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Paper Citation Record · LEDGER

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation

As of 18 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 3 inbound Pith citation observations for arXiv:2412.10103.

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

pith.paper-citation-record.v1
2412.10103 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:25:15.109673Z

measured 50 of 50 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T07:04:04.812401Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

47 of 47 outbound references displayed

  • verified exact1
  • verified fuzzy46
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 9f3936a0-ccab-4af0-8551-5c228dce0853 · outbound

This paper cites The role of auditory and visual cues in the interpretation of mandarin ironic speech,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation The role of auditory and visual cues in the interpretation of mandarin ironic speech,

Reference 1

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raw_fallback, observed 2026-08-11T16:25:15.467913Z

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=2026-08-11T16:25:14.995813Z digest=sha256:c0c147f6b3357e38d60ab610c7de5739abee21422672ada508a00ea1780c3d66

Observation a3af8a30-0d09-4d6a-ac40-bafb33df1fba · outbound

This paper cites Tag questions and common ground effects in the perception of verbal irony,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Tag questions and common ground effects in the perception of verbal irony,

Reference 2

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raw_fallback, observed 2026-08-11T16:25:15.460636Z

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=2026-08-11T16:25:14.998747Z digest=sha256:9baf0b0f3cd4537195a0b2a4e51f7af05a93e6c3fa58c82ec103f4429de03a3c

Observation 37f1f8c3-2e27-493b-9392-f8230c966297 · outbound

This paper cites Asymmetries in the use of verbal irony,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Asymmetries in the use of verbal irony,

Reference 3

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raw_fallback, observed 2026-08-11T16:25:15.453527Z

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=2026-08-11T16:25:15.001140Z digest=sha256:2dc692824a364e6ef3a1e2e9edbde53311acda501d92bf738c7b74b3beebcd97

Observation 011af994-87d6-4517-b85d-cf483e411e4d · outbound

This paper cites Irony and use-mention distinction,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Irony and use-mention distinction,

Reference 4

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raw_fallback, observed 2026-08-11T16:25:15.446404Z

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=2026-08-11T16:25:15.003702Z digest=sha256:9e3571b3a8d602714e9b761d16d8a652e555ab91c4d9be0b216e136ce2aaf3ae

Observation 4bc7de5d-327a-4d3e-abba-21dde377e420 · outbound

This paper cites On the psycholinguistics of sarcasm,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation On the psycholinguistics of sarcasm,

Reference 5

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raw_fallback, observed 2026-08-11T16:25:15.438967Z

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=2026-08-11T16:25:15.006157Z digest=sha256:41492a2f8d9cc08cc0ca71160ffbc87e9f730a5502eda99a0e1cff16033afa6b

Observation ff731b91-a397-4224-99b7-b228b2d8e8ac · outbound

This paper cites How to be sarcastic: The reminder theory of verbal irony,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation How to be sarcastic: The reminder theory of verbal irony,

Reference 6

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raw_fallback, observed 2026-08-11T16:25:15.431666Z

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=2026-08-11T16:25:15.008539Z digest=sha256:dcde907340847847d5513f6ab2382f9407939f919c80b4134b1ea68ff6ed7110

Observation a3808929-604c-4e55-b230-147a4e18c9e2 · outbound

This paper cites Detecting sarcasm in multimodal social platforms,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Detecting sarcasm in multimodal social platforms,

Reference 7

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raw_fallback, observed 2026-08-11T16:25:15.424857Z

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=2026-08-11T16:25:15.010893Z digest=sha256:503e8f20d8306e5956dfdbb37c3dad2f869ba38e28c8e7d44a03b463b29e1c48

Observation 99c27631-c21b-4623-acc6-92956a34c45d · outbound

This paper cites Towards multimodal sarcasm detection (an obviously perfect paper),.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Towards multimodal sarcasm detection (an obviously perfect paper),

Reference 8

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raw_fallback, observed 2026-08-11T16:25:15.417706Z

