Paper Citation Record · LEDGER

Audio Deepfake Detection at the First Greeting: "Hi!"

As of 6 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2601.19573.

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

pith.paper-citation-record.v1
2601.19573 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T11:05:33.744633Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-16T11:05:33.744633Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-16T11:07:48.301303Z

Reference resolution

30 of 30 outbound references displayed

verified exact4
verified fuzzy24
unresolved0
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40bb36b5-548b-4f0e-9067-a622009676f1 · outbound

This paper cites Audio Deepfake Detection at the First Greeting: "Hi!".

Audio Deepfake Detection at the First Greeting: "Hi!" Audio Deepfake Detection at the First Greeting: "Hi!"

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-16T11:07:48.302826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0272d145-5a0f-49c2-8be6-bd61a2f8fdd1 · outbound

This paper cites Framework Architecture Our work extends the Multi-Granularity Adaptive Time- Frequency Attention (MGAA) framework for ADD [7] to ultra-short utterances (0.5s–2s).

Audio Deepfake Detection at the First Greeting: "Hi!" Framework Architecture Our work extends the Multi-Granularity Adaptive Time- Frequency Attention (MGAA) framework for ADD [7] to ultra-short utterances (0.5s–2s)

Reference 2

Resolution: malformed identifier; raw_fallback, observed 2026-05-16T11:12:47.548000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 45005e85-cdf9-4559-93b7-67450980ad07 · outbound

This paper cites Deep” and “Shallow.

Audio Deepfake Detection at the First Greeting: "Hi!" Deep” and “Shallow

Reference 3

Resolution: malformed identifier; raw_fallback, observed 2026-05-16T11:12:47.534986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a161ed1d-3018-4725-9f8f-5c10303f52b8 · outbound

This paper cites The framework enhances discriminative repre- sentation learning from limited audio inputs, enabling reliable detection within durations as short as a greeting phrase.

Audio Deepfake Detection at the First Greeting: "Hi!" The framework enhances discriminative repre- sentation learning from limited audio inputs, enabling reliable detection within durations as short as a greeting phrase

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.552761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1fefbf82-8b2f-479e-b822-1b0b32706a6c · outbound

This paper cites A survey on speech deepfake detection.

Audio Deepfake Detection at the First Greeting: "Hi!" A survey on speech deepfake detection

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.554778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f680f200-6087-486d-95ef-47fdb0a18367 · outbound

This paper cites ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detection.

Audio Deepfake Detection at the First Greeting: "Hi!" ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detection

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-16T11:07:48.296408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ff05468d-5f95-4c31-ac72-3974f86ca448 · outbound

This paper cites Asvspoof 2021: Towards spoofed and deep- fake speech detection in the wild.

Audio Deepfake Detection at the First Greeting: "Hi!" Asvspoof 2021: Towards spoofed and deep- fake speech detection in the wild

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.545173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 78078ef2-2817-4516-a26f-3a4d218dc82b · outbound

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

Audio Deepfake Detection at the First Greeting: "Hi!" Asvspoof 5: Crowdsourced speech data, deepfakes, and adversarial attacks at scale

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.532418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c3b4b70a-42c4-4667-8cbb-6ec84d08f241 · outbound

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

Audio Deepfake Detection at the First Greeting: "Hi!" Add 2022: the first audio deep synthesis detection challenge

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.537694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 838be841-5a04-4221-b9f2-27641d050b11 · outbound

This paper cites Benchmarking audio deepfake detection ro- bustness in real-world communication scenarios.

Audio Deepfake Detection at the First Greeting: "Hi!" Benchmarking audio deepfake detection ro- bustness in real-world communication scenarios

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.540060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 929dec8c-b7be-43d5-a4bc-a70806d3029e · outbound

This paper cites Multi-Granularity Adaptive Time-Frequency Attention Framework for Audio Deepfake Detection under Real-World Communication Degradations.

Audio Deepfake Detection at the First Greeting: "Hi!" Multi-Granularity Adaptive Time-Frequency Attention Framework for Audio Deepfake Detection under Real-World Communication Degradations

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-16T11:07:48.299756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation dcc8a845-f90a-455b-8556-7d856ac0e626 · outbound

This paper cites Aasist: Audio anti- spoofing using integrated spectro-temporal graph atten- tion networks.

Audio Deepfake Detection at the First Greeting: "Hi!" Aasist: Audio anti- spoofing using integrated spectro-temporal graph atten- tion networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.550361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation aa6793e1-fd2f-49c8-8513-965ca704864f · outbound

This paper cites Domain general- ization via aggregation and separation for audio deepfake detection.

Audio Deepfake Detection at the First Greeting: "Hi!" Domain general- ization via aggregation and separation for audio deepfake detection

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.542739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c02beabc-3684-43c0-b769-1a3f35b3a77f · outbound

This paper cites End-to-end spectro-temporal graph at- tention networks for speaker verification anti-spoofing and speech deepfake detection.

