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Paper Citation Record · LEDGER

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection

As of 8 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2509.09175.

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

pith.paper-citation-record.v1
2509.09175 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:37:29.997581Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T10:28:22.453820Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

62 of 62 outbound references displayed

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Outbound references

Observation 9e61517d-83b6-4862-8bba-dccecbbcc6d9 · outbound

This paper cites Asvspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Asvspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale,

Reference 1

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Observation d8ae4f8c-4df6-4b5d-8834-a4d75741dc7b · outbound

This paper cites CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models

Reference 2

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source=pdf_text observed=2026-08-04T19:37:26.488189Z digest=sha256:dd0a18b4c9830c39c78f3cc2fcc1ac577c29feaa29b8795005c1d792c25ae1c2

Observation 50776e04-6bb1-4881-bbc5-32fb62cf93c9 · outbound

This paper cites Aasist3: Kan-enhanced aasist speech deepfake detection using ssl features and additional regularization for the asvspoof 2024 challenge,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Aasist3: Kan-enhanced aasist speech deepfake detection using ssl features and additional regularization for the asvspoof 2024 challenge,

Reference 3

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Observation 22c6a242-7c07-4fb9-aa82-29d5edf093da · outbound

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

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 4

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source=pdf_text observed=2026-08-04T19:37:26.629639Z digest=sha256:21abcaebdd6bddc97a4299531dcf25b7f3f64bbc0a7ce09311eae9b969fafc6f

Observation 6b5d2fbe-6db3-41f8-a01b-8151965077e2 · outbound

This paper cites Hubert: Self-supervised speech representation learning by masked prediction of hidden units,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 5

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source=pdf_text observed=2026-08-04T19:37:26.689621Z digest=sha256:5c06a19ce0118cb657beafc27fd1da1b4b9275b6f3bc907b5fca1afd1f34fe9d

Observation 42a860d6-b608-42f0-b262-19c3d866853f · outbound

This paper cites Wavlm: Large-scale self-supervised pre- training for full stack speech processing,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Wavlm: Large-scale self-supervised pre- training for full stack speech processing,

Reference 6

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source=pdf_text observed=2026-08-04T19:37:26.752799Z digest=sha256:9091c6dfe398508b060d131ca1cae6c05859ec27a269efe1627e621bf7cb0690

Observation 498a1191-8534-48ee-bb4a-d989f45d3531 · outbound

This paper cites Learn from real: reality defender’s submission to asvspoof5 challenge,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Learn from real: reality defender’s submission to asvspoof5 challenge,

Reference 7

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source=pdf_text observed=2026-08-04T19:37:26.811824Z digest=sha256:47eebdec2ce1caeb0a36a500290ebb1171448f8b2646b53a45df2b3e970c83e9

Observation 16a2d937-2780-4802-a986-d9b1409744b1 · outbound

This paper cites Peft-ser: On the use of parameter efficient transfer learning approaches for speech emotion recognition using pre- trained speech models,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Peft-ser: On the use of parameter efficient transfer learning approaches for speech emotion recognition using pre- trained speech models,

Reference 8

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source=pdf_text observed=2026-08-04T19:37:26.851820Z digest=sha256:aea2e91fa4982d22d05bfb36c8f7b5e8b9b0e19e1ed8cfb13857754603068873

Observation 442220de-eaa2-4d6b-8fdd-ea0834ad28fa · outbound

This paper cites PEFT for Speech: Unveiling Optimal Placement, Merging Strategies, and Ensemble Techniques.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection PEFT for Speech: Unveiling Optimal Placement, Merging Strategies, and Ensemble Techniques

Reference 9

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source=pdf_text observed=2026-08-04T19:37:26.915596Z digest=sha256:29551bed38756eeb0a099baef2a17cbecdf827c36db86cfbe694facb27e1ee2b

Observation f5af7429-8913-4402-a9ae-f1ebad3f3921 · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 10

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source=pdf_text observed=2026-08-04T19:37:26.986670Z digest=sha256:6056e10f73e97d91a8079866d6f05eb6bce7ab7e85bd0159806314f1e9f107dc

