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Paper Citation Record · LEDGER

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition

As of 18 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2506.22807.

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

pith.paper-citation-record.v1
2506.22807 v3

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:02:36.800670Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

  • verified exact1
  • verified fuzzy16
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5de9afb8-f2c3-435c-8ec4-4f3f2e346bba · outbound

This paper cites Hypergraph Multi-Modal Learning for EEG-based Emotion Recognition in Conversation.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition Hypergraph Multi-Modal Learning for EEG-based Emotion Recognition in Conversation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T22:02:34.974269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:02:34.974269Z digest=sha256:cf23b1a5f5edc5d3277daeec6521d60a635f22eb59e1576d625d95c12cc7528a

Observation 84b3671b-bdd5-4bec-b4d8-45c83332803a · outbound

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

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition EEG emotion recognition using dynamical graph convolutional neural networks

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:39.812075Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.044886Z digest=sha256:7962c626f58d12f170d06283d9116b2ba407bed32c35083e0470643ad7c0a4f3

Observation 3565cc29-5a07-42fd-a2f4-cc5cfc7ea3c9 · outbound

This paper cites EmT: A Novel Transformer for Generalized Cross-subject EEG Emotion Recognition.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition EmT: A Novel Transformer for Generalized Cross-subject EEG Emotion Recognition

Reference 3

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unresolved
no resolver link, observed 2026-08-06T22:02:35.111519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:02:35.111519Z digest=sha256:17d6621b184d4cd6e450fe44ca9b13fa93ab8b7a3983e0f22d6baf2e50de0de8

Observation 083d812e-1600-4956-bebc-4298b8cdf36e · outbound

This paper cites Approaches, applications, and challenges in physiological emotion recognition—a tutorial overview.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition Approaches, applications, and challenges in physiological emotion recognition—a tutorial overview

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:39.716696Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.177669Z digest=sha256:7a3f97ff88fd2f586dc2891c5bd73a4b7ecbe9dd44eb6561182d28c97552e218

Observation eb63f183-9535-4599-9796-3762a3451b79 · outbound

This paper cites A dual-branch dynamic graph convolution based adaptive transformer feature fusion network for EEG emotion recognition.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition A dual-branch dynamic graph convolution based adaptive transformer feature fusion network for EEG emotion recognition

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:39.578722Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.263009Z digest=sha256:fb6931e27198e21a9dcfcea81cf17d932ad6b16456b15dd60da54d2e6cec7075

Observation 67e8f051-24d7-4167-846d-50014a71020b · outbound

This paper cites PGCN: Pyramidal graph convolutional network for EEG emotion recognition.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition PGCN: Pyramidal graph convolutional network for EEG emotion recognition

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:39.428763Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.360316Z digest=sha256:c7e88a3ce3f7fff78a7405d054bd6d8a01ec80f06daed8ce251c8dd272071cad

Observation 7c9964c7-d569-4786-8d5c-2c1468b3c9fb · outbound

This paper cites LEREL: Lipschitz continuity-constrained emotion recognition ensemble learning for electroencephalography.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition LEREL: Lipschitz continuity-constrained emotion recognition ensemble learning for electroencephalography

Reference 7

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verified exact
raw_fallback, observed 2026-08-06T22:02:37.103886Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.466568Z digest=sha256:f4e0719fd3db07e470bb1dacdf38ad0667893e1a1049819747fe617db6cd961d

Observation d4b62762-ad4b-4679-b1dd-0c402b8e0dc7 · outbound

This paper cites Dynamic domain adaptation for class-aware cross-subject and cross-session EEG emotion recognition.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition Dynamic domain adaptation for class-aware cross-subject and cross-session EEG emotion recognition

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:39.291184Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.557347Z digest=sha256:a9aeeaf56cf6f6d027fdac601e5955b105418ed4d8872bd4629199b48770cbff

Observation 939c3cb9-e5cd-41e8-aa65-ef80eb52e896 · outbound

This paper cites EEG-based emotion recognition using regularized graph neural networks.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition EEG-based emotion recognition using regularized graph neural networks

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:39.175589Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.661161Z digest=sha256:737c3d31f07ba73a4f9ea332cbc546676eda2b09c13567600912fdf74e18d2d5

Observation cbd79e2c-3fab-473a-877f-c1bdd1bf3457 · outbound

This paper cites GCB-Net: Graph convolutional broad network and its application in emotion recognition.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition GCB-Net: Graph convolutional broad network and its application in emotion recognition