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=2026-08-11T16:25:15.013700Z digest=sha256:a5a5fc60feb1b2a780f255d5810f2f204d4255a7a5c7d44ff616e8dc05acc2cf

Observation c942762a-6f8f-48c1-9d41-b483b28c6f4f · outbound

This paper cites Modeling incongruity between modalities for multimodal sarcasm detection,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Modeling incongruity between modalities for multimodal sarcasm detection,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.410928Z

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=2026-08-11T16:25:15.016259Z digest=sha256:0fadc895ba71e1373795d1476c9f6e157a3e251ef4421415f684955896bd42bd

Observation b6322f5b-cfeb-4f6d-ab24-1d33eb3f08c1 · outbound

This paper cites Multimodal learning using optimal transport for sarcasm and humor detection,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Multimodal learning using optimal transport for sarcasm and humor detection,

Reference 10

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raw_fallback, observed 2026-08-11T16:25:15.404439Z

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=2026-08-11T16:25:15.018778Z digest=sha256:2e3666fffbb1c0cee0dacbef87ed8b5d391266b6ae0e91db0b9955f9304b4f61

Observation 589325dc-7134-4c75-96d9-cf0a1e9e7f37 · outbound

This paper cites Attention is all you need,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Attention is all you need,

Reference 11

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raw_fallback, observed 2026-08-11T16:25:15.397267Z

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=2026-08-11T16:25:15.021198Z digest=sha256:82816048eea127dd52cc5987298a6b2ae8d5e47ddedb5476f657ccd582075474

Observation 672f9f18-0bec-489d-b804-104e54d82287 · outbound

This paper cites Improving neural machine translation models with monolingual data,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Improving neural machine translation models with monolingual data,

Reference 12

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raw_fallback, observed 2026-08-11T16:25:15.390147Z

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=2026-08-11T16:25:15.024347Z digest=sha256:c534a8dec92110ffc75277936f1439d6fda8a555062e8ff6907f401baaace846

Observation 94918f63-728a-4271-901b-4eab1fbda27d · outbound

This paper cites Improving short text classification through global augmentation methods,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Improving short text classification through global augmentation methods,

Reference 13

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raw_fallback, observed 2026-08-11T16:25:15.382718Z

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=2026-08-11T16:25:15.026891Z digest=sha256:64e8e77a34397efa8584ed7b5406dd9b5acd19b4b6e6116ea529801c2eb58770

Observation 2560e609-8e42-419f-8f17-0f3212bf3a6c · outbound

This paper cites Audio augmentation for speech recognition,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Audio augmentation for speech recognition,

Reference 14

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raw_fallback, observed 2026-08-11T16:25:15.375259Z

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=2026-08-11T16:25:15.029377Z digest=sha256:34df5a297df61bef12f8de098441c031a45eda9f08542a17f17dbdc5591ff515

Observation c2eccb54-98e2-4f55-a7ef-23bfceb4b5f9 · outbound

This paper cites Training Neural Speech Recognition Systems with Synthetic Speech Augmentation.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Training Neural Speech Recognition Systems with Synthetic Speech Augmentation

Reference 15

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local_arxiv, observed 2026-08-11T16:25:15.134001Z

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=2026-08-11T16:25:15.031712Z digest=sha256:4f90e40863c336a3e16c7dacc3af1ec19a133f199497c57e5e8838d7c1240ae9

Observation 77796d90-9938-424a-8124-e95815f91a85 · outbound

This paper cites Mda: Multimodal data aug- mentation framework for boosting performance on sentiment/emotion classification tasks,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Mda: Multimodal data aug- mentation framework for boosting performance on sentiment/emotion classification tasks,

Reference 16

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raw_fallback, observed 2026-08-11T16:25:15.367935Z

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=2026-08-11T16:25:15.034640Z digest=sha256:d432dc8af93802f6fd5b7db96bc597b71a7c922e5ec928b64982257d13da8265