Observation ecfff722-331f-4df5-ae13-4058782cb55b · outbound

This paper cites X-lora: Mixture of low-rank adapter experts, a flexible framework for large language models with appli- cations in protein mechanics and molecular design,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection X-lora: Mixture of low-rank adapter experts, a flexible framework for large language models with appli- cations in protein mechanics and molecular design,

Reference 11

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source=pdf_text observed=2026-08-04T19:37:27.049152Z digest=sha256:fecb6392b58d1ffb6123b759fcb4ab189ae3149875a6b020de2ba2f2eb86e2b9

Observation bcd6788c-2d94-4fce-9215-357c3e2411bb · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection LoRA: Low-Rank Adaptation of Large Language Models

Reference 12

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source=pdf_text observed=2026-08-04T19:37:27.112089Z digest=sha256:d0ad61d4085dfec392f4983db0f4c0f3f7d1213a77d98ddc72961d909fc2ae8b

Observation d1c2eb36-9da2-4eb5-b15a-26c536277600 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 13

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source=pdf_text observed=2026-08-04T19:37:27.164902Z digest=sha256:7a8ad0c033e4847c56a16034c6de98a899dd83528292712c6f40a5a707bdd1cf

Observation b4016bff-8614-4827-8e25-b67cda9bb738 · outbound

This paper cites Mixture of A Million Experts.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Mixture of A Million Experts

Reference 14

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source=pdf_text observed=2026-08-04T19:37:27.224525Z digest=sha256:96ccf24421ae753841bf933df19fa9277aeb39dc89bd95b09c0b4be83ee9ad3e

Observation 6e1e16d4-1592-44df-822a-1ad66aaaef8e · outbound

This paper cites Improving speech emotion recognition by fusing self-supervised learning and spectral features via mixture of experts,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Improving speech emotion recognition by fusing self-supervised learning and spectral features via mixture of experts,

Reference 15

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source=pdf_text observed=2026-08-04T19:37:27.286758Z digest=sha256:d95eb238aaa13752f213b38d595adac7a0a930d661b8a2c3df96aaad88a9956b

Observation 0645af8c-2bc8-4eb0-981d-ed3fef437a2e · outbound

This paper cites AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning

Reference 16

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Observation c98fe56a-7c31-48d7-942c-1bb2771b9382 · outbound

This paper cites Adaptermix: Exploring the efficacy of mixture of adapters for low-resource tts adaptation,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Adaptermix: Exploring the efficacy of mixture of adapters for low-resource tts adaptation,

Reference 17

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source=pdf_text observed=2026-08-04T19:37:27.373238Z digest=sha256:e1ffefcf20d7f15b13f45c4083ff8991c68d7e087bca339621343ce17095af62

Observation a80f0cdd-6755-46e7-945e-cc720d132eb2 · outbound

This paper cites Moe-ffd: Mixture of experts for generalized and parameter-efficient face forgery detection,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Moe-ffd: Mixture of experts for generalized and parameter-efficient face forgery detection,

Reference 18

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Observation 3387b20a-329e-46bd-94c8-e744a022718d · outbound

This paper cites Mixture of lora experts,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Mixture of lora experts,

Reference 19

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source=pdf_text observed=2026-08-04T19:37:27.462244Z digest=sha256:6a0028e0c94b3d7dba29aff3763b2e2f01266d3912d0b295d33b74d2bb43782d

Observation e71a7a06-99c8-47c6-bc1e-ab5032375729 · outbound

This paper cites Attention is all you need,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Attention is all you need,

Reference 20

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source=pdf_text observed=2026-08-04T19:37:27.521356Z digest=sha256:17c947dc562e1f3a18976827a18bd56a70300981af224a2084fad261eeb56423

Observation dccbc5ce-3281-4247-a735-0a3280c2ef20 · outbound

This paper cites Attentive merging of hidden embeddings from pre-trained speech model for anti-spoofing detection,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Attentive merging of hidden embeddings from pre-trained speech model for anti-spoofing detection,

Reference 21

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source=pdf_text observed=2026-08-04T19:37:27.554581Z digest=sha256:a7f8cc0dd6f71720975e33060408e6a4657ac9b5eb5202684a53da8de2b8a119

Observation ffcc0233-1023-46f1-ab9f-0171f3987d29 · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 22

