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Paper Citation Record · LEDGER

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks

As of 22 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2606.04317.

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

pith.paper-citation-record.v1
2606.04317 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T06:29:34.540587Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

51 of 51 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved47
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d161c61-8a1f-499e-9ffe-e59749e9fb96 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Imagenet classification with deep convolutional neural networks,

Reference 1

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:bdd04c4509d80be98cccc1efe7a722fc325c906152a32ecc1c63ff6dc65cd381

Observation a04340f9-0822-483d-9a48-113d4551cdfd · outbound

This paper cites Learning deep structured semantic models for web search using clickthrough data,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Learning deep structured semantic models for web search using clickthrough data,

Reference 2

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Observation 562acf56-727d-480f-afe2-10d4363128d9 · outbound

This paper cites Wide & deep learning for recommender systems,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Wide & deep learning for recommender systems,

Reference 3

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:789870234029b200bba90b4963f1e7d3a2381a7e2f8056b5cda5481bdd97e70e

Observation 1e9cff5d-c348-4355-aa4a-03734af1fb14 · outbound

This paper cites Deep neural networks for youtube recommendations,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Deep neural networks for youtube recommendations,

Reference 4

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:aa9412c05dea8f499898f90126eb75fa308d1823e8bdd6746e985fec8757386f

Observation b38ab979-c599-472a-b2e9-f690db1c1ecb · outbound

This paper cites Clipper: A low- latency online prediction serving system,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Clipper: A low- latency online prediction serving system,

Reference 5

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:2ac78870b9767705912cb78f3058b92c129c38b365700cf75cc7ce33c80ff9a2

Observation cc3dc184-01b5-4fc5-bf4a-e84f9e06e506 · outbound

This paper cites Model inversion attacks via prediction error reduction,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Model inversion attacks via prediction error reduction,

Reference 6

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:51dbdb67be016efb5b4f955820d29308369559d10d9872ae63144b9de39ab693

Observation bce403ce-fb80-46a1-bdf3-4e8824ad95ea · outbound

This paper cites Trusted deep neural execution—a survey,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Trusted deep neural execution—a survey,

Reference 7

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:e65e56853de8c520570f0cb729506867e69b594a66e32654649b314dce6b8ecc

Observation 25e7fdb1-216b-4f27-9bb6-80a0a8a8a162 · outbound

This paper cites Supply-chain attacks in machine learning pipelines: A survey of threats and mitigations,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Supply-chain attacks in machine learning pipelines: A survey of threats and mitigations,

Reference 8

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:0169b746bb9224f788c158e075fd9ae848abb1339d7ea7b3400233d36f5a7103

Observation 34abac19-05d4-4504-b727-60419da3e4b2 · outbound

This paper cites Weight poisoning attacks on pre- trained models,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Weight poisoning attacks on pre- trained models,

Reference 9

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:7a3c194070ec352dbb51d49ecf9604c677c16097b7af772fd0015441fb50c9f9

Observation 2c1ec01c-ded8-4d69-91cc-98bdb22417cf · outbound

This paper cites Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents

Reference 10

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arxiv_id, observed 2026-07-02T07:56:47.706814Z

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:90c460023609ebed5c52cc15828d6d6aa415a0e008258f5937904a9e1b3c908d

Observation 53cfab94-db6c-4c3e-88e6-e5cc80942c97 · outbound

This paper cites Pickle’s hidden perils: A systematic study of insecure model serialization,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Pickle’s hidden perils: A systematic study of insecure model serialization,

Reference 11

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:7deeacad5515fea4bd3cc1c9308227a3d60155eeae174b83fd9ecad02bb61484

Observation d693baa7-46ed-4d0e-92fc-ebead99a7a33 · outbound

This paper cites Morello: Security analysis of ml model registries and pipelines,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Morello: Security analysis of ml model registries and pipelines,

Reference 12

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:97b9165c4eea336a8bacb52859535de8024915834529d410c68c65c75e7de9f2

Observation eae3d96d-8c96-4012-a61d-092a8f6af3a9 · outbound

This paper cites IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency

Reference 13

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arxiv_id, observed 2026-07-02T07:56:47.702252Z

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:94093199e9defe0ae3f31186133b4bb770cdf1208404262d5ca8c62a9b62f3ec

Observation 3596b189-161f-4f9c-84b1-1a000d096577 · outbound

This paper cites Bit-flip attack: Crushing neural network with progressive bit search,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Bit-flip attack: Crushing neural network with progressive bit search,