Observation 6277fef8-7567-4396-b6ec-861e25d49e27 · outbound

This paper cites Semantic equivalent adversarial data augmentation for visual question answering,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Semantic equivalent adversarial data augmentation for visual question answering,

Reference 17

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raw_fallback, observed 2026-08-11T16:25:15.360703Z

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=2026-08-11T16:25:15.036958Z digest=sha256:d520f4b0751089226e8a0ce52b1c3a5d1073f4fd3c38dd42a5016f7d0ac88920

Observation 6151f691-31ff-41ef-b974-730628d02514 · outbound

This paper cites When did you become so smart, oh wise one?! sarcasm explanation in multi-modal multi-party dialogues,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation When did you become so smart, oh wise one?! sarcasm explanation in multi-modal multi-party dialogues,

Reference 18

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raw_fallback, observed 2026-08-11T16:25:15.353205Z

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=2026-08-11T16:25:15.039391Z digest=sha256:2b3c0107c4f79eacf65f2c97300c1a1c96de70ffce2635ce384cc00d48eaa0f1

Observation cc4fce41-3ad1-4842-b1d0-08c2b5a43456 · outbound

This paper cites A multimodal corpus for emotion recognition in sarcasm,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation A multimodal corpus for emotion recognition in sarcasm,

Reference 19

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raw_fallback, observed 2026-08-11T16:25:15.345605Z

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=2026-08-11T16:25:15.041841Z digest=sha256:b66099e76ac904154b6330a433566cff7c560b8213097db763d67161b1eac97e

Observation 8d4adca7-0a9a-4035-ba60-a58478bbc76b · outbound

This paper cites A multimodal fusion method for sar- casm detection based on late fusion,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation A multimodal fusion method for sar- casm detection based on late fusion,

Reference 20

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raw_fallback, observed 2026-08-11T16:25:15.338308Z

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=2026-08-11T16:25:15.044239Z digest=sha256:7f15e3b0b9563d6fe12112e0dc0e4e9b4745e3d4419c651d474551a4f2e7905a

Observation ae8d853a-505f-4045-b440-285671836920 · outbound

This paper cites Sarcasm detection using cognitive features of visual data by learning model,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Sarcasm detection using cognitive features of visual data by learning model,

Reference 21

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raw_fallback, observed 2026-08-11T16:25:15.330748Z

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=2026-08-11T16:25:15.046806Z digest=sha256:733724fb5c7dd447fec277957df06846e3811859b74f7b66a9f1f870f048aac6

Observation aa334b37-2a31-4b68-88ee-05fa1d475bea · outbound

This paper cites Sentiment and emotion help sarcasm? a multi-task learning framework for multi-modal sarcasm, sentiment and emotion analysis,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Sentiment and emotion help sarcasm? a multi-task learning framework for multi-modal sarcasm, sentiment and emotion analysis,

Reference 22

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raw_fallback, observed 2026-08-11T16:25:15.323832Z

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=2026-08-11T16:25:15.049228Z digest=sha256:d0492e932a96b7c92f7204fff4149eae0aff2b1c040d97c084573ce9edd88c95

Observation 3fc226d0-cd50-44ee-9979-e47bb2b0291b · outbound

This paper cites Multi-modal sarcasm detection based on contrastive attention mechanism,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Multi-modal sarcasm detection based on contrastive attention mechanism,

Reference 23

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raw_fallback, observed 2026-08-11T16:25:15.316800Z

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=2026-08-11T16:25:15.051640Z digest=sha256:22c87863a8be7750997c413493d6504c6459cd76c7aa3f7479e32dfd72a01270

Observation 52552c91-f99d-4a88-a844-5c2f2094f1a9 · outbound

This paper cites Learning multi-task commonness and uniqueness for multi- modal sarcasm detection and sentiment analysis in conversation,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Learning multi-task commonness and uniqueness for multi- modal sarcasm detection and sentiment analysis in conversation,

