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Paper Citation Record · LEDGER

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection

As of 14 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2608.09593.

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

pith.paper-citation-record.v1
2608.09593 v1

Coverage vector

measured 80 of 80 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:31:01.058934Z

measured 80 of 80 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

80 of 80 outbound references displayed

  • verified exact1
  • verified fuzzy53
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a1da2697-a02c-4038-b713-052a931bfeba · outbound

This paper cites Proceedings of the IEEE/CVF international conference on computer vision , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the IEEE/CVF international conference on computer vision , pages=

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.735982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.735982Z digest=sha256:6971d39168834d42eeb2f09d325173a4549e4739bde2fea8bc90b8c4a09aaacf

Observation 6fdd7dd9-93b7-4baf-a245-8d544ea1a7a0 · outbound

This paper cites The DeepFake Detection Challenge (DFDC) Dataset.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection The DeepFake Detection Challenge (DFDC) Dataset

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.740719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.740719Z digest=sha256:7460fd4d485d7d0829ff9e713842335fc0f3f9a52e38729453a8267b3c0ac143

Observation 18f61cbe-d349-4058-8cbf-027bfef890b1 · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.349932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.745299Z digest=sha256:ca545bf67f3a19b504b60b5f84481370c30b171f679052250b7626b707cf0fcc

Observation 64690104-3068-4fe1-a956-c73c07941c57 · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , month =.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , month =

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.337185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.749174Z digest=sha256:65511fd221e6839b309b61e28042ae6f3d628513563a995e3922e3f58ab19dac

Observation 90813349-9c57-4a0a-90c9-ecb70281ad3b · outbound

This paper cites FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.753023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.753023Z digest=sha256:3a10db4c2f78a13f3e25c990f9d5ea9cc92b8d96dea78a8cf5151613429cf09e

Observation 2403e095-a99e-4da9-859e-7ad3def6bd87 · outbound

This paper cites 2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA) , pages=

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.324564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.756978Z digest=sha256:6fb206f8db45ffa469c91f00d4fc03372bbcda905c87b52091a06305605f614e

Observation 3d147709-f32a-4a6b-a848-33270b5e9940 · outbound

This paper cites 2024 , isbn =.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2024 , isbn =

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.760337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.760337Z digest=sha256:c9f27c541594b6829a631ab25d31ef6fedf69be303cc260469534d1d064fc1d1

Observation 56aaa945-fc35-4656-ad73-5197fceac14b · outbound

This paper cites Computer Speech & Language , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Computer Speech & Language , volume=

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.763580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.763580Z digest=sha256:991a92e960c322d2657bb9d05b966d13d5b247d08e5efab4a38e662eca45cb28

Observation 0ae87d91-7c7f-455e-a2be-0e95df44bc1f · outbound

This paper cites IEEE/ACM Transactions on Audio, Speech, and Language Processing , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection IEEE/ACM Transactions on Audio, Speech, and Language Processing , volume=

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.767160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.767160Z digest=sha256:2b1b8cae45c28732acd66d3a61387d75fbd73f352c360250dbb9d672f0582cb8

Observation 17aae820-c3a3-4259-bb70-d888c2fe3485 · outbound

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

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.770648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.770648Z digest=sha256:d3686c8bc5f1244a12add235c20d99cf8e427c91fb6dac08bd2df58651752263

Observation 514eb979-6189-4080-86d6-0190cb5662e8 · outbound

This paper cites ICASSP 2022-2022 IEEE international conference on acoustics, speech and signal processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2022-2022 IEEE international conference on acoustics, speech and signal processing (ICASSP) , pages=

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.774156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.774156Z digest=sha256:67cb9ef57dc402d5ef8c9d45054138e5eefab17795c2f20d6b10a8814927d5ab

Observation 13696b7d-c9bf-4d02-96d6-942bb0b8fe62 · outbound

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

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection WaveFake: A Data Set to Facilitate Audio Deepfake Detection

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.778198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.778198Z digest=sha256:d0062f048337cceff8f6e0de346115d884ec24f76b5af73dfea9902330749fb3

Observation 17aa2b48-8173-47ea-969f-c2271dd0cc3f · outbound

This paper cites IEEE/ACM Transactions on Audio, Speech, and Language Processing , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection IEEE/ACM Transactions on Audio, Speech, and Language Processing , volume=