Reference 14

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:f341f0e4077c5fbdc5260ceaccc877c832504b423321cdb85b1c915639e23c7f

Observation 0a7cf3bc-1b47-458d-a8cc-f14e09b46e9d · outbound

This paper cites Fault sneaking attack: A stealthy framework for misleading deep neural networks,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Fault sneaking attack: A stealthy framework for misleading deep neural networks,

Reference 15

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:0f1eff858e983eb893a4816179869974d343cb8f26e7f896b3458eb94fb1e2ec

Observation 87245735-47d0-4b73-af0c-0d5b8322ba25 · outbound

This paper cites Verification of bit-flip attacks against quantized neural networks,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Verification of bit-flip attacks against quantized neural networks,

Reference 16

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:4c424dab6ddcef4eed3da836e8b779974d744eeaf2a61dffab2e7d5e58e42ffc

Observation 75efa3ef-3d66-43dd-8aea-77e5715c7d50 · outbound

This paper cites Deep- hammer: Depleting the intelligence of deep neural networks through targeted chain of bit flips,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Deep- hammer: Depleting the intelligence of deep neural networks through targeted chain of bit flips,

Reference 17

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:8b8fbe8fe0abc22970182f2121aa1ce532cc5721a77650ab0d8dae5535a9922c

Observation 1eebeda7-4a5c-4ee9-b885-99b8626bc92c · outbound

This paper cites Flip it once: Bfa attacks with single weight perturbation,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Flip it once: Bfa attacks with single weight perturbation,

Reference 18

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:7e5b1bb2a85a2aab7a4fcb4e5fcc0c32b9feda706660b2c354a79070214a9655

Observation 6719f0f7-498e-4cfc-b9a4-448a061e0055 · outbound

This paper cites 3sat: A simple self-supervised adversarial training framework,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks 3sat: A simple self-supervised adversarial training framework,

Reference 19

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:6f190d8e9c62e6bcfe5496555851ddea97c0a99f7bf685caa2d035c0d0bd5c8b

Observation 97710faa-ae87-4cfa-946c-0abf0026db35 · outbound

This paper cites Towards security threats of deep learning systems: A survey,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Towards security threats of deep learning systems: A survey,

Reference 20

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Observation 0718d9e5-16e5-48cb-b275-0b1f85590958 · outbound

This paper cites Rise of inspectron: Automated black-box auditing of cross-platform electron apps,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Rise of inspectron: Automated black-box auditing of cross-platform electron apps,

Reference 21

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:36c25790f0903f864e01a01f600bdabff2e732f398d4b2a61e436b00b180fd2c

Observation 8b997596-96e4-44c8-ba0e-92d5029dc65c · outbound

This paper cites Defending against web application attacks: Approaches, challenges and implications,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Defending against web application attacks: Approaches, challenges and implications,

Reference 22

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:e6a2674248df796745a85ec39e36e866f85db8b5b107dcf6152177c8ca0c56af

Observation ccc61352-1f3e-4dfe-80f3-d8da56b965ae · outbound

This paper cites Bit-flip attack: Crushing neural network with progressive bit search,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Bit-flip attack: Crushing neural network with progressive bit search,

Reference 23

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:418bf7afeb8ec76650d24a645b95a64087118275df2b453608ff441eb755a350

Observation 3917478c-a2b9-4448-a644-e55ec6fb1429 · outbound

This paper cites Defending and harnessing the bit-flip based adversarial weight attack,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Defending and harnessing the bit-flip based adversarial weight attack,

Reference 24

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:f5641579d0daf3cf0d1d8c477a238f6e225f87be0b99513a35e4eae5945100bc

Observation 5e33af48-eb9d-427c-a658-211235dadbeb · outbound

This paper cites Aegis: Mitigating targeted bit-flip attacks against deep neural networks,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Aegis: Mitigating targeted bit-flip attacks against deep neural networks,

Reference 25

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:779472473fecd729ec3d8e47ea368e4e64c7e107a65c603e6d81a1c6e1bc8055

Observation 5a799168-4fa7-43d9-99d9-3abc68bcb5f4 · outbound

This paper cites Efficient encoding of quasi-cyclic low-density parity-check codes,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Efficient encoding of quasi-cyclic low-density parity-check codes,

Reference 26

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:22d7431ff13601818a86a9bba992e6442dccc5e3865a70905ce6549039b20d2f

Observation 17096136-1588-4b68-b561-1ed3b67b749b · outbound

This paper cites Learning multiple layers of features from tiny images,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Learning multiple layers of features from tiny images,