Reference 24

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raw_fallback, observed 2026-08-11T16:25:15.310568Z

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=2026-08-11T16:25:15.054132Z digest=sha256:33a82d1ef131697d7db8776676bbbb184bc899ff3b71e71b43316982a83a304f

Observation 38762fa8-43dc-4224-8593-132c41c0b91b · outbound

This paper cites Aggression detection in social media: Using deep neural networks, data augmentation, and pseudo labeling,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Aggression detection in social media: Using deep neural networks, data augmentation, and pseudo labeling,

Reference 25

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raw_fallback, observed 2026-08-11T16:25:15.304167Z

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=2026-08-11T16:25:15.056353Z digest=sha256:6d6ed5aa8f8c5e72793f74f06a7f010f68376930bcceb573249aeb2d810fd05f

Observation 40173f14-f19d-4f52-a58b-35374600dd00 · outbound

This paper cites Augmenting data for sarcasm detection with unlabeled conversation context,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Augmenting data for sarcasm detection with unlabeled conversation context,

Reference 26

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raw_fallback, observed 2026-08-11T16:25:15.297611Z

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=2026-08-11T16:25:15.058857Z digest=sha256:4a5ef30156b76c75c8ad756977907c18caed816e082187b3ac3451663a19072e

Observation 581858eb-3539-4ba2-ab77-98b7bdc773c9 · outbound

This paper cites Deep cnn-based inductive transfer learning for sarcasm detection in speech,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Deep cnn-based inductive transfer learning for sarcasm detection in speech,

Reference 27

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raw_fallback, observed 2026-08-11T16:25:15.290645Z

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=2026-08-11T16:25:15.061279Z digest=sha256:04f109657347d657a1b95e48deaee18dd9ed4fae0044da820f0389a7f9b80ec2

Observation 459e82c5-2e57-46e8-b82c-e8af2f4ee595 · outbound

This paper cites Libritts: A corpus derived from librispeech for text-to- speech,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Libritts: A corpus derived from librispeech for text-to- speech,

Reference 28

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raw_fallback, observed 2026-08-11T16:25:15.283845Z

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=2026-08-11T16:25:15.063734Z digest=sha256:1a954d806e1ae0c1d8abdfc4c9f5f5dcf1efc2513bd65a270bf91bae3fcdc25c

Observation 28183e52-5fdb-4c8a-bb59-5bb3227f347f · outbound

This paper cites Speech recognition with augmented synthesized speech,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Speech recognition with augmented synthesized speech,

Reference 29

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raw_fallback, observed 2026-08-11T16:25:15.276939Z

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=2026-08-11T16:25:15.066159Z digest=sha256:3ec10af7d7660bdc7383d977564314be1e090c67d870c9894b8d02b933b9fd83

Observation 696a6b84-6587-4cf6-bf76-c194c52019ea · outbound

This paper cites Multimodal continuous emotion recognition with data augmentation using recurrent neural networks,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Multimodal continuous emotion recognition with data augmentation using recurrent neural networks,

Reference 30

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raw_fallback, observed 2026-08-11T16:25:15.269725Z

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=2026-08-11T16:25:15.068667Z digest=sha256:f1f7ee505adf17d2466210701c3416325b7c444b6590fab64729f09af2b726e7

Observation 68374653-bdca-48c0-94f7-834968904011 · outbound

This paper cites Mixgen: A new multi-modal data augmentation,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Mixgen: A new multi-modal data augmentation,

Reference 31

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raw_fallback, observed 2026-08-11T16:25:15.262872Z

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=2026-08-11T16:25:15.071061Z digest=sha256:2e11d3fdbb3468a2abacb804efa2b034cba9a0a29be8cca5b6c6533edab4cfb7

Observation 96d2cef3-35b9-410b-80ae-f023cc253c8b · outbound

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

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 32

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raw_fallback, observed 2026-08-11T16:25:15.256084Z