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source=pdf_text observed=2026-08-04T19:37:27.614417Z digest=sha256:3bb56a92ca6dbfb6059916dde3cbe504528b636c854528f001524c97628590b7

Observation 358c3471-c0d9-40c8-85b2-ec2687cc0572 · outbound

This paper cites A survey on lora networking: Research problems, current solutions, and open issues,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection A survey on lora networking: Research problems, current solutions, and open issues,

Reference 23

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source=pdf_text observed=2026-08-04T19:37:27.668639Z digest=sha256:5a35aeddbf1615e02ae6aafce3b9ee9610eb993c9cb66181158ecdca0bef1698

Observation aa3d488f-19f2-42d3-8d71-84593692de37 · outbound

This paper cites Mixture-of-experts with expert choice routing,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Mixture-of-experts with expert choice routing,

Reference 24

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Observation e52f48aa-afc8-4fba-8f60-a8e6c41a453f · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

Reference 25

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Observation eaad7d50-c8c8-423c-a681-d2f274001293 · outbound

This paper cites Speech foundation model ensembles for the controlled singing voice deepfake detection (ctrsvdd) challenge 2024,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Speech foundation model ensembles for the controlled singing voice deepfake detection (ctrsvdd) challenge 2024,

Reference 26

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Observation a719c4e9-1ca6-4f82-b0f5-674aa98375f6 · outbound

This paper cites The Expressive Power of Low-Rank Adaptation.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection The Expressive Power of Low-Rank Adaptation

Reference 27

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Observation 35f7b1bd-e857-4848-b271-a4503828b550 · outbound

This paper cites ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale,

Reference 28

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Observation 848c1aaf-d54a-4383-9768-2fc677161c19 · outbound

This paper cites The Singular Value Decomposition (SVD) and Low-Rank Matrix Approximations,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection The Singular Value Decomposition (SVD) and Low-Rank Matrix Approximations,

Reference 29

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Observation cb014dbe-4d5c-4238-9b0c-a9593d95dfef · outbound

This paper cites A single end-to-end voice anti-spoofing model with graph attention and feature aggregation for asvspoof 5 challenge,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection A single end-to-end voice anti-spoofing model with graph attention and feature aggregation for asvspoof 5 challenge,

Reference 30

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source=pdf_text observed=2026-08-04T19:37:28.049871Z digest=sha256:73f8eb6c3e0796a898e53daee088ec7cde2ce839048e13770c9e68078fde466b

Observation a56a2e1e-edf2-4d8f-9681-6552597b9b28 · outbound

This paper cites A study of guided masking data augmentation for deepfake speech detection,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection A study of guided masking data augmentation for deepfake speech detection,

Reference 31

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source=pdf_text observed=2026-08-04T19:37:28.081373Z digest=sha256:6ecb8517f91be635eec329793c1006cfdce313d9eeb797297d3b71af1a61c85c

Observation 8d5f0672-958c-4602-a79d-41cfef8d30d7 · outbound

This paper cites Enhancing spoofing detection in asvspoof 5 workshop 2024: fusion of wavlm-resnet18-sa for optimal performance against speech deepfakes,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Enhancing spoofing detection in asvspoof 5 workshop 2024: fusion of wavlm-resnet18-sa for optimal performance against speech deepfakes,

Reference 32

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source=pdf_text observed=2026-08-04T19:37:28.134227Z digest=sha256:1220b52736ae16e96843add53a7829673029d93f8c119c177059a0f463cb5a64

Observation 76fc21ef-2d16-4cdf-9d43-a95ebe74b6d3 · outbound

This paper cites Exploring wavlm back- ends for speech spoofing and deepfake detection,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Exploring wavlm back- ends for speech spoofing and deepfake detection,

Reference 33

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source=pdf_text observed=2026-08-04T19:37:28.163760Z digest=sha256:dd42383ea4441306d4e9198c85b2823199eca96f7632afd9521d20cc840e2259

Observation b536bf72-91c5-4ba2-b61c-f95340407f66 · outbound

This paper cites Wavlm model ensemble for audio deepfake detection,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Wavlm model ensemble for audio deepfake detection,

