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Paper Citation Record · LEDGER

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning

As of 15 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2606.02998.

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

pith.paper-citation-record.v1
2606.02998 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

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measured 30 of 30 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

30 of 30 outbound references displayed

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Outbound references

Observation 0fc107fe-64d3-4077-9d6b-353b6bfcf027 · outbound

This paper cites Global Health Estimates: Leading Causes of Disease Burden.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Global Health Estimates: Leading Causes of Disease Burden

Reference 1

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Observation 845edae4-c6e5-4beb-94eb-b48b07a93d1a · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Robust speech recognition via large-scale weak supervision

Reference 2

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Observation fae1dc53-12fb-4671-9335-7850d4b5bd7d · outbound

This paper cites Coswara: a database of breathing, cough, and voice sounds for COVID-19 diagnosis.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Coswara: a database of breathing, cough, and voice sounds for COVID-19 diagnosis

Reference 3

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Observation 60bf5c51-6c3b-45b5-9cbd-c65b65233c06 · outbound

This paper cites The CoughVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms.Sci Data.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning The CoughVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms.Sci Data

Reference 4

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Observation 90973744-e854-4a7b-8fea-ac5f796ef123 · outbound

This paper cites Virufy: Global Applicability of Crowdsourced and Clinical Datasets for AI Detection of COVID-19 from Cough.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Virufy: Global Applicability of Crowdsourced and Clinical Datasets for AI Detection of COVID-19 from Cough

Reference 5

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

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Observation 5d0da243-627b-4c66-9e9c-66c40275728e · outbound

This paper cites Analysis of pediatric cough sounds for bronchitis and pneumonia diagnosis.Figshare; 2022.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Analysis of pediatric cough sounds for bronchitis and pneumonia diagnosis.Figshare; 2022

Reference 6

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doi, observed 2026-06-28T12:22:07.923872Z

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Observation d0d9fd4d-ec20-4fb4-8073-195d525f9d0a · outbound

This paper cites Towards open respiratory acoustic foundation models: pretraining and benchmarking.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Towards open respiratory acoustic foundation models: pretraining and benchmarking

Reference 7

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Observation bec63797-5fd3-45bd-8875-5061f070d7d4 · outbound

This paper cites Supervised contrastive learning.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Supervised contrastive learning

Reference 8

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Observation acd5fccb-d247-4991-a32c-bc2669ef4431 · outbound

This paper cites Mixup: Beyond empirical risk minimization.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Mixup: Beyond empirical risk minimization

Reference 9

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Observation cfa99b59-788d-4d83-8456-4750fa7f55ce · outbound

This paper cites Balanced-mixup for highly imbalanced medical image classification.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Balanced-mixup for highly imbalanced medical image classification

Reference 10

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Observation c5787320-20d1-4cbf-933a-d883533c51e2 · outbound

This paper cites Focal loss for dense object detection.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Focal loss for dense object detection

Reference 11

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Observation de7bc8b6-cfd7-4f4b-8a64-44faa9102256 · outbound

This paper cites FiLM: Visual reasoning with a general conditioning layer.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning FiLM: Visual reasoning with a general conditioning layer

Reference 12

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Observation 421b6740-d359-428c-9bc8-4ccb25df8f31 · outbound

This paper cites Domain-adversarial training of neural networks.J Mach Learn Res.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Domain-adversarial training of neural networks.J Mach Learn Res

Reference 13

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Observation 4eb84989-d546-408c-9ad6-3e0445b54d8c · outbound

This paper cites EfficientNet: Rethinking model scaling for convolutional neural networks.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning EfficientNet: Rethinking model scaling for convolutional neural networks

Reference 14

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Observation 1f4d4774-9544-441e-8f19-f23c1efb52c9 · outbound

This paper cites Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation

Reference 15

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Observation d9a4ea0a-037e-4c02-ac5b-1098574495f9 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning wav2vec 2.0: A framework for self-supervised learning of speech representations

Reference 16

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Observation 221102d7-3a3a-4cce-b53b-d0fb9954b8d5 · outbound