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:39.037613Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.783216Z digest=sha256:0d91fe526f341dd447d06cac932d5ac4f8ecad16c8b04bff74325ea922e72947

Observation 2cdf0a22-ecc0-4b4e-97d8-ad714ad4c780 · outbound

This paper cites EEG Conformer: Convolutional transformer for eeg decoding and visualization.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition EEG Conformer: Convolutional transformer for eeg decoding and visualization

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:38.894214Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.859696Z digest=sha256:7360c5d606b6d3644ba195f8e248a60d9137f0e5321c8a33d0cd86a0d05eac9d

Observation 985f5e94-0419-4309-9120-d6d9ef0fa787 · outbound

This paper cites AMDET: Attention based multiple dimensions EEG transformer for emotion recognition.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition AMDET: Attention based multiple dimensions EEG transformer for emotion recognition

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:38.760779Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:35.943156Z digest=sha256:e8ec9bfd63e14714ddf3ec44e7fdb9dadc10a8b45f01517ed5827fcbb9486860

Observation 446efa10-19b8-48c2-b25a-e930fb7fccda · outbound

This paper cites MS-MDA: Multisource marginal distribution adaptation for cross-subject and cross-session EEG emotion recognition.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition MS-MDA: Multisource marginal distribution adaptation for cross-subject and cross-session EEG emotion recognition

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:38.587357Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:36.015882Z digest=sha256:8a13a4b9a9ef5734864d41e6c129de4e36739ed4f45990a457912aa5a943a7b9

Observation 299c205e-dd3e-4710-9c5a-571de60e6015 · outbound

This paper cites Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:38.513084Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:36.127435Z digest=sha256:9d104c194b17ed0027d11d9f8d4380a121fccd717e398b8af119ce485202788e

Observation 2caa24a2-9391-4278-b787-6d0a607e081c · outbound

This paper cites Neural-MCRL: Neural Multimodal Contrastive Representation Learning for EEG-based Visual Decoding.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition Neural-MCRL: Neural Multimodal Contrastive Representation Learning for EEG-based Visual Decoding

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T22:02:36.175772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:02:36.175772Z digest=sha256:544f05b4c4dc1541ea70c4d03f5a164727e6e11c877be01c10b00a5d70f073c8

Observation ade13a50-0658-4b02-bcdb-24046ac8d166 · outbound

This paper cites Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:38.283106Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:36.285837Z digest=sha256:e11f4f33f7be327455b5d2a803842bb7f53fb4896f4aea652814ec61c2a999c4

Observation 96780325-53fa-4254-84ae-87c68c202ae1 · outbound

This paper cites A large finer-grained affective computing EEG dataset.Scientific Data, 10(1):740, 2023.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition A large finer-grained affective computing EEG dataset.Scientific Data, 10(1):740, 2023

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:38.002378Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:36.350770Z digest=sha256:9acdb02a7eaf2f551fef76d30006ca5b54eef1a896f2848da9317d11035df3d4

Observation bc7fc3fd-f8b3-46d8-bcac-982de443af3e · outbound

This paper cites Emotionmeter: A multimodal framework for recognizing human emotions.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition Emotionmeter: A multimodal framework for recognizing human emotions

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:37.802563Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:36.477700Z digest=sha256:31512bb456307d56179a3d141a796161711eaa72c9d6a2f11a69fcf429f48392

Observation 1dbbcbc4-4d27-4b42-9135-7085a22088c0 · outbound

This paper cites EEG alpha activity reflects attentional demands, and beta activity reflects emotional and cognitive processes.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition EEG alpha activity reflects attentional demands, and beta activity reflects emotional and cognitive processes

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:37.591461Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:36.646470Z digest=sha256:e9a00020c74b2d5e2c3fc58fc7920c77774304eaaa179b77f79216b9ea0364ce

Observation 02a3d8bd-f97c-4876-94b2-36a21805195b · outbound

This paper cites On the role of asymmetric frontal cortical activity in approach and withdrawal motivation: An updated review of the evidence.

FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition On the role of asymmetric frontal cortical activity in approach and withdrawal motivation: An updated review of the evidence

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:02:37.376966Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T22:02:36.800670Z digest=sha256:00e92d63145e2a44b9bb2b132cccdfcb9c68b8c6e2853e5badf9248fca38a152

Pith citing papers

No inbound Pith citation observations are available.