Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition | Paper Citation Record

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This paper cites Optimal and privacy-aware resource management in artificial intelligence of things using osmotic computing,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Optimal and privacy-aware resource management in artificial intelligence of things using osmotic computing,

Reference 1

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This paper cites Empowering things with intelligence: A survey of the progress, challenges, and opportunities in artificial intelligence of things,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Empowering things with intelligence: A survey of the progress, challenges, and opportunities in artificial intelligence of things,

Reference 2

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This paper cites Enable deep learning on mobile devices: Methods, systems, and applications,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Enable deep learning on mobile devices: Methods, systems, and applications,

Reference 3

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This paper cites Tinyad: Memory- efficient anomaly detection for time series data in industrial iot,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Tinyad: Memory- efficient anomaly detection for time series data in industrial iot,

Reference 4

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This paper cites Real-time speech emotion analysis for smart home assistants,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Real-time speech emotion analysis for smart home assistants,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.516712Z

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Observation df2f0f5b-f2ac-4e0c-a249-e3da27f29189 · outbound

This paper cites Speech emotion detection using iot based deep learning for health care,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Speech emotion detection using iot based deep learning for health care,

Reference 6

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This paper cites Iot-enabled WBAN and machine learning for speech emotion recognition in patients,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Iot-enabled WBAN and machine learning for speech emotion recognition in patients,

Reference 7

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Observation f4918b85-ff9b-4f19-9c5a-e1524cd61756 · outbound

This paper cites Emotion-aware connected health- care big data towards 5g,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Emotion-aware connected health- care big data towards 5g,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.472840Z

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This paper cites Attention is all you need,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Attention is all you need,

Reference 9

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This paper cites Pre-trained models for natural language processing: A survey,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Pre-trained models for natural language processing: A survey,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.443769Z

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This paper cites Transformers in vision: A survey,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Transformers in vision: A survey,

Reference 11

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This paper cites Dawn of the transformer era in speech emotion recognition: Closing the valence gap,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Dawn of the transformer era in speech emotion recognition: Closing the valence gap,

Reference 12

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Observation 1e8f8255-ed1b-42b6-a385-f9ab9300e2b8 · outbound

This paper cites A Survey of Large Language Models.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition A Survey of Large Language Models

Reference 13

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This paper cites Language models are few-shot learners,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Language models are few-shot learners,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.398990Z

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This paper cites PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing

Reference 15

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This paper cites Training Compute-Optimal Large Language Models.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Training Compute-Optimal Large Language Models

Reference 16

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This paper cites Model compression and hardware acceleration for neural networks: A comprehensive survey,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Model compression and hardware acceleration for neural networks: A comprehensive survey,

Reference 17

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This paper cites Federated learning: Challenges, methods, and future directions,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Federated learning: Challenges, methods, and future directions,

Reference 18

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Observation bc80056e-e43f-4cc1-a05f-ed6a2f09bc99 · outbound

This paper cites Efficient acceleration of deep learning inference on resource-constrained edge devices: A review,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Efficient acceleration of deep learning inference on resource-constrained edge devices: A review,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.353567Z

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This paper cites Toward tailored models on private aiot devices: Federated direct neural architecture search,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Toward tailored models on private aiot devices: Federated direct neural architecture search,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.338985Z

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This paper cites Compressing large-scale transformer-based models: A case study on bert,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Compressing large-scale transformer-based models: A case study on bert,

Reference 21

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This paper cites Efficient transformers: A survey,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Efficient transformers: A survey,

Reference 22

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This paper cites Pruning deep neural networks by opti- mal brain damage,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Pruning deep neural networks by opti- mal brain damage,

Reference 23

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This paper cites An efficient framework for counting pedestrians crossing a line using low-cost devices: the benefits of distilling the knowledge in a neural network,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition An efficient framework for counting pedestrians crossing a line using low-cost devices: the benefits of distilling the knowledge in a neural network,

Reference 24

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This paper cites Linformer: Self-Attention with Linear Complexity.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Linformer: Self-Attention with Linear Complexity

Reference 25

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This paper cites WakeUpNet: A Mobile-Transformer based Framework for End-to-End Streaming Voice Trigger.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition WakeUpNet: A Mobile-Transformer based Framework for End-to-End Streaming Voice Trigger

Reference 26

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This paper cites From hard to soft: Towards more human-like emotion recognition by modelling the perception uncertainty,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition From hard to soft: Towards more human-like emotion recognition by modelling the perception uncertainty,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.263353Z

