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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 11 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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:14.995813Z digest=sha256:830771c1ebd6d9f66736215f0a6b543a50c4feffe523de56ab1bc56f9aa9de01

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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verified fuzzy
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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:14.998747Z digest=sha256:1c695d4c358c29e189048f9ec90b47b5c87c97c62543a38a40f42670c22efdf6

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.001140Z digest=sha256:feb69c2dca77f6399d711f28f0126cd2f19600051eeb9ef5f37f9a9e67ea2068

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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verified fuzzy
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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.003702Z digest=sha256:abbbaa5e1404814c817607ccf37cb3baafc7ba602b7fab61238b062a8ad53444

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.006157Z digest=sha256:1fea571d51762ac96f839c7a7c47d58ffaf81359b0087ea48e1a0749170ba8cb

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.008539Z digest=sha256:2f405525996610da563a9ab99a2bc23813313f78c32e5029b7260f41018256be

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.010893Z digest=sha256:f0ef4fdac3c933d1a4846273a78fae9518ee056ad413dec2344c3318f72691ea

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.013700Z digest=sha256:fc48c3231f704ace05bd2a82a22cac936a547128bf78af1ae710a196b2766858

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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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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.016259Z digest=sha256:9b7d2782ab4c4887cc487e99f2a9f6575c674f9b2aab642fa2423b0de5fbbf21

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.018778Z digest=sha256:48e7e6fbbd4c063afa1fc7fb0f04f32e4e5adeff70dde75dd7679aefbf43f6b9

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.021198Z digest=sha256:7d79bcd61aeb316907853ec3468120947cdab615469ee94426cc7944c8be2896

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.024347Z digest=sha256:530190002b4477843f42278866f762736a9f31460b5a982dc33d5c344604847d

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.026891Z digest=sha256:70a297ad102cf5c05116f5c0f7d172055655376b49252c0150413f848abeeb61

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.029377Z digest=sha256:272f8469d6a6738aff666c664f9f20746b0afc472dc29e11f30af4e925c0d463

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.031712Z digest=sha256:53574137cb05d1c0615246df22b2d9977e614e7a6bb8fccf39d3a17622a77f7c

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.034640Z digest=sha256:789a6541a7ca38aa648517f5d93bf40e4d44ef9cd9c8fa58b78b25324babafe7

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.036958Z digest=sha256:d3376834f16a7a54a531333e1a102cadeea3d9d4b94efbda26a04e88a07a5b1e

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.039391Z digest=sha256:81392e52074bef962d0c24f3e8c4a5ec1560f22bb12f5387c05e1d3fab312238

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.041841Z digest=sha256:e2293d80f8f30e52b70a74a191738fd3f4ebd3efd8aff056bb47081d04874165

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.044239Z digest=sha256:04840345c76b04f2a4f6e804cafd6a7e827b5a71288fff5b3dc36c22d0087e92

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.046806Z digest=sha256:c42c27a1368ba303bbe386ecf42b596ce1f9fbe1f2161859d626ed173bcc2109

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.049228Z digest=sha256:3812bcc9492a6233961693c930bf7716887f5dde64da3a80f76726e02311dceb

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.051640Z digest=sha256:4e5aa420799524c866e99b80773cacbe17834b347d6f57c4ed0b3430dcfdaa57

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.054132Z digest=sha256:7e55aed843062df23834f677b1853de2ee45d4ff3d91dff88ff0afb2e1dca6ed

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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verified fuzzy
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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.056353Z digest=sha256:73ef073997e90109c499d02fb5c642a05514cf6b2968b316c97904ef3d009e73

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.058857Z digest=sha256:672c75bfd74b67fb8c8d6a9d6fb98f038e9951312ac6d70fcb953f17de8aa3d8

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.061279Z digest=sha256:45395fa6f471e22cb81e7a51a43400b151b41443df71cf4a843ba633ccdc0b00

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.063734Z digest=sha256:adf36d464e45fdda0f34e81e870436142a84e68a81161d67b21902d3d68e1211

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.066159Z digest=sha256:fc98d5c9a79a041f5c5c87a1e2a990172e2bfe80630f924224fe9c22951e9bbe

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.068667Z digest=sha256:97301621bcc2586f69d9f949870b26913caba2be517ab8f4aa0f0bee8029000a

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.071061Z digest=sha256:f7b8cdabaa5d0850636fbdc0428dd7543fd735aa9e6caa116e92823f24b767b0

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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verified fuzzy
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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.073542Z digest=sha256:e9f66262c8e83ab983ac15a4994628aa1afe4d8682f3ae587fbce0522c702f62

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.076121Z digest=sha256:563736de79b65145f6ffc901d408afbc2f08e2840a330a0fe316a9eacabf2b74

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.078726Z digest=sha256:39f313be65484fbe032e3e20a01689730d46d066a0c9f215acf1396eaa940161

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.081330Z digest=sha256:977fd2674ce5c3370138c6c3202faaba966e8513f9fcf662001b41db9b8e9935

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.083783Z digest=sha256:29d81be053b6172dcf203047f1d3dc5d44a4d9932447d05ccd0875e2820bc3fc

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.086275Z digest=sha256:f872b14248e50d82411ae651a96dbfbb16be36a26a9cf978d9b34a1a85069801

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.088830Z digest=sha256:1b607024aaab56999a2522567bc37daf9e65b29a6f414820f9245a4c3b4caf89

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.091660Z digest=sha256:d3ae31465b7a5a98b67729032746b8798c0921b76c27924c30652bd64da3829e

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.094107Z digest=sha256:05bf1df5f37321a279998a3fd682bf392b152742a35a72e6762b9d00c24ebe2f

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.096161Z digest=sha256:39e1973cb384ae97d8a23f2feaf92ad264b6c0c957a751e4b907721d21fd5dcf

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.098247Z digest=sha256:187348e8f71f03d2bc290f6c5cc2371414905bb11742483bda6fc5ad357deef3

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.100546Z digest=sha256:ff2e26bcb4b4ebd09bc9b7652f809852884d9928f1830e5abd5b307f09e733b6

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.102838Z digest=sha256:baa791d7b99683f77f90a3f8348b17e1aa354e57e28a3cffe82d59012d657103

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.105165Z digest=sha256:d546cbaede9dfe95d33e2875fba4ecd5b5812383cf99a799fae30e922c59d1f0

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.107305Z digest=sha256:5ec42e694dc0867090b2deff2f7c35e09734c28342785f88c4c2c40c7c091401

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T16:25:15.109673Z digest=sha256:0086a82bab5aff79c85a8729ff9eacc3d0aaef73ffab07496a7bd3e49ba39cc3

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-19T11:29:56.464755Z digest=sha256:9617427ff0b938c7f5a9034dde4ac2e2afa4f30f155953bdfda13e230e643f0c

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-28T01:20:28.456854Z digest=sha256:ce067fc4852a3917a546f0b658f7de778dd52827d5a37afd80cc9bedd562dbec

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:e8fb92a698a1f429c8717d37a417fa4183487a28386c3d453e881f2e1b790d5c