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=2026-08-11T16:25:15.073542Z digest=sha256:293a335fc0b2c1c78924d61d5a7adc29340bba23e92d62d7856c72c154371619

Observation fe14560c-380f-432d-8bcb-6cab1197b1ff · outbound

This paper cites Cnn architectures for large-scale audio classifica- tion,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Cnn architectures for large-scale audio classifica- tion,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.249722Z

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=2026-08-11T16:25:15.076121Z digest=sha256:36d6d3e273060678b385f0504d740fb0877969a6877b5cc1ca7980d0a886d7dc

Observation 02e609c3-fcf0-420a-a830-8eef79e7fd24 · outbound

This paper cites Inves- tigating on incorporating pretrained and learnable speaker representa- tions for multi-speaker multi-style text-to-speech,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Inves- tigating on incorporating pretrained and learnable speaker representa- tions for multi-speaker multi-style text-to-speech,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.243349Z

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=2026-08-11T16:25:15.078726Z digest=sha256:ad5ab6d9e85e72142d435128c06a43138395cc0ec3df578e04620d938f768302

Observation df97f711-d9ae-4865-a977-84681af7b4de · outbound

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

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Adam: A method for stochastic optimization,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.236743Z

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=2026-08-11T16:25:15.081330Z digest=sha256:de5be81e82725848a04dabe55bbbd6541c2905b1ae18d731b382f8622538fad3

Observation 35fb4d61-840f-4a0e-8ab3-7993ad49ce59 · outbound

This paper cites Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.230612Z

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=2026-08-11T16:25:15.083783Z digest=sha256:24a3fb5be89f0aff17fb24e8e24a4d9c3a84839abf30f2235707a2ba11e4eafc

Observation d3217630-5e62-4c4d-a718-8231968b9bf4 · outbound

This paper cites A quantum probability driven frame- work for joint multi-modal sarcasm, sentiment and emotion analysis,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation A quantum probability driven frame- work for joint multi-modal sarcasm, sentiment and emotion analysis,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.224418Z

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=2026-08-11T16:25:15.086275Z digest=sha256:bc927d9c6156e6b495aca085f459faabac2a895a1d2648285e8e51028f005b63

Observation 3d6f2f75-f484-4b4c-8bc6-671283239b84 · outbound

This paper cites A multitask learning model for multimodal sarcasm, sentiment and emotion recognition in conversations,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation A multitask learning model for multimodal sarcasm, sentiment and emotion recognition in conversations,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.217817Z

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=2026-08-11T16:25:15.088830Z digest=sha256:3c2652af40112f718b1ee1b30242501ca22eae19305ca88add63bdbfe357dd51

Observation 39cac452-b4b7-4dc6-86d7-22a92ab0a5bc · outbound

This paper cites Support-vector networks,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Support-vector networks,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.210377Z

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=2026-08-11T16:25:15.091660Z digest=sha256:77ce084e8ee9ed6adfd28c7424bcce8c7e1a33623ea9fab2f07ce45495772741

Observation dfc334ec-60e8-4cf4-83f9-f990682b0eff · outbound

This paper cites An emoji-aware multitask framework for multimodal sarcasm detec- tion,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation An emoji-aware multitask framework for multimodal sarcasm detec- tion,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.203218Z

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=2026-08-11T16:25:15.094107Z digest=sha256:42ede3bf1431e17055ce84e0040b37f007146bd43061e323e6e16b792dcaa64b

Observation 8e534eda-a7c5-40f9-97d5-658d009f8cdf · outbound

This paper cites Dropout: A simple way to prevent neural networks from overfit- ting,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Dropout: A simple way to prevent neural networks from overfit- ting,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.195532Z

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=2026-08-11T16:25:15.096161Z digest=sha256:14a153cafccb34d732eb19e5b1f6730ece23620ee2788f70453ec881727ab77a