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This paper cites The power of interpolation: Under- standing the effectiveness of SGD in modern over-parametrized learn- ing,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition The power of interpolation: Under- standing the effectiveness of SGD in modern over-parametrized learn- ing,

Reference 30

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This paper cites Multi-head atten- tion for speech emotion recognition with auxiliary learning of gender recognition,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Multi-head atten- tion for speech emotion recognition with auxiliary learning of gender recognition,

Reference 31

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This paper cites The INTER- SPEECH 2013 computational paralinguistics challenge: Social signals, conflict, emotion, autism,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition The INTER- SPEECH 2013 computational paralinguistics challenge: Social signals, conflict, emotion, autism,

Reference 32

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This paper cites Self-attention for speech emotion recognition,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Self-attention for speech emotion recognition,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.203779Z

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This paper cites Speechformer: A hierarchical efficient framework incorporating the characteristics of speech,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Speechformer: A hierarchical efficient framework incorporating the characteristics of speech,

Reference 34

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This paper cites Dwformer: Dynamic window transformer for speech emotion recognition,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Dwformer: Dynamic window transformer for speech emotion recognition,

Reference 35

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This paper cites A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding

Reference 36

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This paper cites Are sixteen heads really better than one?.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Are sixteen heads really better than one?

Reference 37

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This paper cites Analyzing multi-head self-attention: Specialized heads do the heavy lifting, the rest can be pruned,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Analyzing multi-head self-attention: Specialized heads do the heavy lifting, the rest can be pruned,

Reference 38

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This paper cites When BERT plays the lottery, all tickets are winning,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition When BERT plays the lottery, all tickets are winning,

Reference 39

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This paper cites Earlybert: Efficient bert training via early-bird lottery tickets,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Earlybert: Efficient bert training via early-bird lottery tickets,

Reference 40

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This paper cites Reducing Transformer Depth on Demand with Structured Dropout.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Reducing Transformer Depth on Demand with Structured Dropout

Reference 41

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This paper cites On the effect of dropping layers of pre-trained transformer models,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition On the effect of dropping layers of pre-trained transformer models,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:49.101219Z

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This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 43

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This paper cites Tinybert: Distilling BERT for natural language understanding,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Tinybert: Distilling BERT for natural language understanding,

Reference 44

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This paper cites Mobilebert: a compact task-agnostic BERT for resource-limited devices,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Mobilebert: a compact task-agnostic BERT for resource-limited devices,

Reference 45

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This paper cites Distilhubert: Speech representation learning by layer-wise distillation of hidden-unit bert,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Distilhubert: Speech representation learning by layer-wise distillation of hidden-unit bert,

Reference 46

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This paper cites Fmmformer: Efficient and flexible transformer via decomposed near- field and far-field attention,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Fmmformer: Efficient and flexible transformer via decomposed near- field and far-field attention,

Reference 47

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This paper cites Is attention better than matrix decomposition?.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Is attention better than matrix decomposition?

Reference 48

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This paper cites DRONE: data- aware low-rank compression for large NLP models,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition DRONE: data- aware low-rank compression for large NLP models,

Reference 49

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This paper cites Lightweight and efficient end-to-end speech recognition using low-rank transformer,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Lightweight and efficient end-to-end speech recognition using low-rank transformer,

Reference 50

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Observation f6e5e4df-f59f-4174-954b-17c04a202201 · outbound

This paper cites A t2-tensor-aided multiscale transformer for remaining useful life prediction in iiot,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition A t2-tensor-aided multiscale transformer for remaining useful life prediction in iiot,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.980711Z

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Observation e902a9fb-b46e-41fe-9181-a48bbaadb1c9 · outbound

This paper cites Expandnets: Linear over- parameterization to train compact convolutional networks,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Expandnets: Linear over- parameterization to train compact convolutional networks,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.966159Z

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Observation 26cb931c-7252-4d42-a70d-9257ea30fd0d · outbound

This paper cites Repvgg: Making vgg-style convnets great again,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Repvgg: Making vgg-style convnets great again,

Reference 53

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Observation d6fe245b-b8d4-464c-9cd5-08ba609495a3 · outbound

This paper cites Acnet: Strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Acnet: Strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.937791Z

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Observation 96d116f8-07d9-4ead-92b0-1a9dda813c17 · outbound

This paper cites Transformer-Transducer: End-to-End Speech Recognition with Self-Attention.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Transformer-Transducer: End-to-End Speech Recognition with Self-Attention

Reference 55

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Observation b2c3ffb1-0b89-4372-bbff-c122f8338de6 · outbound

This paper cites Conformer: Convolution-augmented transformer for speech recognition,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Conformer: Convolution-augmented transformer for speech recognition,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.923004Z