Reference 27

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:963674326d2d2e2e560b2057574949a5a2ea5bb2f2d4ded2a539b5cf88b3c20b

Observation 1d20faf9-1170-434c-a051-e26e7e290e88 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Imagenet: A large-scale hierarchical image database,

Reference 28

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:74021e3de3aeec10e830d4c415298392493d7055462ed5b1b589234bd9e9fb13

Observation 1b624299-9699-44c4-bdee-f9387cba7829 · outbound

This paper cites (2026) https://github.com/beanduan22/pardef.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks (2026) https://github.com/beanduan22/pardef

Reference 29

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:672353f5c3e721d559345e17b604c601599949d2b22c21fae87c238d9434dc25

Observation e549feb4-94ce-4864-9bcb-f815b4dbb341 · outbound

This paper cites Malicious ai models undermine software supply-chain security,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Malicious ai models undermine software supply-chain security,

Reference 30

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:3c2fbde034d081fa5ebcde2585ee2c0b90ff5d7c7521b7c1776651d4f09ba8f3

Observation d12e7956-4721-42fc-a440-b6652ea00661 · outbound

This paper cites Threat modeling ai/ml with the attack tree,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Threat modeling ai/ml with the attack tree,

Reference 31

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:1ca7a68ead15c8693c8e28425262bb208f5bae13219a16b5d99247b947567e0a

Observation de01a606-7334-425f-81bc-cdc692f881c1 · outbound

This paper cites A com- prehensive survey on non-invasive fault injection attacks,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks A com- prehensive survey on non-invasive fault injection attacks,

Reference 32

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:4b82f142f858111ddc4a02bb451152ed7a64ef81a387760644680954f80ee9fb

Observation 1ab0c1cd-b9c8-4ac7-bef0-d6294cc1adcc · outbound

This paper cites Proflip: Targeted bit-flip attack with probabilistic search,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Proflip: Targeted bit-flip attack with probabilistic search,

Reference 33

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:4a6514a6ef14a497544f13a46826ce1cbfa2e686b7c311893ead275dceb059cc

Observation 5eee07bf-5872-4704-903d-6c06b3525a88 · outbound

This paper cites Fault injection attack on deep neural network,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Fault injection attack on deep neural network,

Reference 34

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:e786e287bcae148095ac40e111dab35d6994f9f93a1cba654fac8704e49fa8b4

Observation 5331468c-aca7-4d40-9928-84d3885fd5dd · outbound

This paper cites Terminal: Terminating bit-flip attack via end-to-end bit corruption detection,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Terminal: Terminating bit-flip attack via end-to-end bit corruption detection,

Reference 35

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:d0af17bfe2367e2c6ada386f90205683a922950b203bc8b1300102b192b3bf4a

Observation 8804b3b3-ec01-40b0-b652-e21c64f1a698 · outbound

This paper cites Bitshield: Defending against bit-flip attacks on dnn executables,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Bitshield: Defending against bit-flip attacks on dnn executables,

Reference 36

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:96c6d85d8b3486de6baa8287875502b76087ec6f59ad520d83d9c9eb2e8e960f

Observation a83e2c87-32d1-48ae-a4af-ce78fd3341e0 · outbound

This paper cites Slalom: Fast, verifiable and private execution of neural networks in trusted hardware,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Slalom: Fast, verifiable and private execution of neural networks in trusted hardware,

Reference 37

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:6420b681fad5792d04a7f384ffa02beb66502b1ca1fa83887c53d904212c0cc2

Observation f5f20cb1-aacd-47eb-877b-3121137b60d8 · outbound

This paper cites DarkneTZ: Towards model privacy at the edge using trusted execution environments,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks DarkneTZ: Towards model privacy at the edge using trusted execution environments,

Reference 38

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:83d23f8ea7115ca23edd4805db8a12a80d792b6a6cd70111374ce667a33c2aec

Observation 91a2770f-9da1-4ed0-82f6-9c2d9aac3139 · outbound

This paper cites Intel® software guard extensions (intel® sgx) support for dynamic memory management inside an enclave,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Intel® software guard extensions (intel® sgx) support for dynamic memory management inside an enclave,

Reference 39

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:22c3f0c152d045016376d1e226e64afb3f07fa0889a6151b8be574174c90a943

Observation c4722795-d981-4a7a-94f7-cdb005f78536 · outbound

This paper cites Sok: Understanding the prevailing security vulnerabilities in trustzone-assisted tee systems,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Sok: Understanding the prevailing security vulnerabilities in trustzone-assisted tee systems,