Reference 34

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source=pdf_text observed=2026-08-04T19:37:28.217084Z digest=sha256:a4aedbcc09425988e55a3202b54fefa45c795247110461a958c43752489234be

Observation b3f4e066-afc5-47d7-809d-5dd91d53825f · outbound

This paper cites Asvspoof 2019: A large-scale public database of synthesized, converted and replayed speech,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Asvspoof 2019: A large-scale public database of synthesized, converted and replayed speech,

Reference 35

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source=pdf_text observed=2026-08-04T19:37:28.246187Z digest=sha256:c89d0bd636c83b0b11d99b870bdfc434e6bb035f7879937a3dd2915eed535a4a

Observation a3d99d15-ceae-4833-894c-0d751bda2fc7 · outbound

This paper cites Asvspoof 2021: Towards spoofed and deepfake speech detection in the wild,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Asvspoof 2021: Towards spoofed and deepfake speech detection in the wild,

Reference 36

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source=pdf_text observed=2026-08-04T19:37:28.307795Z digest=sha256:6db799fe7fbaf5334a4ff43c517fdf68b7ce540055c17ebc2c40d34370e04ea7

Observation 888ed3db-8aef-4776-8ec4-eb1ce59ed668 · outbound

This paper cites Does audio deepfake detection generalize?.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Does audio deepfake detection generalize?

Reference 37

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source=pdf_text observed=2026-08-04T19:37:28.390868Z digest=sha256:f131e0e2c3c12c686e4068c891d2aa6bd5763a03cc4272f949144b485ac6cf3e

Observation 595c4713-c689-4669-bad1-cf3adb20ce88 · outbound

This paper cites Robust audio deepfake detection: Exploring front-/back-end combinations and data augmentation strate- gies for the asvspoof5 challenge,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Robust audio deepfake detection: Exploring front-/back-end combinations and data augmentation strate- gies for the asvspoof5 challenge,

Reference 38

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source=pdf_text observed=2026-08-04T19:37:28.417083Z digest=sha256:ad27eabbed8f0f7b870bfc006bf75cbd1ddff0aed55d6039ff49d45e993351cb

Observation b7cc17db-b246-40e7-aa47-7b2ee83bb467 · outbound

This paper cites Ai-synthesized voice detection using neural vocoder artifacts,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Ai-synthesized voice detection using neural vocoder artifacts,

Reference 39

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source=pdf_text observed=2026-08-04T19:37:28.472799Z digest=sha256:3233bacced43ff9023fdf8dce67fb429632642b0999d044bdc36b77aa17c28b1

Observation 93e0feb2-0bf0-4d88-8399-c66f5bad3fab · outbound

This paper cites Dfadd: The diffusion and flow-matching based audio deepfake dataset,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Dfadd: The diffusion and flow-matching based audio deepfake dataset,

Reference 40

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source=pdf_text observed=2026-08-04T19:37:28.528723Z digest=sha256:7031939aab837fc7d98efcad66de465ef26711559fb66ddcb3452c52e47152df

Observation eb95a7c6-7a37-416a-b0bf-887b682defa2 · outbound

This paper cites The Fake-or-Real Dataset,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection The Fake-or-Real Dataset,

Reference 41

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source=pdf_text observed=2026-08-04T19:37:28.588288Z digest=sha256:08e7242e41ebcbdb4245a0f7f970eb6b669f52f9659c6562c5e21a8cf8b3146c

Observation 7bcb1ea6-5443-4c86-89e1-a2595681ac02 · outbound

This paper cites Speech arena: Speech deepfake leaderboard,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Speech arena: Speech deepfake leaderboard,

Reference 42

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source=pdf_text observed=2026-08-04T19:37:28.648220Z digest=sha256:e0747b697d7968eaee4ab177b5b9ea233d3889d48ba835d763b0b78c3b8cac6f

Observation 39bad17e-1cd5-435f-a93e-ee7a54f76ed9 · outbound

This paper cites Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit,

Reference 43

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source=pdf_text observed=2026-08-04T19:37:28.704232Z digest=sha256:33f87814790357d71b5b958c8c2414d980fdd8f99e61c970a366cf6041f37109