Audio Deepfake Detection at the First Greeting: "Hi!" End-to-end spectro-temporal graph at- tention networks for speaker verification anti-spoofing and speech deepfake detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.586188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 78acbf48-ee40-494f-9a5e-f249dd4677c7 · outbound

This paper cites A comparative study on physical and perceptual features for deepfake audio detection.

Audio Deepfake Detection at the First Greeting: "Hi!" A comparative study on physical and perceptual features for deepfake audio detection

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.588637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 938f9066-47ce-410e-9f98-04b1d06b8316 · outbound

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

Audio Deepfake Detection at the First Greeting: "Hi!" A conformer-based classifier for variable-length utterance processing in anti-spoofing

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.577007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 13e433ee-fb48-4ae7-97ac-ea7584c9497b · outbound

This paper cites Low- rank adaptation method for wav2vec2-based fake audio detection.

Audio Deepfake Detection at the First Greeting: "Hi!" Low- rank adaptation method for wav2vec2-based fake audio detection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.579206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 05359564-6c10-4865-b6ff-91e0c8f3a1ea · outbound

This paper cites Im- proving short utterance anti-spoofing with aasist2.

Audio Deepfake Detection at the First Greeting: "Hi!" Im- proving short utterance anti-spoofing with aasist2

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.590606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 97547fcc-6978-4765-b30d-005e5ea3ef75 · outbound

This paper cites Xlsr-mamba: A dual-column bidirectional state space model for spoofing attack detec- tion.

Audio Deepfake Detection at the First Greeting: "Hi!" Xlsr-mamba: A dual-column bidirectional state space model for spoofing attack detec- tion

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.556904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fe6439f6-00af-493e-bfe4-2e77cf3701e7 · outbound

This paper cites Dynamic ensemble teacher-student distillation framework for light- weight fake audio detection.

Audio Deepfake Detection at the First Greeting: "Hi!" Dynamic ensemble teacher-student distillation framework for light- weight fake audio detection

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.574835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c0799b43-19a6-4809-8c63-002762923e7b · outbound

This paper cites The partialspoof database and countermeasures for the detection of short fake speech segments embedded in an utterance.

Audio Deepfake Detection at the First Greeting: "Hi!" The partialspoof database and countermeasures for the detection of short fake speech segments embedded in an utterance

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.569835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d03ba036-1944-4188-a613-977ff69fd265 · outbound

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

Audio Deepfake Detection at the First Greeting: "Hi!" End-to-end anti-spoofing with rawnet2

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.571941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ef197cc4-dfc6-4899-9bd4-3c98a5f77c83 · outbound

This paper cites For: A dataset for synthetic speech detection.

Audio Deepfake Detection at the First Greeting: "Hi!" For: A dataset for synthetic speech detection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.581301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9c2dceaa-600a-41d5-9d19-b8cd4c11baca · outbound

This paper cites WaveFake: A Data Set to Facilitate Audio Deepfake Detection.

Audio Deepfake Detection at the First Greeting: "Hi!" WaveFake: A Data Set to Facilitate Audio Deepfake Detection

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-16T11:07:48.305813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1c2a4745-7506-483a-8f6c-67c9f12ab7f0 · outbound

This paper cites The lj speech dataset.

Audio Deepfake Detection at the First Greeting: "Hi!" The lj speech dataset

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.567866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 83d685a2-ab54-47e6-a736-e7cd680dde3e · outbound

This paper cites Mlaad: The multi-language audio anti-spoofing dataset.

Audio Deepfake Detection at the First Greeting: "Hi!" Mlaad: The multi-language audio anti-spoofing dataset

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.583813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation aec6bc1b-6eaf-448e-9736-da4e676fd6b2 · outbound

This paper cites The m-ailabs speech dataset.

Audio Deepfake Detection at the First Greeting: "Hi!" The m-ailabs speech dataset

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.563839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5f731df1-8f89-4178-9eb5-b1cd301f192e · outbound

This paper cites Optimization methods for large-scale machine learning.

Audio Deepfake Detection at the First Greeting: "Hi!" Optimization methods for large-scale machine learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.566002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 54d73f30-2de9-4df6-8dbb-592a9060c6e7 · outbound

This paper cites Decoupled weight decay regularization.

Audio Deepfake Detection at the First Greeting: "Hi!" Decoupled weight decay regularization

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.559674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f4cf640d-661b-43c7-b2df-3bd30a015e2e · outbound

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

Audio Deepfake Detection at the First Greeting: "Hi!" SGDR: Stochastic gradient descent with warm restarts

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:12:47.561987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation 40bb36b5-548b-4f0e-9067-a622009676f1 · inbound