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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 2026-08-14T06:32:32.682623+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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.652606Z digest=sha256:f394b6d3dcc726411835e8c0fc207a128df3b42f0e3d17b37d11ff1782fad670

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.702698Z digest=sha256:e821568aaff303660e3cd3cbe951f829c2b4e3c04434a2a6e9373d2c6fa04918

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.707253Z digest=sha256:e37a88d9c3d3d1b9ebaafb158684fd1e17d78a174c6b1cb397d139bb318f333e

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.714089Z digest=sha256:c2fb5d67ace959f938183f8b920b7ef417dabf30411c1356db663365840a18c0

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.719483Z digest=sha256:9e13e96e91cbff6e1286013c82a268d6ff46be4f3ebf17f977f20144e72f2130

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.723844Z digest=sha256:2018da5c53fe48dff791baa5509e18d7a0c2f4a8c5f5fbd0318958fe1799db82

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.727840Z digest=sha256:efb1bf4c7589b9bf19b01680e6334375d6fc8c95b5e7bf663a53f6aa3461ca22

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.731584Z digest=sha256:75c0d1929cc6688b6349f19352500418445628a51a8552706cf3a330746dd71e

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:43:41.767831Z digest=sha256:a09e5b175dae77286baa09753f95428286ba6ce04e82e60cf78e52e5ddd5fcc5

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:43:41.819277Z digest=sha256:f5fa7cbd1d282713b36dfcbe6c2024cb40995a1e378d9aeb414468c59eb76945

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.

source=pdf_text observed=2026-08-10T14:43:41.873432Z digest=sha256:13ed6a1ede18b002dd06e9105943324f9c206030a0981e330e816c407eaddbef

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:43:41.895820Z digest=sha256:57c149095a5f9845cf79d5a772443ba23536c102454e14cfe043958382265e06

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.

source=pdf_text observed=2026-08-10T14:43:41.930124Z digest=sha256:51b175c78464fd603e196d3efdb2724bb9ace62834e01b77ddfe099099c6f9de

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.967556Z digest=sha256:655b5445d808f63cf497789b2ffde4d19f1c3fc0509c1742779148b91da631b8

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 2026-08-14T06:32:32.682623+00:00.

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.983315Z digest=sha256:6f005529af366ff48099a872add852f4f51d78943cc01e6df6caaef61495a1d4

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.989176Z digest=sha256:cee00a0d9fc20e40d9c240b18bc18f0361f79593f7e6378c44ef44ca40b22d81

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.992511Z digest=sha256:763a6f44d25cfa1b4620d14e39e916485ad6f120f12e842393819730b2b9bc40

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:41.997186Z digest=sha256:fe8f01314a9064c9cbc905b07a50655f98c1b44e3448704516ab3f487d4823e8

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:43:42.001119Z digest=sha256:5d3093490c73060508bd3293989821e1d423f22e9ccfde67b932e027681c2273

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:42.014650Z digest=sha256:edbe228e8aa372b024ad826b596bfd8b133a3a7093a8d5e40fe385e2c43c8793

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 2026-08-14T06:32:32.682623+00:00.

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:42.039088Z digest=sha256:356a6c5120729be229b2f0ab750275cec4b342236ad3a1b4bef9145db9683c3d

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 2026-08-14T06:32:32.682623+00:00.

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:42.097107Z digest=sha256:10df9feea4614a4622d7fbd0d99ae863141d9f972c2a48fc1ec27b20e5605566

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:42.100612Z digest=sha256:a8040b65e76185204e14ae2859e1fec0b05c6dced015706b88319732c50df469

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:42.105581Z digest=sha256:ef5734bc29d33c78eac6f41b851ca5982dba0fa386f5e2fe8cc8bdbb3ae3be84

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:42.114214Z digest=sha256:bf597cc32a1472d08af26dacbfc775658d113c2b630180364f7295e2e32e8cba

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:42.117755Z digest=sha256:f46415c1820ec98b162a8c94cfc0212738ca8a1139149dad824431c86490dd94

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T14:43:42.124560Z digest=sha256:aafea11898e441becd7bcce359a8ebe0904894b7d47ad16797d52f862a7c8688

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 2026-08-14T06:32:32.682623+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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