Observation 8b22a565-f130-470e-98f4-93fce908a1f5 · outbound

This paper cites WaveNet: A Generative Model for Raw Audio.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection WaveNet: A Generative Model for Raw Audio

Reference 44

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source=pdf_text observed=2026-08-04T19:37:28.759964Z digest=sha256:cdd990ddd305e2e294d56119fef0109b1ba737b00c019facda21858275cf0fa2

Observation 8d589217-0c50-48e4-8824-724d316dc43f · outbound

This paper cites Natural tts synthesis by conditioning wavenet on mel spectrogram predictions,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Natural tts synthesis by conditioning wavenet on mel spectrogram predictions,

Reference 45

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source=pdf_text observed=2026-08-04T19:37:28.819383Z digest=sha256:9b4a150162e88b780560ebc2f6fabd57224b62aea1805f5bb3118283342b9a8a

Observation 6403b49e-59dd-4c25-aae1-ec90309f2b20 · outbound

This paper cites Mls: A large-scale multilingual dataset for speech research,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Mls: A large-scale multilingual dataset for speech research,

Reference 46

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source=pdf_text observed=2026-08-04T19:37:28.906835Z digest=sha256:5e5768a6a8529f8d8216b975630585d3424771684e09a7b2e42b0bf62a02cfe9

Observation 53fff485-e278-4622-b773-7695c7021ff4 · outbound

This paper cites Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme

Reference 47

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source=pdf_text observed=2026-08-04T19:37:28.960970Z digest=sha256:4134e8ae06f206a68bf75ce8ac81e5b5b0938b4f55e5f2882bb72a4477e8cdc7

Observation 8bec96b2-18d6-4151-86bd-7ba647480784 · outbound

This paper cites Low-Resource Multilingual and Zero-Shot Multispeaker TTS.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Low-Resource Multilingual and Zero-Shot Multispeaker TTS

Reference 48

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source=pdf_text observed=2026-08-04T19:37:29.050838Z digest=sha256:8f47f785d9485b4bedaf231efcc4030fc7ca92799f49a9766f93281160c7227a

Observation a3d4efd4-e109-4887-a478-5a4012b86cd4 · outbound

This paper cites Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech,

Reference 49

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source=pdf_text observed=2026-08-04T19:37:29.132724Z digest=sha256:8da53e2303a139f35851922ba56a5e81dd63c2c4398e4914a60a14a8a2354b29

Observation 340fe693-35d8-4fd5-95d7-040645ff8ec4 · outbound

This paper cites Glow-tts: A generative flow for text-to-speech via monotonic alignment search,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Glow-tts: A generative flow for text-to-speech via monotonic alignment search,

Reference 50

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source=pdf_text observed=2026-08-04T19:37:29.217370Z digest=sha256:d9d4481cf9d306ac4c636bb5da745df6fcf11e9872267bb70c81d899d10ada25

Observation 2cbd3c2b-93a2-4968-ac0c-9ce15b9976f0 · outbound

This paper cites Creating New Language and Voice Components for the Updated MaryTTS Text-to-Speech Synthesis Platform.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Creating New Language and Voice Components for the Updated MaryTTS Text-to-Speech Synthesis Platform

Reference 51

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source=pdf_text observed=2026-08-04T19:37:29.300199Z digest=sha256:c011cbdbdadf290c2056bf5804541720869ae23f9a4e71fee005c76bd240c88a

Observation 75a2e6e7-66ba-4d1c-8379-6f8fab5fca2e · outbound

This paper cites P-flow: A fast and data-efficient zero-shot tts through speech prompting,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection P-flow: A fast and data-efficient zero-shot tts through speech prompting,

Reference 52

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source=pdf_text observed=2026-08-04T19:37:29.382603Z digest=sha256:d551200650933781fa07d4f441ce727a8000e2b5b9812f2292c1d10c3297ac34

Observation 22f6a433-e921-48fa-aaf5-161bf922802c · outbound

This paper cites Matcha-tts: A fast tts architecture with conditional flow matching,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Matcha-tts: A fast tts architecture with conditional flow matching,

Reference 53

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source=pdf_text observed=2026-08-04T19:37:29.465327Z digest=sha256:dd8c09b5472651afc87f4d190dcf4193c4dde899855c51ef63d1ebebc3c681f6

