Paper Citation Record · LEDGER

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models

As of 19 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2506.14153.

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

pith.paper-citation-record.v1
2506.14153 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:22:27.487255Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:22:22.154746Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:22:28.684424Z

Reference resolution

37 of 37 outbound references displayed

verified exact2
verified fuzzy14
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e82d7be-0693-468d-8763-111cf02d8ecb · outbound

This paper cites an unresolved cited work.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:22:33.146718Z

Source-reported events for the cited work

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Observation 24d7d5b6-d9a6-440e-addf-d2346afdf17a · outbound

This paper cites Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:22:28.864756Z

Source-reported events for the cited work

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Observation 7ffd35bf-b163-49ca-89bf-d7ad2d4214db · outbound

This paper cites an unresolved cited work.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Unresolved cited work

Reference 3

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Source-reported events for the cited work

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Observation 6f98283c-3ea8-49d2-985c-e4e23afb1127 · outbound

This paper cites an unresolved cited work.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:22:32.476791Z

Source-reported events for the cited work

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Observation c0af91c7-86f3-48dc-86fc-1b61f97e754b · outbound

This paper cites Our model replaces fully-connected layer by GR-KAN, which is powerful in func- tion approximation and dimensionality reduction.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Our model replaces fully-connected layer by GR-KAN, which is powerful in func- tion approximation and dimensionality reduction

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:32.224479Z

Source-reported events for the cited work

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Observation fd50d60d-0415-4af4-94fa-3c87e6ce77c0 · outbound

This paper cites Temporal-channel modeling in multi-head self- attention for synthetic speech detection,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Temporal-channel modeling in multi-head self- attention for synthetic speech detection,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:31.739064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fb8008a6-b391-4d12-94c3-de2eaaa8441c · outbound

This paper cites An overview of voice conversion and its challenges: From statistical modeling to deep learning,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models An overview of voice conversion and its challenges: From statistical modeling to deep learning,

Reference 7

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T00:22:28.574404Z

Source-reported events for the cited work

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Observation a66ec33e-8da7-4b1f-97b2-2f194ad86cac · outbound

This paper cites Human perception of audio deepfakes,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Human perception of audio deepfakes,

Reference 8

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T00:22:28.201085Z

Source-reported events for the cited work

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Observation c435dc4a-cda6-4d61-9b19-8717ebbdb45f · outbound

This paper cites Vsasv: a vietnamese dataset for spoofing-aware speaker verification,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Vsasv: a vietnamese dataset for spoofing-aware speaker verification,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:32.064747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 06d63d74-52f3-4262-b1e1-6d20e8a47b05 · outbound

This paper cites Voice Spoofing Countermeasures: Taxonomy, State-of-the-art, experimental analysis of generalizability, open challenges, and the way forward.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Voice Spoofing Countermeasures: Taxonomy, State-of-the-art, experimental analysis of generalizability, open challenges, and the way forward

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:22:27.925357Z

Source-reported events for the cited work

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Observation 873bb6f6-0357-45e7-b386-4c8d92744db7 · outbound

This paper cites A conformer-based classifier for variable-length utterance process- ing in anti-spoofing,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models A conformer-based classifier for variable-length utterance process- ing in anti-spoofing,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:31.884788Z

Source-reported events for the cited work

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Observation 9eb81d16-a75f-4fa4-9f06-e9fe42610936 · outbound

This paper cites Robust audio deep- fake detection using ensemble confidence calibration,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Robust audio deep- fake detection using ensemble confidence calibration,

Reference 12

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Observation 12526466-dd26-473f-8f19-33f05db62938 · outbound

This paper cites Fine-tuning wav2vec2 for speaker recognition,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Fine-tuning wav2vec2 for speaker recognition,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:31.608287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 18e4f72e-a1bb-4c3b-9640-c8ee63a8a452 · outbound

This paper cites Exploring wav2vec 2.0 fine tuning for improved speech emotion recognition,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Exploring wav2vec 2.0 fine tuning for improved speech emotion recognition,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:24.045258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fc03c4d-28b1-4c44-860d-276687bfba28 · outbound

This paper cites Exploring speaker age estimation on different self-supervised learning models,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Exploring speaker age estimation on different self-supervised learning models,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:24.114754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 808f34b7-5ed7-4ee5-a026-085eb4eeb549 · outbound

This paper cites Estimation of speaker age and height from speech signal using bi-encoder transformer mixture model,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Estimation of speaker age and height from speech signal using bi-encoder transformer mixture model,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:24.214744Z

Source-reported events for the cited work

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Observation 5f5fa4c0-a08f-4360-bf63-3af4811c17e4 · outbound

This paper cites Nes2net: A lightweight nested architecture for foundation model driven speech anti-spoofing,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Nes2net: A lightweight nested architecture for foundation model driven speech anti-spoofing,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:24.364748Z