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.287854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.781982Z digest=sha256:53c8cda8d7aa09a78435517ba023bd756f01af388e8fbb59eba632773843aa07

Observation 561c049e-96ad-480d-9eca-3549fced96a6 · outbound

This paper cites AudioGen: Textually Guided Audio Generation.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection AudioGen: Textually Guided Audio Generation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.785155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.785155Z digest=sha256:2888c111b1bed65d864c4a162282d0a25cf9001e71828c405a2ea7cfd9f2a873

Observation 12f5a2b2-a70d-41d7-93af-cf9ad3508f90 · outbound

This paper cites , title =.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection , title =

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.274457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.788981Z digest=sha256:0e295c4464c29510e05b0385f5e7fdb0966c70596a55e164816bde0e8baf562d

Observation c886858a-47f6-4629-a684-6877cfa36fbd · outbound

This paper cites IEEE/ACM Transactions on Audio, Speech, and Language Processing , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection IEEE/ACM Transactions on Audio, Speech, and Language Processing , volume=

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.792519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.792519Z digest=sha256:3257ecef1c60aabee3d899093525134d925ca2f6de8fc2b90f1e99393fe7b8b7

Observation 81038192-3e2f-436b-a1ba-c363d9b87a49 · outbound

This paper cites Proceedings of Interspeech , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of Interspeech , pages=

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.256602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.796569Z digest=sha256:0d06a85618284f173d7e82af13c69510406644d3aad348fb658b2948a424cf29

Observation 0a2ded39-02a7-41ed-a155-321efad41616 · outbound

This paper cites ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , year=

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.244809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.800235Z digest=sha256:76ffc3559deef02be788bc1b8bc989aedea637b1d7680240442969331efe4fca

Observation 251dd8a9-4a59-45e1-8c03-465cdc18fca3 · outbound

This paper cites INTERSPEECH 2026 , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection INTERSPEECH 2026 , year=

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.231835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.804321Z digest=sha256:14aac166c5766a6bbc0d7d99beba8b9a4e90f11daa5065823c64a8c84a886ead

Observation 20f9d01f-89ad-4d5e-9440-be0a9e9be8da · outbound

This paper cites 2026 IEEE International Conference on Multimedia and Expo (ICME) , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2026 IEEE International Conference on Multimedia and Expo (ICME) , year=

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.219122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.808603Z digest=sha256:00f3325068b97a5a2951428a80de09fca25f5fcfee2c79b8057d82826616b58a

Observation 87b2f847-3dc1-4b4f-b8be-a5eae3780442 · outbound

This paper cites ICASSP Grand Challenge Evaluation Plan , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP Grand Challenge Evaluation Plan , year=

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.207203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.813934Z digest=sha256:62efd92b1c9e5422d04748c1971480dedad930fb9fbd28bf1689dd33d3993d29

Observation 783544e2-1c89-4e84-b380-346fd3decb3d · outbound

This paper cites ICME Grand Challenge Evaluation Plan , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICME Grand Challenge Evaluation Plan , year=

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.195190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.817886Z digest=sha256:4020ab1f6c32d6378f0191ee43dd3bc0fec14fd2cfaf2992fb11c46427b8c6d0

Observation 0f456d3a-1629-4e93-9508-c92ebf808190 · outbound

This paper cites A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook

Reference 23

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T14:31:01.447278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.822147Z digest=sha256:aca25a91061006e2bf231a2321d14c6a407b9b93382e531a0a4008333b674312

Observation 1aa5d988-e214-48da-a82b-204c4031fecc · outbound

This paper cites Proceedings of Interspeech , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of Interspeech , pages=

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.182844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.826549Z digest=sha256:e8a21c81a8d39cda1109d07bee99f03f0aa6dd3849f2c50b9e100fb1cdde4ba8

Observation 9108c2f9-c3c0-4785-b6c5-c6cd8f2b5afb · outbound

This paper cites 2016 24th European signal processing conference (EUSIPCO) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2016 24th European signal processing conference (EUSIPCO) , pages=

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.171056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.830856Z digest=sha256:8a767b1f518c8b01f28a6c0eb69eb4497f481c5e62d5568908abcee4f3235a59

Observation db55ea79-95bf-4300-9118-c90c07d62946 · outbound

This paper cites ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.834206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.834206Z digest=sha256:039d7e9f18c7fb00e81b4d92b92183b3f99482f0e942a3660c949d44f772fdd4