Reference 40

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:2d86f8266ec4b34fbb69aed4a70381dd8037df1e956078538ff5b967bc0083db

Observation 3b6e376a-9b29-48f7-91bf-114d9ab93fb1 · outbound

This paper cites Privacy risk in machine learning: Analyzing the connection to overfitting,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Privacy risk in machine learning: Analyzing the connection to overfitting,

Reference 41

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:dc1cbf4c9c5d784d4e68684435fe42b8e96e5ea70c60e4573281599920535f42

Observation 2a104c1d-0994-4111-a97e-c6c3adbd691b · outbound

This paper cites Toward confidential cloud computing,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Toward confidential cloud computing,

Reference 42

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:ba75fd22a5f6b9cb397b4b14ce7a1ef45d97fe053b0879e74e0fd3476fd96240

Observation a246183e-7b65-4357-97e9-37c44bb8098f · outbound

This paper cites A Tight Max-Flow Min-Cut Duality Theorem for Non-Linear Multicommodity Flows.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks A Tight Max-Flow Min-Cut Duality Theorem for Non-Linear Multicommodity Flows

Reference 43

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verified exact
arxiv_id, observed 2026-07-02T07:56:47.703807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:7bea4a5ec28f23776e4df5f967a1c12fc3da4df2c3269de765dd5dc74c3debbf

Observation 317e13bd-0ba2-4a88-837a-b06a6f1b0e73 · outbound

This paper cites Polynomial time cryptanalytic extraction of neural network models,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Polynomial time cryptanalytic extraction of neural network models,

Reference 44

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:5145f3fc13be0f60267fd75f6ad30442eaca45682e32534fd11b09524e0d6ba9

Observation 56f8524c-9544-4cd9-a178-fbf76d5f2c18 · outbound

This paper cites A review on machine learning for channel coding,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks A review on machine learning for channel coding,

Reference 45

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:8dcadf28b15e2a3dfb75fb7f338d91183fc1be628ba45554fca0a80728073590

Observation 0dd19573-0e51-4632-a73d-cdabc7182270 · outbound

This paper cites Memory system optimization for fpga-based implementation of quasi-cyclic ldpc codes decoders,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Memory system optimization for fpga-based implementation of quasi-cyclic ldpc codes decoders,

Reference 46

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:365866a551cd8aee6c6f68568dffab244dfbe3cb210ef7ec9f6e52bf73429a37

Observation 2d624c86-4e93-4efa-bc3b-8d3fb4c5c3a4 · outbound

This paper cites Training data-efficient image transformers & distillation through attention,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Training data-efficient image transformers & distillation through attention,

Reference 47

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:7ca10a75b15f8a63cee75f0320153353962d7f3fd37c75451f33b05b76df4fd4

Observation 2b8a7139-6d15-4191-9960-308a5529f427 · outbound

This paper cites Advanced Encryption Standard (AES) Key Wrap Algorithm,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Advanced Encryption Standard (AES) Key Wrap Algorithm,

Reference 48

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:33a76854b6014c2bd6739c5529280fd5a58c831e00ef08a88570e470da18a603

Observation 634a41d9-baf4-40ae-8d01-f6a3a158f202 · outbound

This paper cites A secure and reliable bootstrap architecture,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks A secure and reliable bootstrap architecture,

Reference 49

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:727e1e21e55f1a46e85683176fb3b3b6a5e2f03b4be494d184ac257a2d994ab7

Observation fa9261e9-f65b-4a16-a98b-0ed8221d6347 · outbound

This paper cites An Exploratory Study of Attestation Mechanisms for Trusted Execution Environments.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks An Exploratory Study of Attestation Mechanisms for Trusted Execution Environments

Reference 50

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verified exact
arxiv_id, observed 2026-07-02T07:56:47.699814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:461cdc083cd9d9acc733582e7c3847e62f0967432767f3a9b3e25ec6f110434b

Observation fa60c19e-6617-471a-9ef1-4f7da3c08bc5 · outbound

This paper cites Intel trust domain extensions (TDX) architec- ture specification,.

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks Intel trust domain extensions (TDX) architec- ture specification,

Reference 51

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T06:29:34.540587Z digest=sha256:7c994e5b17d7b4f622e34dc635baf4c1d55b8f0a60410936dcc2a35b0d1d5f1b

Pith citing papers

No inbound Pith citation observations are available.