over- parametrization for over-confidence: Theoretical analysis of calibration in binary classification,.

A Trustworthy Method for Multimodal Emotion Recognition Don’t just blame over- parametrization for over-confidence: Theoretical analysis of calibration in binary classification,

Reference 25

Resolution
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Observation 5f441efb-5512-4435-9d8e-8fc9b59424d6 · outbound

This paper cites Be confident! towards trustworthy graph neural networks via confidence calibration,.

A Trustworthy Method for Multimodal Emotion Recognition Be confident! towards trustworthy graph neural networks via confidence calibration,

Reference 26

Resolution
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Source-reported events for the cited work

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Observation a07459d4-8d63-4423-a994-d5f33422ff7f · outbound

This paper cites Masked autoencoders are scalable vision learners,.

A Trustworthy Method for Multimodal Emotion Recognition Masked autoencoders are scalable vision learners,

Reference 27

Resolution
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Source-reported events for the cited work

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Observation cbb07041-cf80-4396-905b-92824afe7354 · outbound

This paper cites Mage: Masked generative encoder to unify representation learning and image synthesis,.

A Trustworthy Method for Multimodal Emotion Recognition Mage: Masked generative encoder to unify representation learning and image synthesis,

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 6bda7b6f-c829-485e-9fd5-bcad7a2c05c6 · outbound

This paper cites Video swin transformer,.

A Trustworthy Method for Multimodal Emotion Recognition Video swin transformer,

Reference 29

Resolution
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Source-reported events for the cited work

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Observation f135dd7f-edc7-44bc-93b5-867186452e4f · outbound

This paper cites CNN architectures for large-scale audio classification,.

A Trustworthy Method for Multimodal Emotion Recognition CNN architectures for large-scale audio classification,

Reference 30

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 208a5894-7922-421f-b5e8-156487719cc9 · outbound

This paper cites The relationship between precision-recall and roc curves,.

A Trustworthy Method for Multimodal Emotion Recognition The relationship between precision-recall and roc curves,

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 2781783a-3794-449c-9a74-4d8dd8b78a2b · outbound

This paper cites IEMOCAP: Interactive emotional dyadic motion capture database,.

A Trustworthy Method for Multimodal Emotion Recognition IEMOCAP: Interactive emotional dyadic motion capture database,

Reference 32

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation ab1350f3-57ff-43cf-a19e-98b6992f31c6 · outbound

This paper cites Deep learning-based late fusion of multimodal information for emotion classification of music video,.

A Trustworthy Method for Multimodal Emotion Recognition Deep learning-based late fusion of multimodal information for emotion classification of music video,

Reference 33

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 980747dd-7ab4-4c74-a790-85037ef6e799 · outbound

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

A Trustworthy Method for Multimodal Emotion Recognition Pytorch: An imperative style, high-performance deep learning library,

Reference 34

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 265f0ca7-e241-4ae0-b705-3e4accf34a01 · outbound

This paper cites Adam: A method for stochastic optimization,.

A Trustworthy Method for Multimodal Emotion Recognition Adam: A method for stochastic optimization,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.273312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.001019Z digest=sha256:9cf2d7a1ffb3a42f343d84377e6b6aefd723b85a47b4fa5d5e854807ff077c3b

Observation 0223686d-90ca-4d97-895d-dc3bbe639272 · outbound

This paper cites Context-dependent sentiment analysis in user-generated videos,.

A Trustworthy Method for Multimodal Emotion Recognition Context-dependent sentiment analysis in user-generated videos,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.263350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.004054Z digest=sha256:b01d991b0b23f4e31b1e9e216c79eb1580492ccbc49756f93efe15e6d47baeca

Observation 91c4fed3-ae47-4670-88e1-aa12afa77709 · outbound

This paper cites DialogueGCN: A graph convolutional neural network for emotion recognition in conversation,.

A Trustworthy Method for Multimodal Emotion Recognition DialogueGCN: A graph convolutional neural network for emotion recognition in conversation,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.253457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.007130Z digest=sha256:a580777a67bf6b4c24a07c44005ba80d8b08f44a5825206e082d27d3ef6e7f82

Observation b9f2eb33-be9b-47da-bb8f-a29849694e7c · outbound

This paper cites Directed acyclic graph network for conversational emotion recognition,.

A Trustworthy Method for Multimodal Emotion Recognition Directed acyclic graph network for conversational emotion recognition,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.243287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.010602Z digest=sha256:2539eb04b3ddece13c526c5e020b5b90027cfbde9811ad8bca619a46ef522dde

Observation aaeca31b-1f61-4598-b9cf-c8cc98da671c · outbound

This paper cites Multi-task learning for multi-modal emotion recognition and sentiment analysis,.

A Trustworthy Method for Multimodal Emotion Recognition Multi-task learning for multi-modal emotion recognition and sentiment analysis,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.233305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.013716Z digest=sha256:a0d7c13c9760a983990a58773d9f43feed73f5eab31bce4c59ae0f206a915f84

Observation c607ec7c-8818-421f-a4dd-171c3cc8d94a · outbound

This paper cites COGMEN: COntextualized GNN based multimodal emotion recognition,.

A Trustworthy Method for Multimodal Emotion Recognition COGMEN: COntextualized GNN based multimodal emotion recognition,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.223333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.016787Z digest=sha256:f0e91ab3aa230a3b02474f16e6dda6b3b2238027e4baceda75eda199a01344ce

Observation 0a7ad3cb-0c38-4797-b53e-31a8bd89b797 · outbound

This paper cites MMGCN: Multimodal fusion via deep graph convolution network for emotion recognition in conversation,.