Observation 3f58ba92-aa52-4662-b65e-91a7c0fbc011 · outbound

This paper cites 2017 IEEE international conference on acoustics, speech and signal processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2017 IEEE international conference on acoustics, speech and signal processing (ICASSP) , pages=

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.838023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.838023Z digest=sha256:bfd6842401491f70dc8feb0b5554b8cdbb32ba7991f61792eb4dc2dc5f46205f

Observation 30394f21-ed0a-4e3c-a799-c5a5e899bdbb · outbound

This paper cites 2019 , publisher=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2019 , publisher=

Reference 28

Resolution
verified exact
doi, observed 2026-08-11T14:31:01.099091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.841579Z digest=sha256:d1fa0e7b829334a256ddc41fe3fda7854fc29fe8cfb83e983cd282110eb82c07

Observation c33ac3cb-e184-4a36-9476-20d68e8d568b · outbound

This paper cites International conference on machine learning , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection International conference on machine learning , pages=

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.845227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.845227Z digest=sha256:1819a9f7adaf73d614a9cccfaecdcc8abe39262c389069d10eb1ff0808e64d0a

Observation 4f23f63b-f373-4786-bc13-7346fe203edb · outbound

This paper cites ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.848906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.848906Z digest=sha256:7ade58ecbb82b16da7be20c23d39a0453cd03cf2870fdc9c446c02c268aec509

Observation c2cad614-cac0-4e7b-9e34-1ffa083df70a · outbound

This paper cites 2023 , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2023 , volume=

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.125607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.852452Z digest=sha256:430414640ce484508e2699caa3ba4ff8dbca58e5df573bb0f664858b9db2ddf8

Observation 51344037-c096-4c6b-8e19-35173b9fcbd7 · outbound

This paper cites IEEE Journal of Selected Topics in Signal Processing , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection IEEE Journal of Selected Topics in Signal Processing , volume=

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.856125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.856125Z digest=sha256:ebdd97c5bd4855fc6c6c20796377774974dfe13c3580f11ca3e06f23cc2d3a1d

Observation 1769326f-1779-4d3f-a589-05ec7d586afb · outbound

This paper cites 2023 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2023 , eprint=

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.104574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.860208Z digest=sha256:f10e9c41327e49f9eed5f3e2777f601102fd1af6d56dea8dce2d92ec76a205ba

Observation be75a2a7-7d1c-433f-9fc3-d7508910698a · outbound

This paper cites 2018 IEEE international workshop on information forensics and security (WIFS) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2018 IEEE international workshop on information forensics and security (WIFS) , pages=

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.093566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.863642Z digest=sha256:d104fcb516965569e7fcf5274e0407ebc6dc14f4a6d5553f856fe87c056df355

Observation 5a02ff02-afe8-4f95-a331-43bdd0422f03 · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.082093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.867266Z digest=sha256:ada1069229cfaa43790dbecb28b3dcd08e8bb423c69aaf8a24a8b997579999c3

Observation f12855c1-6059-45b8-91b7-dcbcccd3e0c8 · outbound

This paper cites Proceedings of the 28th ACM international conference on multimedia , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the 28th ACM international conference on multimedia , pages=

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.071303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.871114Z digest=sha256:dc3c4f5795c9690ad3bbe7d5d45de8f66a06ed32eb4058496864b1dbd0549a8f

Observation b0b04500-1ce2-4498-8e0c-ac1bcbb63bfc · outbound

This paper cites Proceedings of the 2023 ACM International Conference on Multimedia Retrieval , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the 2023 ACM International Conference on Multimedia Retrieval , pages=

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.060163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.875267Z digest=sha256:6fec5b555719f100f29512cf936e170f99d556e2086f5049d68de61d2c95ba5d

Observation f1438510-7058-42ca-9641-ea8d3bab8426 · outbound

This paper cites Proceedings of the Computer Vision and Pattern Recognition Conference , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the Computer Vision and Pattern Recognition Conference , pages=

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.046515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.879321Z digest=sha256:3bc2ed794c9d24304d7a3443baea8b13ae057e1a29c96c5ddb78f65860cd7df0

