Paper Citation Record · LEDGER

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

As of 19 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 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

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.

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 2026-08-19T06:32:44.657259+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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

Resolution: 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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

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 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.