A Trustworthy Method for Multimodal Emotion Recognition MMGCN: Multimodal fusion via deep graph convolution network for emotion recognition in conversation,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.213273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.019616Z digest=sha256:4ab044281a991ad3e5e9b5400616909430ae1dd0387a0882ceab8eccdd60aae8

Observation 6c13b476-e6bf-4a0d-a4b9-cf1f14ff830d · outbound

This paper cites Opensmile: the munich versatile and fast open-source audio feature extractor,.

A Trustworthy Method for Multimodal Emotion Recognition Opensmile: the munich versatile and fast open-source audio feature extractor,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.202126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.022536Z digest=sha256:6e0ab52118b60ed90801745e107d34ca5dde1efbf629e21ae0c612614f3d1299

Observation 7b37490e-b215-472b-8851-7002ae141ee6 · outbound

This paper cites Speech emotion recognition: Two decades in a nutshell, benchmarks, and ongoing trends,.

A Trustworthy Method for Multimodal Emotion Recognition Speech emotion recognition: Two decades in a nutshell, benchmarks, and ongoing trends,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.190673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.025354Z digest=sha256:9e2cc6e3e3dc2db7cded3bbbf7254d313279dfecfe30978ef969dde7be4e9c2a

Observation e24274b6-66b3-400d-871e-e30aec67ced6 · outbound

This paper cites Speech emotion recognition based on attention weight correction using word-level confidence measure.

A Trustworthy Method for Multimodal Emotion Recognition Speech emotion recognition based on attention weight correction using word-level confidence measure

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.180328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.028775Z digest=sha256:e6fa7292a399d8f16a0a1cf8186e09a86b1225a6c89fd00d3a781006d60f838f

Observation 735e80f2-44a9-4678-9437-3bc37e6de663 · outbound

This paper cites Confidence measures for speech Junxiao Xue et al.:A Trustworthy Method for Multimodal Emotion Recognition ...15 emotion recognition: A start,.

A Trustworthy Method for Multimodal Emotion Recognition Confidence measures for speech Junxiao Xue et al.:A Trustworthy Method for Multimodal Emotion Recognition ...15 emotion recognition: A start,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.170289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.031713Z digest=sha256:22350724337786e80d7599871f9265a9e91909dd4b627936137e67763363ddb2

Observation 5c29db5c-59da-4d49-b633-1f08146e9fdb · outbound

This paper cites Confidence measures in speech emotion recognition based on semi-supervised learning,.

A Trustworthy Method for Multimodal Emotion Recognition Confidence measures in speech emotion recognition based on semi-supervised learning,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.159415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.034841Z digest=sha256:91bdb9e13841b7d935a526a45cc11d158f3801b08af542acb622afe98280c4e9

Observation 365e7b1b-14de-4131-8d34-6b849dbf0e74 · outbound

This paper cites Confidence estimation for speech emotion recognition based on the relationship between emotion categories and primitives,.

A Trustworthy Method for Multimodal Emotion Recognition Confidence estimation for speech emotion recognition based on the relationship between emotion categories and primitives,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.148930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.037595Z digest=sha256:68c40c47beb7c6f46db51817c04197852085e7a39e911da205ebbb5b78a88ff9

Observation 594d4442-89ff-4a55-ad24-7a14fcc799f1 · outbound

This paper cites MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations.

A Trustworthy Method for Multimodal Emotion Recognition MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-05T22:03:27.040416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:03:27.040416Z digest=sha256:5df2a48b3006bbbd8d136abe51fdc79682080183e850696e9ce9a2cc8cabe0ab

Observation 7b546936-98c0-48a3-a04b-ccdd51aff528 · outbound

This paper cites Affective video content analysis: Decade review and new perspectives,.

A Trustworthy Method for Multimodal Emotion Recognition Affective video content analysis: Decade review and new perspectives,

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-05T22:03:27.043714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:03:27.043714Z digest=sha256:4055df9edcc3406a057bf6f6da31f4452356218baa1c1f9b32693a52595b3ad0

Observation 60ab95da-724a-4a9d-8c9e-44137b5f19c7 · outbound

This paper cites Multimodal graph learning with framelet-based stochastic configuration networks for emotion recognition in conversation,.

A Trustworthy Method for Multimodal Emotion Recognition Multimodal graph learning with framelet-based stochastic configuration networks for emotion recognition in conversation,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.131284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.047064Z digest=sha256:1cd7aad8b71134399f6829281d15ea5b280c334b204b41e745e845e1782078ca

Observation cc0c03d5-238b-458f-9b12-099016932ce4 · outbound

This paper cites Gm2rc: Graph-based multitask modality refinement and complement for multimodal sentiment analysis,.

A Trustworthy Method for Multimodal Emotion Recognition Gm2rc: Graph-based multitask modality refinement and complement for multimodal sentiment analysis,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.118751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.049914Z digest=sha256:a65e00c8a270420f1976f6153cd278f05647c5f77b860f9f2585d0f2225dce94

Observation 805a62a8-973d-4ad6-b9d0-6947c2175a60 · outbound

This paper cites Frameerc: Framelet transform based multimodal graph neural networks for emotion recognition in conversation,.

A Trustworthy Method for Multimodal Emotion Recognition Frameerc: Framelet transform based multimodal graph neural networks for emotion recognition in conversation,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:03:27.107261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:03:27.052890Z digest=sha256:2274c9393244bef70364c95dc7793410ea363c58f98a4585e973c8247dd4b997

Pith citing papers

No inbound Pith citation observations are available.