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Paper Citation Record · LEDGER

From Sharpness to Better Generalization for Speech Deepfake Detection

As of 9 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 3 inbound Pith citation observations for arXiv:2506.11532.

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

pith.paper-citation-record.v1
2506.11532 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:08:06.134207Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:08:06.023468Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy31
  • unresolved6
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  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e4ee6c69-9034-434b-b366-dfc6c28dd70b · outbound

This paper cites From Sharpness to Better Generalization for Speech Deepfake Detection.

From Sharpness to Better Generalization for Speech Deepfake Detection From Sharpness to Better Generalization for Speech Deepfake Detection

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b0f2cd90-0876-462a-87b1-12d71b9dc665 · outbound

This paper cites Given this characteristic, we aim to first explore whether sharpness can serve as a diagnos- tic tool to evaluate how domain mismatch impacts the model’s sensitivity and robustness.

From Sharpness to Better Generalization for Speech Deepfake Detection Given this characteristic, we aim to first explore whether sharpness can serve as a diagnos- tic tool to evaluate how domain mismatch impacts the model’s sensitivity and robustness

Reference 2

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 7dd83860-ba73-4abe-8f8f-9094b37529b1 · outbound

This paper cites Similar to Section 2, let S = (xi, yi)n i=1 be a set of la- beled data, and let ℓi(w) denote the loss evaluated at the point (xi, yi).

From Sharpness to Better Generalization for Speech Deepfake Detection Similar to Section 2, let S = (xi, yi)n i=1 be a set of la- beled data, and let ℓi(w) denote the loss evaluated at the point (xi, yi)

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6aba8530-40c5-4c91-8ce4-7061ab8ed59e · outbound

This paper cites Experimental Settings Datasets.

From Sharpness to Better Generalization for Speech Deepfake Detection Experimental Settings Datasets

Reference 4

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malformed identifier
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation aeb2675f-4165-4fa7-97d2-cec3c2151ed6 · outbound

This paper cites Our findings show that sharpness increases under domain shifts, indicating model sensitivity to unseen conditions.

From Sharpness to Better Generalization for Speech Deepfake Detection Our findings show that sharpness increases under domain shifts, indicating model sensitivity to unseen conditions

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2febeaa9-aaa5-4bac-b00d-1a705aee12f9 · outbound

This paper cites This study is partially supported by JST AIP Acceleration Research (JPMJCR24U3).

From Sharpness to Better Generalization for Speech Deepfake Detection This study is partially supported by JST AIP Acceleration Research (JPMJCR24U3)

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d463b649-e7d6-402b-8ca5-caa6db90ce20 · outbound

This paper cites ASVspoof 2021: Accelerating progress in spoofed and deep- fake speech detection,.

From Sharpness to Better Generalization for Speech Deepfake Detection ASVspoof 2021: Accelerating progress in spoofed and deep- fake speech detection,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 014fb6e4-e95b-4011-8bcd-309a297e8168 · outbound

This paper cites Does audio deepfake detection generalize?.

From Sharpness to Better Generalization for Speech Deepfake Detection Does audio deepfake detection generalize?

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 33e83e4a-72b3-4e5e-9d91-ceb8ea3eed93 · outbound

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

From Sharpness to Better Generalization for Speech Deepfake Detection Raw- Boost: A raw data boosting and augmentation method applied to automatic speaker verification anti-spoofing,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation c02b99e4-d8be-44d5-873e-b6db9d2f2670 · outbound

This paper cites SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition.

From Sharpness to Better Generalization for Speech Deepfake Detection SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ae359a24-39a8-4bc5-8e60-1f3d2aef1ad5 · outbound

This paper cites Spoofed training data for speech spoofing countermeasure can be efficiently created using neural vocoders,.

From Sharpness to Better Generalization for Speech Deepfake Detection Spoofed training data for speech spoofing countermeasure can be efficiently created using neural vocoders,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b0af6fed-7f59-4534-8a78-91335bce76f0 · outbound

This paper cites Can large-scale vocoded spoofed data improve speech spoofing countermeasure with a self-supervised front end?.

From Sharpness to Better Generalization for Speech Deepfake Detection Can large-scale vocoded spoofed data improve speech spoofing countermeasure with a self-supervised front end?

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 247c92a9-543a-4eb8-8c68-e5b8f7eb0c6f · outbound

This paper cites CPAUG: Refining copy-paste augmentation for speech anti-spoofing,.

From Sharpness to Better Generalization for Speech Deepfake Detection CPAUG: Refining copy-paste augmentation for speech anti-spoofing,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a62ff9c9-9c8f-4e2c-8d26-0b252f78576a · outbound

This paper cites AASIST: Audio anti-spoofing using integrated spectro-temporal graph attention networks,.

From Sharpness to Better Generalization for Speech Deepfake Detection AASIST: Audio anti-spoofing using integrated spectro-temporal graph attention networks,

Reference 14

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raw_fallback, observed 2026-08-07T04:08:06.395096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 7c735018-3ee9-4faf-a4f8-24ec1367abea · outbound

This paper cites Spoofing speech detection by modeling local spectro-temporal and long-term dependency,.