Observation c82200d0-3bb6-4367-8673-c017a44ed73e · outbound

This paper cites ACM Transactions on Multimedia Computing, Communications and Applications , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ACM Transactions on Multimedia Computing, Communications and Applications , volume=

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.034256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.883862Z digest=sha256:3483b22dbda74bc4442ab64f1e8f1b3c2fd897cc15e676566b0dbb3831f46bf1

Observation 6b027bda-a45a-42ec-aeb3-c262dbf727e9 · outbound

This paper cites ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.019241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.888012Z digest=sha256:782627c2f170e7e50b2a50406302d8ba072589884c2bef0558ef73522e8f5973

Observation 70cd0cd1-7e4a-40fc-a7a2-09f65410f7bb · outbound

This paper cites 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) , pages=

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:02.003507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.892329Z digest=sha256:835c8730a627ef9751acbfe05d944ed01dadb8e437e11e26c59cad05c6707813

Observation 12268ea4-f24f-494f-b4b8-3e1564e6f7ee · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.990233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.896191Z digest=sha256:71aff7c47ef6c585cf8d8bcf4f1b87519c376a44eaa76260485669092d0ea5c7

Observation 338fa2b4-4fe4-471d-bcad-f8abcba8383d · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Advances in Neural Information Processing Systems , volume=

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.977906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.900182Z digest=sha256:ac592c56acaaa8fc99ae8e0e3c326b865ca4024f69245e29d0569c5e3af1c262

Observation 02765560-25a2-4096-aafd-5cd365ba40d5 · outbound

This paper cites IEEE Transactions on Human-Machine Systems , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection IEEE Transactions on Human-Machine Systems , year=

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.966124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.904262Z digest=sha256:3385631a114671112bd04344198bd775ec135dfc7481ea509070d5543123aa25

Observation 2fafd9c2-5440-4feb-b01f-835c06011127 · outbound

This paper cites ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.953757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.907672Z digest=sha256:53a869892234f821c9375f85ed0b7239f59c70dcfb84aebd2d0e2dafdd1c90af

Observation 89655bfd-c857-44ae-aa63-e7828247656e · outbound

This paper cites AVoiD-DF: Audio-Visual Joint Learning for Detecting Deepfake , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection AVoiD-DF: Audio-Visual Joint Learning for Detecting Deepfake , year=

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.941353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.911882Z digest=sha256:79286d2f4d33e6c97c55ab8abd70897dd9db231e5df6da4aaba0f2728b3a14d5

Observation a120d632-a883-4297-8392-1abec29f8182 · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , month =.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , month =

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.929319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.915860Z digest=sha256:1f15d8f0c7c735f1f6eeeb3625227ba562f86d34a78e4a13b779193e97602ea4

Observation 2224bac7-bfd1-4e31-a8eb-f26b27703a62 · outbound

This paper cites AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection , year=

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.917155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.919295Z digest=sha256:49a73f73c8473c1f5b6ab0046dbb1cdea90d76c5b560e36387617d11806bfee1

Observation e4147ad8-f34b-4d20-a285-31d5de53af22 · outbound

This paper cites Contextual Cross-Modal Attention for Audio-Visual Deepfake Detection and Localization , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Contextual Cross-Modal Attention for Audio-Visual Deepfake Detection and Localization , year=

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.905298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.924250Z digest=sha256:f24d30107e8e5ef6f494604de4a2799dd980a2db6ea36e7e2e779453196bd38c

Observation 0469ebac-7041-4f28-bf3e-558007119f9e · outbound

This paper cites 2025 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2025 , eprint=

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.928038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.928038Z digest=sha256:bf4d0a069df0923bd90b36103f5aca74173ee9251dd80731b6fa4d6ed8a36437

Observation d1fe3d1d-6ddb-49a5-9903-3a9d6501f684 · outbound

This paper cites 2026 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2026 , eprint=

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.932217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.932217Z digest=sha256:3554233b68ad2e4a6db93807d18f2ebb94250e95fa65cd38a45ce4b8a473c99c

Observation 78d4f500-1180-41b3-90ce-d00a7a687946 · outbound

This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , pages=

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.877094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.936492Z digest=sha256:7782d58199cbd210399861bde44ee3d71891c763ff22963756ee33dc83773471

Observation 47feda4e-a90a-4fb6-a686-0a66f2bb3b6f · outbound

This paper cites ACM Transactions on Graphics , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ACM Transactions on Graphics , volume=