Observation ad64ca7f-7248-43cd-a67e-62b1ec82421d · outbound

This paper cites Rectified linear units improve restricted boltzmann machines,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Rectified linear units improve restricted boltzmann machines,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.187810Z

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=2026-08-11T16:25:15.098247Z digest=sha256:b917e34b796a5e8b12f934f4126c77e356b149d389ff70c1b14671f3fcf8a8a3

Observation 900591c8-30bc-407b-9181-30a21921d665 · outbound

This paper cites Glove: Global vectors for word representation,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Glove: Global vectors for word representation,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.179932Z

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=2026-08-11T16:25:15.100546Z digest=sha256:5d5d39d51584c4f7545d662fb3ada808adbc420afb635d8c3338696c29cc7ea8

Observation 4e880068-fa80-4555-8dc6-c946fa54829f · outbound

This paper cites Generative emotional ai for speech emotion recognition: The case for synthetic emotional speech augmen- tation,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Generative emotional ai for speech emotion recognition: The case for synthetic emotional speech augmen- tation,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.172061Z

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=2026-08-11T16:25:15.102838Z digest=sha256:967de9b00a6dc0859b1078f7d101efcebfc7726d8950e9e6f35bd9b53909269e

Observation 13ae927c-7329-4429-a796-7f4938bd4572 · outbound

This paper cites Multimodal markers of irony and sarcasm,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Multimodal markers of irony and sarcasm,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.164111Z

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=2026-08-11T16:25:15.105165Z digest=sha256:ce13c5d1a90c858920093c9063c47ab9b4f0855a6efa88596657009180412975

Observation d4dcd561-23c7-40a7-bc63-dd617e4d1496 · outbound

This paper cites Exploring the role body in communicating ironic stance,.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation Exploring the role body in communicating ironic stance,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.156301Z

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=2026-08-11T16:25:15.107305Z digest=sha256:dd406afe9adfd3fe60a70d76b778fafb37c8f0164aa1dc6267ad937a665cc869

Observation 6673d39f-fb84-412c-aaf9-b395f24cf398 · outbound

This paper cites In 2012, he returned to academia.

AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation In 2012, he returned to academia

Reference 2010

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:25:15.146405Z

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=2026-08-11T16:25:15.109673Z digest=sha256:ac9b0b02070d1694b26c8ce8cd57effa1d643ed3ff160d18df32513dd3b46e74

Pith citing papers

Observation c0d13b66-e23b-41ef-a16c-bf067146fd0e · inbound

Leveraging Large Language Models for Sarcastic Speech Annotation in Sarcasm Detection cites this paper.

Leveraging Large Language Models for Sarcastic Speech Annotation in Sarcasm Detection AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:32:17.505994Z

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=2026-05-19T11:29:56.464755Z digest=sha256:9c1bd1ea674fb0220df651ccf3cf8ae926ce571741c3d6bbc03df168cf15eb85

Observation d39fdd61-4a0d-4b3b-9ce7-b4ca7562b000 · inbound

ProSarc: Prosody-Aware Sarcasm Recognition Framework via Temporal Prosodic Incongruity cites this paper.

ProSarc: Prosody-Aware Sarcasm Recognition Framework via Temporal Prosodic Incongruity AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-06-28T01:21:28.325838Z

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=2026-06-28T01:20:28.456854Z digest=sha256:881cc92bb5e77c07afaa719c9be8cc3f217570a7162025bee371408ed6300d63

Observation cdd85dea-cfd5-4cb2-b1e1-56fe75b84106 · inbound

CHARM: Charge Calibration and Acoustic Rescue for LLM-based Multimodal Sarcasm Detection cites this paper.

CHARM: Charge Calibration and Acoustic Rescue for LLM-based Multimodal Sarcasm Detection AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-14T07:04:04.812401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T07:04:04.812401Z digest=sha256:1f6a2479af64508e3c0cd0d3e7229c4612dc2afe682a2a3e69713ed1860f94ad