Source-reported events for the cited work

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Observation c58d305d-c85c-4ee2-a813-3368951b27b1 · outbound

This paper cites Gradient-based learning applied to document recognition,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Gradient-based learning applied to document recognition,

Reference 18

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Source-reported events for the cited work

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Observation e476e6ee-e1b4-4d25-bbd3-ce95e3e7e672 · outbound

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

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Conformer: Convolution-augmented transformer for speech recognition,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:31.376425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fa195325-19b9-4f33-8fb3-a89dfb17a6f7 · outbound

This paper cites The kolmogorov–arnold representation theorem revisited,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models The kolmogorov–arnold representation theorem revisited,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:30.214749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ebd72612-1bc8-4a31-9734-6d245ea9b544 · outbound

This paper cites AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks

Reference 21

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Source-reported events for the cited work

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Observation 366b73dc-f695-4e15-b22d-bc249db360bc · outbound

This paper cites Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentation.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:25.326738Z

Source-reported events for the cited work

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Observation 96618241-970b-4c93-b949-3cc8b699ce09 · outbound

This paper cites Leveraging positional-related local-global dependency for syn- thetic speech detection,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Leveraging positional-related local-global dependency for syn- thetic speech detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:31.182010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2220e252-cf3f-4cc4-a02b-530ae1ac87db · outbound

This paper cites Light convolutional neu- ral network with feature genuinization for detection of synthetic speech attacks,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Light convolutional neu- ral network with feature genuinization for detection of synthetic speech attacks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:30.833276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ff93de16-16f8-419b-9e1a-54ae05522f3d · outbound

This paper cites XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

Reference 25

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Source-reported events for the cited work

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Observation 04460e29-2d53-4ff7-bf07-341b13031c9c · outbound

This paper cites Given an input speech signalO, theT-length output SSL features are denoted as X=SSL(O) = (x t ∈R D|t= 1, ..., T), withDbeing the output dimension of the SSL model.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Given an input speech signalO, theT-length output SSL features are denoted as X=SSL(O) = (x t ∈R D|t= 1, ..., T), withDbeing the output dimension of the SSL model

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:32.634747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4cc24ee6-d85c-4f59-8129-14fadfd8f5b5 · outbound

This paper cites Kan: Kolmogorov-arnold networks,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Kan: Kolmogorov-arnold networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:30.518804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 024dd031-622c-4aff-a670-66366afca3d9 · outbound

This paper cites Suitability of KANs for Computer Vision: A preliminary investigation.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Suitability of KANs for Computer Vision: A preliminary investigation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:26.234753Z

Source-reported events for the cited work

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Observation eb1bc016-c163-48bb-a042-02a4901497bf · outbound

This paper cites From KAN to GR-KAN: Advancing Speech Enhancement with KAN-Based Methodology.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models From KAN to GR-KAN: Advancing Speech Enhancement with KAN-Based Methodology

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:26.324754Z

Source-reported events for the cited work

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Observation 91507676-6af2-4696-98a5-24392bf54569 · outbound

This paper cites Multilayer feedfor- ward networks are universal approximators,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Multilayer feedfor- ward networks are universal approximators,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:29.913773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 611f1f06-d719-412f-bd51-18cec8ea70ee · outbound

This paper cites Kolmogorov-Arnold Transformer.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Kolmogorov-Arnold Transformer

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:26.574752Z

Source-reported events for the cited work

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Observation e357c04d-e495-4f31-a324-e8262da27bbd · outbound

This paper cites wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:26.904747Z

Source-reported events for the cited work

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Observation a8970429-05a1-4116-944c-6e254bae2879 · outbound

This paper cites End-to-end anti-spoofing with rawnet2,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models End-to-end anti-spoofing with rawnet2,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:26.993331Z

Source-reported events for the cited work

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Observation 3cb245fd-9f0f-4845-8166-dc90d2e09e30 · outbound

This paper cites Asvspoof 2019: Future horizons in spoofed and fake audio detection,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Asvspoof 2019: Future horizons in spoofed and fake audio detection,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:29.443119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c90100fe-c18f-44ed-8aab-7ed609776f88 · outbound

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

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Asvspoof 2021: Towards spoofed and deepfake speech de- tection in the wild,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:27.354775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8e3cba0-2dbf-46e0-978e-ae0aa1cbba00 · outbound

This paper cites Raw- boost: A raw data boosting and augmentation method applied to automatic speaker verification anti-spoofing,.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Raw- boost: A raw data boosting and augmentation method applied to automatic speaker verification anti-spoofing,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:29.184754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bd5a5ea5-4b6a-49a9-85d0-37d29fff8901 · outbound

This paper cites Conformer: Convolution-augmented Transformer for Speech Recognition.

Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models Conformer: Convolution-augmented Transformer for Speech Recognition

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:24.974764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 24d7d5b6-d9a6-440e-addf-d2346afdf17a · inbound