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.867158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.940889Z digest=sha256:194ddafbe1fbd7c615e317f96d22af533b971761602acf7a6f215fac6f71942d

Observation cf0c1592-a009-40af-95bb-dc044993d94b · outbound

This paper cites and Rubinstein, Michael , title =.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection and Rubinstein, Michael , title =

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.945383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.945383Z digest=sha256:6e61514398203da9a3b45ad90ca713baec89c853839bed1e820de7641547320e

Observation 27729264-f4da-4f88-b626-4010bcbc4e21 · outbound

This paper cites ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.857293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.953615Z digest=sha256:889e48fe18d9b4cef5abd0a96a8a71afb7765f1d71a10e75c67fd55c9a4244b8

Observation c4158688-5dfa-4bf6-bf95-cbd2ab3728f8 · outbound

This paper cites an unresolved cited work.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Unresolved cited work

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:00.957540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:00.957540Z digest=sha256:63e9088b776c50f5ff6c5be5bf4f2d6b0be974f9d778937d87cf6f8c75696769

Observation ce2402f7-1361-4430-a364-46b40bffeb16 · outbound

This paper cites and Zhou, Y.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection and Zhou, Y

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.845288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.962638Z digest=sha256:2114f1ff415fb7de7dbcb367bca189dfedd1af3d70e03cb6bcd526a3a041345b

Observation 29420507-0a36-4e07-a739-df3f8938b3d0 · outbound

This paper cites 2024 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2024 , eprint=

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.833773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.966726Z digest=sha256:3b58ea75a77a404240e02971ba9f3eb9a7a7c94810624251083ee86f6920da8b

Observation 27f165d5-ee4b-4af8-bdcd-6d9011e36c74 · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection The Thirteenth International Conference on Learning Representations , year=

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.821546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.970283Z digest=sha256:a5ef34cab101734fdc1047dbd14406a5d1f6bf856fc353af05450a3fb6939b29

Observation a253fc15-2c54-467b-8066-70f912fcf8f8 · outbound

This paper cites 2020 , doi=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2020 , doi=

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.808705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.973898Z digest=sha256:423007ccb37b38a18c1167ec89e7f8c473913754ace1d0d7bc9781a98ccef73e

Observation 509bde39-3272-499b-9d07-e048cf615038 · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection The Fourteenth International Conference on Learning Representations , year=

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.793621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.977510Z digest=sha256:cfbd93c01ccb58eed5461fcaaf26a371526fd28e1dee44cf90590c14a8ab8417

Observation ccd3222c-62f9-496b-9036-50353c3ab68f · outbound

This paper cites 2025 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2025 , eprint=

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.781717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.981215Z digest=sha256:e8a549f0f6fec777489f770241ff6829660eea558000a5ca0ce317a80af11a90

Observation 3fddc8a2-f4a7-44e1-8453-fcf808cf17f5 · outbound

This paper cites 2024 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2024 , eprint=

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.770232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.984830Z digest=sha256:070a91b79b46e328dafaf7d2796605085757a1c23576e1485dca98f605639473

Observation 2c17e74b-5818-4657-9056-428541dc5931 · outbound

This paper cites 2024 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2024 , eprint=

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.758935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.988653Z digest=sha256:2fcefa4a04882bb37ecb0ba75874c7dfc392b6a8dbcaf7da4911466a01e43c54

Observation 2d61a8fd-dd5f-432d-8425-3ca6fcc8c40c · outbound

This paper cites 2025 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2025 , eprint=

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.746610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.992615Z digest=sha256:3226b13b37a06e36a8dbc50d04a6efc9c2b325e7a3ae6b60be0497f7502c9a1c

Observation 9b89aad0-e4f4-4eef-920d-9733ccc4a104 · outbound

This paper cites Computer Vision and Image Understanding , volume=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Computer Vision and Image Understanding , volume=

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.735939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:00.996532Z digest=sha256:eb07ac49b034fbae805a56154639b70794ebf91873e43694ff3551d96aa18253

Observation eeb72b8d-d22a-42b2-9002-94f2a09062c5 · outbound

This paper cites 2025 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2025 , eprint=

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:01.001153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:01.001153Z digest=sha256:a37733c541c00505eb47bd2daf09c28d5c07817ce7ee344a105a05ab0b802472

