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Paper Citation Record · LEDGER

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2502.01152.

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

pith.paper-citation-record.v1
2502.01152 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:26:44.317772Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:08:59.070038Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:08:59.785683Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact2
  • verified fuzzy24
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 47cfd047-1361-4995-81d9-101343d2f089 · outbound

This paper cites Deepface: Closing the gap to human-level performance in face veri- fication,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Deepface: Closing the gap to human-level performance in face veri- fication,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.701035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3c18d9e7-3f3c-4fab-8078-0382338d0464 · outbound

This paper cites Face Recognition Methods & Applications.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Face Recognition Methods & Applications

Reference 2

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no resolver link, observed 2026-08-09T16:26:44.198910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4782955f-54e5-48d3-83c2-9a8ee9579cb5 · outbound

This paper cites Study of automated face recognition system for office door access control application,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Study of automated face recognition system for office door access control application,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.691420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.202846Z digest=sha256:dec73ccd34393f92c82ba65f43a6c76412e757626c25666cb01309b1cc15b786

Observation b90c433a-c2f6-4d27-8901-a22b92e2f49a · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition nuscenes: A multimodal dataset for autonomous driving,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.682209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.206399Z digest=sha256:a82e82be945da19841a9e393265ab6658125d92b208a4c65cac5ea438828c3c1

Observation bfe21cab-b55f-4700-928e-c9868cf51b38 · outbound

This paper cites A survey of autonomous driving: Common practices and emerging technologies,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition A survey of autonomous driving: Common practices and emerging technologies,

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.209904Z digest=sha256:15e875fa5f80e567607d0786dfe1f6cf7548f2a4d9a7721e2d77b4093989674b

Observation 95f13d1f-70d6-42bf-a2ee-afb7b2ef7238 · outbound

This paper cites Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

Reference 6

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unresolved
no resolver link, observed 2026-08-09T16:26:44.213201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:26:44.213201Z digest=sha256:4bc7cd4c22b8180b0435543e9a8dcb657028f1e5fe527f7959503129bcf35664

Observation 244c2bae-73f7-4eb2-a270-ff016a6f8b94 · outbound

This paper cites Automatic speech recognition: a survey,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Automatic speech recognition: a survey,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.662503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d575614d-bca6-4a2b-8576-83c0d9ab6389 · outbound

This paper cites Badnets: Evaluating backdooring attacks on deep neural networks,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Badnets: Evaluating backdooring attacks on deep neural networks,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.653009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.221072Z digest=sha256:cf06562c43f13eca4952018b6705fb124844239bf90814fee4a32c8cda696b8d

Observation ba5a99d6-8980-4b36-9f9c-5598c361b370 · outbound

This paper cites Backdoor Attacks against Voice Recognition Systems: A Survey.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Backdoor Attacks against Voice Recognition Systems: A Survey

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-09T16:26:44.438167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation eed978dc-ab35-4f4f-87c2-15b4b275e7d0 · outbound

This paper cites Fine-pruning: Defending against backdooring attacks on deep neural networks,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Fine-pruning: Defending against backdooring attacks on deep neural networks,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.643075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.228089Z digest=sha256:85f54b34d3f0aba093ebb8e0c22e5ee9845e282fa868c6e53cdd875a3bb003a0

Observation f203c723-b781-49ab-9d57-d08b3de9ac31 · outbound

This paper cites Adversarial neuron pruning purifies backdoored deep models,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Adversarial neuron pruning purifies backdoored deep models,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.632997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.231551Z digest=sha256:1c2c59c4730527ffd0a1a493ab55ff7e84ef3918fcb23dff07bca10934f39148

Observation 0717d614-4186-4101-832c-7ebd16ac1b48 · outbound

This paper cites Anti-backdoor learning: Training clean models on poisoned data,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Anti-backdoor learning: Training clean models on poisoned data,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.621394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.234898Z digest=sha256:404627c565e01ad60926facbae214acf16fc70293343be2ff99b52c6108785e0

Observation c7c21856-6681-452a-b120-96b49e5ca761 · outbound

This paper cites Backdoor Defense via Decoupling the Training Process.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Backdoor Defense via Decoupling the Training Process

Reference 13

Resolution
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no resolver link, observed 2026-08-09T16:26:44.238141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:26:44.238141Z digest=sha256:2f80ef6f2acfe08eee61ac40ad5c56285921e587872c528f6975c57f9f616bdf