This paper cites HuBERT: Self-supervised speech representation learn- ing by masked prediction of hidden units.IEEE/ACM Trans Audio Speech Lang Process.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning HuBERT: Self-supervised speech representation learn- ing by masked prediction of hidden units.IEEE/ACM Trans Audio Speech Lang Process

Reference 17

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Observation 4fdf910d-42a6-4b05-b6c2-f47d73875eaf · outbound

This paper cites Exploring automatic diagnosis of COVID-19 from crowdsourced respiratory sound data.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Exploring automatic diagnosis of COVID-19 from crowdsourced respiratory sound data

Reference 18

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Observation 68505f60-38fc-4786-a79b-025a4e13774a · outbound

This paper cites COVID-19 artificial intelligence diagnosis using only cough recordings.IEEE Open J Eng Med Biol.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning COVID-19 artificial intelligence diagnosis using only cough recordings.IEEE Open J Eng Med Biol

Reference 19

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Observation eb34f4b0-d98c-4d16-8a33-c2f76abed21c · outbound

This paper cites Whisper-AuT: Domain-Adapted Audio Encoder for Efficient Audio-LLM Training.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Whisper-AuT: Domain-Adapted Audio Encoder for Efficient Audio-LLM Training

Reference 20

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Observation acfe6f40-f53f-4306-b3a8-902a693fa93c · outbound

This paper cites Masked autoencoders that listen.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Masked autoencoders that listen

Reference 21

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Observation b0fafade-5388-4af9-b24b-141272a022d7 · outbound

This paper cites PANNs: Large-scale pretrained audio neural networks for audio pattern recognition.IEEE/ACM Trans Audio Speech Lang Process.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning PANNs: Large-scale pretrained audio neural networks for audio pattern recognition.IEEE/ACM Trans Audio Speech Lang Process

Reference 22

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Observation d2155b71-d1e7-4b3f-9b2b-6baa9c76ff4b · outbound

This paper cites BEATs: Audio pre-training with acoustic tokenizers.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning BEATs: Audio pre-training with acoustic tokenizers

Reference 23

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source=pdf_text observed=2026-06-28T11:44:14.720062Z digest=sha256:33c87ab8f335f97dfa543781e0f63b50fe45ce9394267e7336731f1db8041cea

Observation 26b47914-bad0-4c8d-b730-a1ccf601ccbd · outbound

This paper cites Automated cough detection and classification using spectral features.IEEE J Biomed Health Inform.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Automated cough detection and classification using spectral features.IEEE J Biomed Health Inform

Reference 24

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Observation 040f854a-e137-4db2-b707-e743c0d29bcd · outbound

This paper cites Automatic identification of voluntary cough sound features for diagnosis of respiratory diseases.IEEE Trans Biomed Eng.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Automatic identification of voluntary cough sound features for diagnosis of respiratory diseases.IEEE Trans Biomed Eng

Reference 25

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Observation 0720161f-6369-4689-b544-4861729dedf9 · outbound

This paper cites Adjusted learning of convolutional neural networks for multi-condition speech pathology detection.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Adjusted learning of convolutional neural networks for multi-condition speech pathology detection

Reference 26

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Observation e552bb18-687b-4606-991f-cc73c7879720 · outbound

This paper cites SGDR: Stochastic gradient descent with warm restarts.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning SGDR: Stochastic gradient descent with warm restarts

Reference 27

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Observation 7f4a9617-bf57-4b15-96bf-ff9d9fd23f8b · outbound

This paper cites Decoupled weight decay regularization.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning Decoupled weight decay regularization

Reference 28

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Observation ed515fa1-e4e9-4091-8784-f404471bc7b5 · outbound

This paper cites SpecAugment: A simple data augmentation method for automatic speech recognition.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning SpecAugment: A simple data augmentation method for automatic speech recognition

Reference 29

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Observation c145da53-e12b-4870-88ad-712346a488f5 · outbound

This paper cites librosa: Audio and music signal analysis in Python.

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning librosa: Audio and music signal analysis in Python

Reference 30

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Pith citing papers

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