From Sharpness to Better Generalization for Speech Deepfake Detection Spoofing speech detection by modeling local spectro-temporal and long-term dependency,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 67a2c67e-3925-4a05-bda3-a334f3300a82 · outbound

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

From Sharpness to Better Generalization for Speech Deepfake Detection Temporal-channel modeling in multi-head self- attention for synthetic speech detection,

Reference 16

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9e8f77d0-30b0-440d-91f3-1f44ca53a87b · outbound

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

From Sharpness to Better Generalization for Speech Deepfake Detection wav2vec 2.0: A framework for self-supervised learning of speech repre- sentations,

Reference 17

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Source-reported events for the cited work

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Observation e892ec6f-7acc-49c8-a6fa-fde74123eb15 · outbound

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

From Sharpness to Better Generalization for Speech Deepfake Detection XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

Reference 18

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Unavailable: canonical work link unavailable.

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Observation f2058afe-0d13-4553-a960-5f5af0492c51 · outbound

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

From Sharpness to Better Generalization for Speech Deepfake Detection WavLM: Large-scale self- supervised pre-training for full stack speech processing,

Reference 19

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Source-reported events for the cited work

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Observation 18e799f9-d68e-4df4-b396-2d86c841808d · outbound

This paper cites One-class learning towards syn- thetic voice spoofing detection,.

From Sharpness to Better Generalization for Speech Deepfake Detection One-class learning towards syn- thetic voice spoofing detection,

Reference 20

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 4f60f475-7973-4869-bb53-83931b0bcf04 · outbound

This paper cites One-class learning with adap- tive centroid shift for audio deepfake detection,.

From Sharpness to Better Generalization for Speech Deepfake Detection One-class learning with adap- tive centroid shift for audio deepfake detection,

Reference 21

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0dd29b08-6536-4651-9df7-bdbaa24afc79 · outbound

This paper cites Generalizable audio deepfake detection via latent space refinement and augmen- tation,.

From Sharpness to Better Generalization for Speech Deepfake Detection Generalizable audio deepfake detection via latent space refinement and augmen- tation,

Reference 22

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e2a5b489-e3a3-4c41-abe5-653425d8c1d0 · outbound

This paper cites Tandem assessment of spoofing countermeasures and au- tomatic speaker verification: Fundamentals,.

From Sharpness to Better Generalization for Speech Deepfake Detection Tandem assessment of spoofing countermeasures and au- tomatic speaker verification: Fundamentals,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation c3280b87-e298-4c48-918f-3ed4faa65820 · outbound

This paper cites t- EER: Parameter-free tandem evaluation of countermeasures and biometric comparators,.

From Sharpness to Better Generalization for Speech Deepfake Detection t- EER: Parameter-free tandem evaluation of countermeasures and biometric comparators,

Reference 24

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d62f2262-7b7c-4c51-95da-dfcfa3bcade1 · outbound

This paper cites On large-batch training for deep learning: Gen- eralization gap and sharp minima,.

From Sharpness to Better Generalization for Speech Deepfake Detection On large-batch training for deep learning: Gen- eralization gap and sharp minima,

Reference 25

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 761f59f8-b724-471e-9f93-72e4e2f4327f · outbound

This paper cites Fantastic generalization measures and where to find them,.

From Sharpness to Better Generalization for Speech Deepfake Detection Fantastic generalization measures and where to find them,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 194deb78-a70b-4814-9870-1110906c934a · outbound

This paper cites Sharpness- aware minimization for efficiently improving generalization,.

From Sharpness to Better Generalization for Speech Deepfake Detection Sharpness- aware minimization for efficiently improving generalization,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a3384db4-fa1e-43cc-8d2f-ca0dd0fb1820 · outbound

This paper cites Multi-dataset co- training with sharpness-aware optimization for audio anti- spoofing,.

From Sharpness to Better Generalization for Speech Deepfake Detection Multi-dataset co- training with sharpness-aware optimization for audio anti- spoofing,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 408f35d8-df21-4526-9560-d91bfe0f3a59 · outbound

This paper cites Towards understanding sharpness-aware minimization,.

From Sharpness to Better Generalization for Speech Deepfake Detection Towards understanding sharpness-aware minimization,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:08:06.108042Z digest=sha256:4a510510439b72dc2a080ac91b28c2bc6880032454912c5f9cea60e9ded0975d

Observation 530be821-8d0f-4577-9f6e-20edc82a05d2 · outbound

This paper cites ASVspoof 2019: A large-scale public database of synthe- sized, converted and replayed speech,.

From Sharpness to Better Generalization for Speech Deepfake Detection ASVspoof 2019: A large-scale public database of synthe- sized, converted and replayed speech,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:08:06.110853Z digest=sha256:063f24b5080dc900d4815892a32cc5dde970eccd775b593209b3517e85790132

Observation 7e42f1f5-b2bc-4afe-b002-26a6bbcc47ca · outbound

This paper cites FoR: A dataset for synthetic speech detection,.

