Paper Citation Record · LEDGER

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition

As of 15 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2501.15063.

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

pith.paper-citation-record.v1
2501.15063 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:43:42.168958Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:56:45.896590Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy27
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2f250034-acdf-4258-826f-0d1b7b1bea49 · outbound

This paper cites Erc dmsp: Emotion recognition in conversation based on dynamic modeling of speaker personalities,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Erc dmsp: Emotion recognition in conversation based on dynamic modeling of speaker personalities,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.586229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 83b3bf19-bfda-492c-97ec-3412b483b257 · outbound

This paper cites Modeling sentiment-speaker- dependency for emotion recognition in conversation,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Modeling sentiment-speaker- dependency for emotion recognition in conversation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.576430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a8e09736-86c9-48da-9674-04b6f307f4b4 · outbound

This paper cites D-man: a distance- based multi-channel attention network for erc,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition D-man: a distance- based multi-channel attention network for erc,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.566005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d12cb769-63eb-4d26-af57-bdd58d86a80e · outbound

This paper cites Ctf-erc: Coarse-to-fine rea- soning for emotion recognition in conversations,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Ctf-erc: Coarse-to-fine rea- soning for emotion recognition in conversations,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.555337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5bef658f-a64f-4183-a9ec-826939752a62 · outbound

This paper cites Deep learning approaches for effective human computer interaction: A comprehensive survey on single and multimodal emotion detection,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Deep learning approaches for effective human computer interaction: A comprehensive survey on single and multimodal emotion detection,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.542305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 72f6f8c0-f698-4b3d-9706-b3736f02e8ab · outbound

This paper cites Deep learning in digital marketing: brand detection and emotion recognition,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Deep learning in digital marketing: brand detection and emotion recognition,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.528601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f28f388b-259f-44fd-8340-034a55533d53 · outbound

This paper cites Cnn based face emotion recognition system for healthcare application,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Cnn based face emotion recognition system for healthcare application,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.495890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ebe8dec2-6fa8-414b-a4d0-bd5475d8a639 · outbound

This paper cites Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.388013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0da28bd0-9f51-452d-b0f4-915405dfd82b · outbound

This paper cites Multimodal emotion recognition with deep learning: advancements, challenges, and future directions,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Multimodal emotion recognition with deep learning: advancements, challenges, and future directions,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.300592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9b6653dd-112f-426e-8ea9-950ec0b1e79e · outbound

This paper cites Enhancing aerial object detec- tion with selective frequency interaction network,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Enhancing aerial object detec- tion with selective frequency interaction network,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.217819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 42f7b517-b4fa-40d6-9934-6aabf37df891 · outbound

This paper cites LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T14:43:41.767831Z

Source-reported events for the cited work

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Observation d0f365df-1d2f-49fd-8e1f-531eab34470d · outbound

This paper cites Triplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Triplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T14:43:41.819277Z

Source-reported events for the cited work

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Observation c0a4e0e1-2d94-4569-85f5-07b3fb58f0f9 · outbound

This paper cites IMAGDressing-v1: Customizable Virtual Dressing.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition IMAGDressing-v1: Customizable Virtual Dressing

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T14:43:41.873432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81a82d55-675c-4af6-b0b7-c3e303fb504c · outbound

This paper cites Imagpose: A unified conditional framework for pose-guided person generation,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Imagpose: A unified conditional framework for pose-guided person generation,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T14:43:41.895820Z

Source-reported events for the cited work

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Observation c52d4c8e-0baa-4009-af5c-9b6092f02491 · outbound

This paper cites Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T14:43:41.930124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48a52583-0b0b-4a28-8da9-b704d55a958e · outbound

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

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Context-dependent sentiment analysis in user-generated videos

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.200504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1a2521ce-dcbc-49f2-aaec-4b74b015cf60 · outbound

This paper cites Conversational memory network for emotion recognition in dyadic dialogue videos.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Conversational memory network for emotion recognition in dyadic dialogue videos

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.176986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 380519bb-9f61-456c-b5c7-56899c151e1c · outbound

This paper cites Dialoguernn: An attentive rnn for emotion detection in conversations,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Dialoguernn: An attentive rnn for emotion detection in conversations,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:43.152801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1d03fe31-e0ab-40ab-908b-a78e40d7e459 · outbound

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

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Dia- loguegcn: A graph convolutional neural network for emotion recognition in conversation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.996342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 02f9f152-e82d-4c28-b345-b28992bda52e · outbound

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

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Mmgcn: Multimodal fusion via deep graph convolution network for emotion recognition in conversation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.923730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a1c0b045-aee5-4752-b48c-ccd0411ce67c · outbound

This paper cites Git: Graph interactive transformer for vehicle re-identification,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Git: Graph interactive transformer for vehicle re-identification,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.801775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8a806df1-add5-43cd-8df6-578fec6b8e71 · outbound

This paper cites Pedestrian-specific bipartite-aware similarity learning for text-based person retrieval,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Pedestrian-specific bipartite-aware similarity learning for text-based person retrieval,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T14:43:42.001119Z

Source-reported events for the cited work

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Observation 5103a0af-ecc2-498e-8cd4-71e9f1345a1b · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Semi-supervised classification with graph convolutional networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.781459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9f7b8039-5bb8-4ba6-a5ea-93549239f940 · outbound

This paper cites Inductive representation learn- ing on large graphs,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Inductive representation learn- ing on large graphs,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.771000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d140e467-7f26-433e-ab5f-bcdbd38f0af0 · outbound

This paper cites Liu and J.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Liu and J

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.760009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 057b279b-d7cf-4bd8-bf7e-ec0448217d1a · outbound

This paper cites an unresolved cited work.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:43:42.744771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9c0762fa-8f1d-44da-a5cf-a29fa1b0dbaa · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.723644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d8e6dfce-59fc-4411-acdd-d26c639a3ec8 · outbound

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

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Opensmile: the munich versatile and fast open-source audio feature extractor,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.705886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5c23eaf0-84f4-4b8f-ab4a-ecbcd01bf464 · outbound

This paper cites Densely connected convolutional networks,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Densely connected convolutional networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.656901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e19d5933-9d27-48ca-99d3-e354c4675594 · outbound

This paper cites Deep residual learning for image recognition,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Deep residual learning for image recognition,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.552993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2449b76f-a709-41c1-9b91-5458415524d4 · outbound

This paper cites Hierarchical question-image co- attention for visual question answering,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Hierarchical question-image co- attention for visual question answering,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.456047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cc2e2a9d-67d4-47bc-b588-6d225fb1c39f · outbound

This paper cites Empirical evaluation of gated recurrent neural networks on sequence modeling,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Empirical evaluation of gated recurrent neural networks on sequence modeling,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.391944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 97a5c96b-8aa0-4bea-b647-bf30a512f480 · outbound

This paper cites Iemocap: interactive emotional dyadic motion capture database,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Iemocap: interactive emotional dyadic motion capture database,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.330377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c500f671-fa67-4565-80ba-21502555b203 · outbound

This paper cites Icon: Interactive conversational memory network for multimodal emo- tion detection,.

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition Icon: Interactive conversational memory network for multimodal emo- tion detection,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:43:42.274845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e6f5bcd4-f365-4d4a-a6fd-77819a7e2a7d · outbound

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

Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T14:43:42.168958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation c08c528f-3abb-43e8-97f9-8ef52a15dd22 · inbound

Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects cites this paper.

Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:56:45.896590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.