Observation c99e8299-53ef-4080-a2c8-b90d6bc3b6e6 · outbound

This paper cites Styletts 2: Towards human-level text-to-speech through style diffusion and adversarial training with large speech language models,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Styletts 2: Towards human-level text-to-speech through style diffusion and adversarial training with large speech language models,

Reference 54

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source=pdf_text observed=2026-08-04T19:37:29.518622Z digest=sha256:3499197e64c7f64bfa5f8424701b979f88f79bbb43294e15ff7a181f976421b8

Observation 67759627-10f1-4b28-876c-4066934de0a3 · outbound

This paper cites Grad- tts: A diffusion probabilistic model for text-to-speech,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Grad- tts: A diffusion probabilistic model for text-to-speech,

Reference 55

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source=pdf_text observed=2026-08-04T19:37:29.576890Z digest=sha256:c912d38021f27ba5e04094fdee1829a51876802633a2af23955f43218e1e37bb

Observation 60d08358-92fd-4fcf-ae04-9d1b4c507705 · outbound

This paper cites LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech

Reference 56

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source=pdf_text observed=2026-08-04T19:37:29.663715Z digest=sha256:a8a19d26293ba8b03b7c0b20a8251503ea093145df06f9ca47efbc3519f564ab

Observation f9f1113f-9f64-49be-b291-99101b1afe32 · outbound

This paper cites Parallel wavegan: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Parallel wavegan: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram,

Reference 57

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source=pdf_text observed=2026-08-04T19:37:29.719531Z digest=sha256:e5792ee19a8613caf8049b3ddba9d21274d079d340a012cb64f275b8aa6e53a7

Observation 4416c69e-7cc9-4c9e-8ecd-6d28d99763cf · outbound

This paper cites DiffWave: A Versatile Diffusion Model for Audio Synthesis.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 58

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source=pdf_text observed=2026-08-04T19:37:29.774849Z digest=sha256:2c1421b090ccc7eed078334199750307e5d88f9407211a284a86f4bd5a1d7d94

Observation 7f2bda4b-27ae-465c-9966-e83eb48d9040 · outbound

This paper cites WaveGrad: Estimating Gradients for Waveform Generation.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection WaveGrad: Estimating Gradients for Waveform Generation

Reference 59

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source=pdf_text observed=2026-08-04T19:37:29.831388Z digest=sha256:baa57d87c45ca031d90c7d38839e5706a0df07f7610fc4bf25df945ea044c4cf

Observation ae9621c4-edce-4bfe-9f05-4fce2a993088 · outbound

This paper cites V oxForge speech dataset,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection V oxForge speech dataset,

Reference 60

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source=pdf_text observed=2026-08-04T19:37:29.889332Z digest=sha256:9c6487d6388ea9e54c1b92142d05bcd3fa572ebbc2064bcd42274ffe4515a27e

Observation e987ff1d-ba53-4efc-8452-832fe9358039 · outbound

This paper cites Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning

Reference 61

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source=pdf_text observed=2026-08-04T19:37:29.943528Z digest=sha256:f3a2ae89cd78cc8096b019fd8ae8f9b6f2f71b4c6a4b43780d1e0d0a903d927d

Observation 38e4db1f-b9d7-45db-8ca6-d5eb7f6e4e9f · outbound

This paper cites Catastrophic forgetting, rehearsal and pseudorehearsal,.

MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection Catastrophic forgetting, rehearsal and pseudorehearsal,

Reference 62

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source=pdf_text observed=2026-08-04T19:37:29.997581Z digest=sha256:16e5cc12052da632eefa11891ad151bb4b71e691f5d588a530ccda199db1fc9b

Pith citing papers

Observation 36d40298-5761-4e16-a2be-ed767dca83ea · inbound

Teffic-Audio: Tell Fact from Fiction cites this paper.

Teffic-Audio: Tell Fact from Fiction MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection

Reference 20

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source=pdf_text observed=2026-07-31T10:28:22.453820Z digest=sha256:6f00fdd36b6314613b02f04fc3238b2144c0ea4efe24ac14552b1626f0ee4c45