From Sharpness to Better Generalization for Speech Deepfake Detection FoR: A dataset for synthetic speech detection,

Reference 31

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raw_fallback, observed 2026-08-07T04:08:06.253827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8ddca4dd-dd32-41f7-993b-1fc3bb12e62d · outbound

This paper cites WaveFake: A data set to facilitate audio deepfake detection,.

From Sharpness to Better Generalization for Speech Deepfake Detection WaveFake: A data set to facilitate audio deepfake detection,

Reference 32

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2c8b38a1-2083-4f0b-8f88-4a61eae2cd31 · outbound

This paper cites The LJ Speech dataset,.

From Sharpness to Better Generalization for Speech Deepfake Detection The LJ Speech dataset,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:08:06.119259Z digest=sha256:a079e453ec46b737ed8bc261a2b4d552bffc37e89338a1c8121408e7206db764

Observation 9d15f53f-2a35-4420-9f92-e11f896afc4f · outbound

This paper cites JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis.

From Sharpness to Better Generalization for Speech Deepfake Detection JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:06.121956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:06.121956Z digest=sha256:5618cd4a1a47836a386f882c152a85c3dd2c5f84f43afcd9f16749b8ab33d547

Observation c79aa350-f315-4a0a-a25c-7e1bc0e50973 · outbound

This paper cites ADD 2022: the first audio deep synthesis detection challenge,.

From Sharpness to Better Generalization for Speech Deepfake Detection ADD 2022: the first audio deep synthesis detection challenge,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:06.226208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:08:06.125382Z digest=sha256:ae416fa5a5358ae1d6b7c24b3c085f02960460e933fb3eebed1f8c818e80a558

Observation 5227d705-a7cd-4d09-a7bd-ba480342f0a1 · outbound

This paper cites SpoofCeleb: Speech deepfake detection and SASV in the wild,.

From Sharpness to Better Generalization for Speech Deepfake Detection SpoofCeleb: Speech deepfake detection and SASV in the wild,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:06.216868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:08:06.128486Z digest=sha256:12ecaf5bb7029b6540ec81e05e178eb4e814bbcc2e72fec266c9cf18509abee3

Observation 8f747ba8-98df-4bee-9e13-cc09789a5f60 · outbound

This paper cites Automatic speaker verification spoofing and deep- fake detection using wav2vec 2.0 and data augmentation,.

From Sharpness to Better Generalization for Speech Deepfake Detection Automatic speaker verification spoofing and deep- fake detection using wav2vec 2.0 and data augmentation,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:06.207161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:08:06.131506Z digest=sha256:6fad5dbdaed16f939a5c8f14104b3eb62c075e81636fd78ae73adcbc5235be21

Observation b0b2a565-d15c-4378-8e6d-e42fb909f865 · outbound

This paper cites Visualizing the loss landscape of neural nets,.

From Sharpness to Better Generalization for Speech Deepfake Detection Visualizing the loss landscape of neural nets,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:06.134207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:06.134207Z digest=sha256:95e5878be293241e4647087f48fe1b2671fd3be4cae7fb75f41a9de7ec68d1af

Pith citing papers

Observation e4ee6c69-9034-434b-b366-dfc6c28dd70b · inbound

From Sharpness to Better Generalization for Speech Deepfake Detection cites this paper.

From Sharpness to Better Generalization for Speech Deepfake Detection From Sharpness to Better Generalization for Speech Deepfake Detection

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:06.023468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:06.023468Z digest=sha256:a961e9426d127c0ea738e3f7cd5cccd9c60c34f2050476bc2c3a47c0b543e301

Observation 1eb4e7a4-84f1-4094-b8ec-ea7fa693fe63 · inbound

Wolkowicz-Styan Upper Bound on the Hessian Eigenspectrum for Cross-Entropy Loss in Nonlinear Smooth Neural Networks cites this paper.

Wolkowicz-Styan Upper Bound on the Hessian Eigenspectrum for Cross-Entropy Loss in Nonlinear Smooth Neural Networks From Sharpness to Better Generalization for Speech Deepfake Detection

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-10T16:15:34.088794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:13:31.927099Z digest=sha256:56b70664c8c847afda9d7543eed6eb9c8b4b0bbbef86c518d97c10391205cab6

Observation d79952bd-d629-45bc-a079-224e64812c3f · inbound

Closed-Form Steepest Descent Direction toward Flat Minima: Reducing Upper Bounds on the Loss Hessian Eigenspectrum in Neural Networks cites this paper.

Closed-Form Steepest Descent Direction toward Flat Minima: Reducing Upper Bounds on the Loss Hessian Eigenspectrum in Neural Networks From Sharpness to Better Generalization for Speech Deepfake Detection

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-06-30T09:44:36.936858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T09:40:55.428448Z digest=sha256:4411af88ee2d904c0b20eb19346c711337edd3461c113ea3f2fb90703cbdae1c