Observation 37bbbe49-6eef-4481-93f1-293a62c26494 · outbound

This paper cites Reconstructive neuron pruning for backdoor defense,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Reconstructive neuron pruning for backdoor defense,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.611742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.241672Z digest=sha256:af53577a365f19b7b3e31ae5ed1cd4a819403e1570186cb1a7ccbbda31fd2be3

Observation 038988e5-a83b-40cc-8d84-9b6c969a40e3 · outbound

This paper cites Defenses in Adversarial Machine Learning: A Survey.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Defenses in Adversarial Machine Learning: A Survey

Reference 15

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no resolver link, observed 2026-08-09T16:26:44.244831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 72a597f1-341f-45fb-91f2-45157cecc351 · outbound

This paper cites Strip: A defence against trojan attacks on deep neural networks,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Strip: A defence against trojan attacks on deep neural networks,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.602371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.248656Z digest=sha256:ee92836ee32568ded7c0515ab82bf57845064156a2b00cb6e58efb311eafd4c4

Observation fa076d9b-47e8-40dd-808a-df89a3c49902 · outbound

This paper cites The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram Matrices.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram Matrices

Reference 17

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no resolver link, observed 2026-08-09T16:26:44.251843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c12b5e2c-d453-403c-a2fe-7a9351a6b37a · outbound

This paper cites Magnitude-based Neuron Pruning for Backdoor Defens.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Magnitude-based Neuron Pruning for Backdoor Defens

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-09T16:26:44.397453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation da63a96b-92d0-4555-836d-1bf8d8d2c6d4 · outbound

This paper cites Penalizing gradient norm for efficiently improving generalization in deep learning,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Penalizing gradient norm for efficiently improving generalization in deep learning,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.592650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.258733Z digest=sha256:c41e4eb175c3baa2661176710c14a8b705dcf8b81541cd55e6a11dc1adf3cb18

Observation ba5fdf36-c04e-4f6b-963b-9659a2a84ae5 · outbound

This paper cites Going in style: Audio backdoors through stylistic transformations,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Going in style: Audio backdoors through stylistic transformations,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.582809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.262107Z digest=sha256:6438afbc291bbe9aba569ea3197ef05399872afffb0b500996beb51be24f8367

Observation 69f04978-3462-44c2-8c14-22f21c1aeb62 · outbound

This paper cites Deep residual learning for image recognition,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Deep residual learning for image recognition,

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-09T16:26:44.265347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:26:44.265347Z digest=sha256:efb9b50a20e5a9bba6b5b4f0351198ca35e4a454ac2c8ce5ec754c65390714a9

Observation 0b0a38a1-041e-4e5b-8262-787ea2cfaf6f · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-09T16:26:44.268739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:26:44.268739Z digest=sha256:8fb74767a5f4cd382265d3d4c86e29ecdec2683f6b5f46351f7cad6bfb6307fa

Observation 17daf5ed-49f1-4026-843d-9913388a3099 · outbound

This paper cites Input-aware dynamic backdoor attack,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Input-aware dynamic backdoor attack,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.567331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.272594Z digest=sha256:2671d254f7707e3ee243f1c734aeed2f75ecac8e546af1bcbc94bea7fffbe11e

Observation 90c62155-0a4a-4b71-80f1-8deedc3d2151 · outbound

This paper cites WaNet -- Imperceptible Warping-based Backdoor Attack.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition WaNet -- Imperceptible Warping-based Backdoor Attack

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-09T16:26:44.275644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:26:44.275644Z digest=sha256:cfefb68de76fe13494477b7c221414a414328c177f256523247377250c1f1a36

Observation fc35d228-1a25-4234-8953-4a59cf5ff5ee · outbound

This paper cites Bppattack: Stealthy and efficient trojan attacks against deep neural networks via image quantization and contrastive adversarial learning,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Bppattack: Stealthy and efficient trojan attacks against deep neural networks via image quantization and contrastive adversarial learning,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.557948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.279082Z digest=sha256:f220e09391a4e5a1652b3624ed1fbe5b4818489d878bdd3a4752fb14b5dc560a

Observation 0ed40e45-cd0a-4fc5-9169-0db2e31b382f · outbound

This paper cites Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-09T16:26:44.282244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:26:44.282244Z digest=sha256:0f25de2ba72321c500d70dd9509c9c66516b13fd2447edc05cffa312c97593c6

Observation 7f958a7d-90f3-460f-b40f-8fa877f8ef77 · outbound

This paper cites Can you hear it? backdoor attacks via ultrasonic triggers,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Can you hear it? backdoor attacks via ultrasonic triggers,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.548122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.285647Z digest=sha256:39290461683e21e9ec80a43ef96d08e04305d326bed0da3993b38a29febe7749