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Observation 6b6ca1e8-c053-4d96-936a-64d47611e801 · outbound

This paper cites On the optimization of deep net- works: Implicit acceleration by overparameterization,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition On the optimization of deep net- works: Implicit acceleration by overparameterization,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.907553Z

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Observation e512d6dc-b6cd-43e9-9111-0a7679f48985 · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Scaling Laws for Autoregressive Generative Modeling

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T20:49:48.363877Z

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Observation 98323bc2-63e5-44db-8827-9b454f2bc8fc · outbound

This paper cites Scaling Laws for Neural Language Models.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Scaling Laws for Neural Language Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T20:49:48.368529Z

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Observation 6d4d7072-44cf-4447-918e-dc0647c00a8e · outbound

This paper cites Scaling Laws for Transfer.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Scaling Laws for Transfer

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T20:49:48.373303Z

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Observation 4d83ffc5-56c8-48fb-9fb8-b0aa91a996f7 · outbound

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

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Iemocap: interactive emotional dyadic motion capture database,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.892784Z

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Observation 2f92b599-3845-481b-8675-8eee41466e9f · outbound

This paper cites M3ed: Multi-modal multi-scene multi-label emotional dialogue database,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition M3ed: Multi-modal multi-scene multi-label emotional dialogue database,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.877841Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6230e755-8a19-4562-933d-cc2064ca90b0 · outbound

This paper cites The distress analysis interview corpus of human and computer interviews,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition The distress analysis interview corpus of human and computer interviews,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.862591Z

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Observation f56feb4d-b8b0-4460-822e-6ad2f10311da · outbound

This paper cites Emotion recognition with multimodal transformer fusion framework based on acoustic and lexical information,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Emotion recognition with multimodal transformer fusion framework based on acoustic and lexical information,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.848094Z

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Observation b745b628-59de-4675-9ff0-aaacc1a29474 · outbound

This paper cites Lr-gcn: Latent relation-aware graph convolutional network for conversational emotion recognition,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Lr-gcn: Latent relation-aware graph convolutional network for conversational emotion recognition,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.833442Z

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Observation ec0d54a0-36f9-4ba8-9acd-7a9e28ad5cbd · outbound

This paper cites Semantic alignment network for multi-modal emotion recognition,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Semantic alignment network for multi-modal emotion recognition,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.818381Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b1dd5587-5b70-4d24-8234-ae68a06d4c49 · outbound

This paper cites Learning and generalization in overparameterized neural networks,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Learning and generalization in overparameterized neural networks,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.803222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 362273d8-e110-4762-af1e-49d45c0f0022 · outbound

This paper cites A convergence theory for deep learn- ing via over-parameterization,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition A convergence theory for deep learn- ing via over-parameterization,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.787266Z

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Observation ae88e96f-3db0-40fc-94ac-b79b23e1222b · outbound

This paper cites Representation learning with spectro-temporal-channel attention for speech emotion recognition,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Representation learning with spectro-temporal-channel attention for speech emotion recognition,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.772120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation aac0533c-a036-4fcf-9438-8cfe35b37e48 · outbound

This paper cites Exploiting vocal tract coordination using dilated cnns for depression detection in naturalistic environments,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Exploiting vocal tract coordination using dilated cnns for depression detection in naturalistic environments,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.755660Z

Source-reported events for the cited work

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Observation 00ed2d0b-2890-4129-91ad-b5df834930f4 · outbound

This paper cites Towards robust deep neural networks for affect and depres- sion recognition from speech,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Towards robust deep neural networks for affect and depres- sion recognition from speech,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.738308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cfc25ecb-beed-4445-b649-533974eb26ba · outbound

This paper cites Hybrid cnn-svm classifier for efficient depression detection system,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Hybrid cnn-svm classifier for efficient depression detection system,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.722859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 428e12eb-96eb-4bc6-b8e6-408dfae49ae0 · outbound

This paper cites The detection of depression using multimodal models based on text and voice quality features,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition The detection of depression using multimodal models based on text and voice quality features,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.706540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3de48a96-35e1-4f7a-bcea-220d9bcc0017 · outbound

This paper cites Double trouble in double descent: Bias and variance(s) in the lazy regime,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Double trouble in double descent: Bias and variance(s) in the lazy regime,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.690850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 55f800ce-4d05-434c-b82d-8f9e17a8f211 · outbound

This paper cites Deep double descent: Where bigger models and more data hurt,.

Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Deep double descent: Where bigger models and more data hurt,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:49:48.675154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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