Observation 52f14b2b-95bd-499e-b2e6-e09af9e37a68 · outbound

This paper cites 2021 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2021 , eprint=

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.716373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.005102Z digest=sha256:90bdd0f0f6960770d78f8642637f9e7e4bbb59291d88e843841655505cf04571

Observation 74039481-95d2-4b4e-beba-69d03d46611d · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages=

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.705142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.008861Z digest=sha256:3b708c2a637f0f2134e2080fb57cc89e76f85c01e2372445d78eede1df77e203

Observation f31973ea-e1aa-467a-885f-e0d9311691aa · outbound

This paper cites ADD 2023: the Second Audio Deepfake Detection Challenge.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ADD 2023: the Second Audio Deepfake Detection Challenge

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:01.012994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:01.012994Z digest=sha256:9fa33444e192ce755ee0f2462a41775b439e341493560024542d578826514bb1

Observation fd88a61b-d54b-42cf-9262-ef963362c011 · outbound

This paper cites ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.691341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.018492Z digest=sha256:d68e3223b81a488001b881d30a1981be0ca64e0084e20257d502017c472f5688

Observation 835d2d76-27e2-48f2-9d52-d89010047579 · outbound

This paper cites and Wilson, Kevin and Thorpe, Jeremy and Chinen, Michael and Patton, Brian and Saurous, Rif A.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection and Wilson, Kevin and Thorpe, Jeremy and Chinen, Michael and Patton, Brian and Saurous, Rif A

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.678272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.023295Z digest=sha256:bbf9fb5e8096fd160dae3a4831f5e3e3faf28ee2dc1747dfa7f41938b67a1858

Observation e9cfc5c0-ec67-4ced-9c56-9de429cff8cd · outbound

This paper cites ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.666041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.027599Z digest=sha256:a9855b1b258ba08ab2074c640c82236a2f261c24d9c768212d7f9a872778707f

Observation c17bb496-2096-4798-a788-7c7ee5852367 · outbound

This paper cites arXiv preprint arXiv:2512.19687 , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection arXiv preprint arXiv:2512.19687 , year=

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:01.032424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:01.032424Z digest=sha256:70f9cbcad7aeafccca106bac0a9b38fbe6a4cdd3317ae966297ccb6e2e54019d

Observation 9638767e-1b02-450b-bc6f-2dd8b7803001 · outbound

This paper cites Proceedings of the Computer Vision and Pattern Recognition Conference , pages=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Proceedings of the Computer Vision and Pattern Recognition Conference , pages=

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.654048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.036641Z digest=sha256:2f80d5df76e74fea2fb4e5b7cab6f0bf55bf001905d16e1d849a7c1052e9e552

Observation 5a0c026d-6a49-4b40-bee8-7649e165ac1a · outbound

This paper cites arXiv preprint arXiv:2501.15368 , year=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection arXiv preprint arXiv:2501.15368 , year=

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:01.041325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:01.041325Z digest=sha256:e069f428d5e150338eae2da64c9bc590fa8c74098f69bcd022780cf02b0e0e81

Observation bf9aa9db-553a-4c55-816a-232b5d2f7180 · outbound

This paper cites Gemma 4 Technical Report.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection Gemma 4 Technical Report

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-11T14:31:01.047215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:31:01.047215Z digest=sha256:6bc2f04a6b20735ae89deefad8779bb84ba62b8bbd71c99026f35979e06d544b

Observation 0a4f8b76-2526-43b5-a072-6239cb522f7d · outbound

This paper cites 2024 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2024 , eprint=

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.641844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.051780Z digest=sha256:9d5842b908394504abd1a189dfbbfdbae3288e525f41e640c5e317984831a0d0

Observation 9416d375-af2d-4fe0-b34f-eb9bb677accc · outbound

This paper cites 2026 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2026 , eprint=

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.628661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.055678Z digest=sha256:8deeb2f4726a3b458c5197919cd1d1fd2c3d8ea7438fcf2505fd0d378c0363d9

Observation c36d2d82-1a8a-4401-be25-949b2e371af7 · outbound

This paper cites 2026 , eprint=.

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection 2026 , eprint=

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:31:01.613023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T14:31:01.058934Z digest=sha256:5bf7dfc5bfde05e119fef11891e45d02d3389da2eab902e85d18f4d9992cb9b7

Pith citing papers

No inbound Pith citation observations are available.