Observation 7d61d50c-c969-406f-9203-2b4825d4057b · outbound

This paper cites Oppor- tunistic backdoor attacks: Exploring human-imperceptible vulnerabilities on speech recognition systems,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Oppor- tunistic backdoor attacks: Exploring human-imperceptible vulnerabilities on speech recognition systems,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.538539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.288985Z digest=sha256:4f99c7f95179a2f4b6c10254bdea1e1660b22cac76509e76ffd8cee66cbc6a09

Observation 241601a5-1e02-433d-92cf-176f59d8b822 · outbound

This paper cites Towards stealthy backdoor attacks against speech recognition via elements of sound,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Towards stealthy backdoor attacks against speech recognition via elements of sound,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.528848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.292157Z digest=sha256:0df3f3096db62862cac96ab2cde4b1cfe3f0a1863ea7051f598dfa2f0ec017d0

Observation 4ebd42e1-ee5b-4fd3-ba35-7107c1eb174b · outbound

This paper cites Flowmur: A stealthy and practical audio backdoor attack with limited knowledge,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Flowmur: A stealthy and practical audio backdoor attack with limited knowledge,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.518393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.295235Z digest=sha256:5cbf4a867e9462cc0b06de58cff130dc37a36ab3ed042ae3aa9770d04bbc078a

Observation facf4f0e-7932-441c-8156-3b2cce722074 · outbound

This paper cites Long short-term memory,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Long short-term memory,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.508008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.298170Z digest=sha256:0b699aa28d0dab3e920957c4261d49f75e92d3460c61fb8e5f4fd2185978ba58

Observation 2ad07f71-8a7e-4ea4-9f92-c3978ad25f62 · outbound

This paper cites Introduction to convolutional neural networks,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Introduction to convolutional neural networks,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.496935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.301395Z digest=sha256:da04ac01ccf7162d4e29f1410e0bf90358e98f91822f98af8ad6a36d0034db3a

Observation 224d0f52-0119-4a3b-97ce-5770514b9c32 · outbound

This paper cites Adversarial example detection by classification for deep speech recog- nition,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Adversarial example detection by classification for deep speech recog- nition,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.486703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.304379Z digest=sha256:09dc5c2c9002f072e067725b09b64845384325597aee9bb5c73186667fd02d70

Observation c6e5fb32-9761-46b5-8b5b-e1e64cc24c91 · outbound

This paper cites Keyword Transformer: A Self-Attention Model for Keyword Spotting.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Keyword Transformer: A Self-Attention Model for Keyword Spotting

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-09T16:26:44.307677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:26:44.307677Z digest=sha256:eaec07c871f8718fe1a7ce21f63e1a4e402d9f9730d2b1024a22997652006faf

Observation 95f1a151-8fb1-4eb1-8dfc-172ec9d7ef66 · outbound

This paper cites End-to-End Audio Strikes Back: Boosting Augmentations Towards An Efficient Audio Classification Network.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition End-to-End Audio Strikes Back: Boosting Augmentations Towards An Efficient Audio Classification Network

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-09T16:26:44.311161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:26:44.311161Z digest=sha256:32ced56dd9133cf1501ca075138fa461ff40bbab3e5d395a544f2f36229802c3

Observation c1a5123b-15c1-41b7-bf6d-540469be9c0d · outbound

This paper cites Feature extraction using mfcc,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Feature extraction using mfcc,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.476399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.314606Z digest=sha256:33914e726b060453842a9cfb935c87276e69a301a801959191f15b999f795a43

Observation 4f112601-d983-4bcd-bede-a709795da6a3 · outbound

This paper cites Visualizing data using t-sne.,.

Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition Visualizing data using t-sne.,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:26:44.465961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T16:26:44.317772Z digest=sha256:48ef25ea6a3df57896ea6c9a05e4214ce722b766239b64c9f5d634f4ff4177ff

Pith citing papers

Observation 9d551f57-9e41-4827-b69d-881870e55c21 · inbound

Investigating Vulnerabilities and Defenses Against Audio-Visual Attacks: A Comprehensive Survey Emphasizing Multimodal Models cites this paper.

Investigating Vulnerabilities and Defenses Against Audio-Visual Attacks: A Comprehensive Survey Emphasizing Multimodal Models Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition

Reference 148

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T04:08:59.918719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T04:08:59.070038Z digest=sha256:856a76ece2b36418e605042d17d00700a149a4db65a80af0659febf72e9c1725