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Paper Citation Record · LEDGER

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery

As of 10 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2506.04556.

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

pith.paper-citation-record.v1
2506.04556 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:44:40.250400Z

measured 45 of 45 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 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

45 of 45 outbound references displayed

  • verified exact5
  • verified fuzzy36
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 25100a51-66b9-4b48-b7e2-4fec3d2f6fff · outbound

This paper cites Efficient self-supervised learning with contextualized target representations for vision, speech and language,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Efficient self-supervised learning with contextualized target representations for vision, speech and language,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.905537Z

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=2026-08-07T10:44:39.191629Z digest=sha256:81edf60a00b4daf937981c930d4b9a79eac7b2e2afaec58119499af01364c5ef

Observation f97fde2f-c62c-4097-af6c-89b07d60b78d · outbound

This paper cites Reaas: Enabling adversarially robust downstream classifiers via robust encoder as a service,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Reaas: Enabling adversarially robust downstream classifiers via robust encoder as a service,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.892746Z

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=2026-08-07T10:44:39.271897Z digest=sha256:439c0bc8eeda3c91ddb1a8e08e886321c2143ab0898a2c9741bcc2485a2778fb

Observation 462d6e05-03b5-42fc-b673-e93bf2ad8838 · outbound

This paper cites Can’t steal? cont- steal! contrastive stealing attacks against image encoders,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Can’t steal? cont- steal! contrastive stealing attacks against image encoders,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.879691Z

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=2026-08-07T10:44:39.275499Z digest=sha256:072a866b6417721cbf2fed9b7e6643ab99472571d9ad9c20e48e78709a57f596

Observation 0d1ce80d-5b78-4ecb-9f69-c7dd58346f03 · outbound

This paper cites AWEncoder: Adversarial Watermarking Pre-trained Encoders in Contrastive Learning.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery AWEncoder: Adversarial Watermarking Pre-trained Encoders in Contrastive Learning

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:44:40.411203Z

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=2026-08-07T10:44:39.279936Z digest=sha256:42d4f1552277d1b291f7591b5d7f100a4c01067ffe04ce2cb24735ebb0c36035

Observation eaeffeaf-138c-461e-a72e-b1600f0533c8 · outbound

This paper cites 10 Security and Privacy Problems in Large Foundation Models.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery 10 Security and Privacy Problems in Large Foundation Models

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:44:40.392059Z

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=2026-08-07T10:44:39.405645Z digest=sha256:543c57868e1a618aa603893cf99232460e2e068a1ddf85299f9b9d97ce113562

Observation 3fb902fe-7253-4ed3-a7d7-c37e3540bf34 · outbound

This paper cites On the difficulty of defending self-supervised learning against model extraction,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery On the difficulty of defending self-supervised learning against model extraction,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.867200Z

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=2026-08-07T10:44:39.499997Z digest=sha256:b7e727c6d1e7c2e89cc3e32d41f1dd11bc2f2291b4eeadae18e587c0e87141ac

Observation 0be1f689-d3b0-457b-9e9e-c4e6ddc79874 · outbound

This paper cites Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.841539Z

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=2026-08-07T10:44:39.627456Z digest=sha256:ba26aa798ff8f5b987936620428a18af559bad61863ac414e0bfea807e2b9e1a

Observation 7c68f1ab-f8f8-4a91-9806-8cecb448b2f7 · outbound

This paper cites Encodermi: Membership inference against pre-trained encoders in contrastive learning,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Encodermi: Membership inference against pre-trained encoders in contrastive learning,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.827495Z

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=2026-08-07T10:44:39.634529Z digest=sha256:14d2f45750a238bc0056deded2178d367b47284434d962aaa655bda5d9b8d652

Observation 90e8f8cd-8899-4cad-81c7-190cad8b5033 · outbound

This paper cites Semi-leak: Membership inference attacks against semi-supervised learning,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Semi-leak: Membership inference attacks against semi-supervised learning,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.813801Z

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=2026-08-07T10:44:39.638965Z digest=sha256:a31114cdac45f3067071470eb2a8cf73374e08007920536f2724e9a2a627ba84

Observation 473f2a09-63d0-49ca-b6c8-4b91c1d4ed6b · outbound

This paper cites Badencoder: Backdoor attacks to pre- trained encoders in self-supervised learning,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Badencoder: Backdoor attacks to pre- trained encoders in self-supervised learning,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.799812Z

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=2026-08-07T10:44:39.694412Z digest=sha256:63e92960f9b72493617801d7fe209546268402ccf86c2a3dcd3592f44a400289

Observation 8b7e4dfa-b66c-4594-afca-3d0ae65969f2 · outbound

This paper cites Backdoor attacks on self-supervised learning,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Backdoor attacks on self-supervised learning,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.787281Z

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=2026-08-07T10:44:39.774646Z digest=sha256:747d5a17802e60fb31198d8ad2aa191f78455be9683a4860ff120306ff5c61e9

Observation 0ebc5ab2-4f13-404e-b51e-7ef85bf686e2 · outbound

This paper cites An embarrassingly simple backdoor attack on self-supervised learning,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery An embarrassingly simple backdoor attack on self-supervised learning,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.774694Z

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=2026-08-07T10:44:39.834205Z digest=sha256:07365490448a2fcac68dbb187f5625211796e7cd597f12f0c2d10327f7b95514

Observation 9e76930d-5102-4c76-956f-ced949968441 · outbound

This paper cites PRADA: protecting against DNN model stealing attacks,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery PRADA: protecting against DNN model stealing attacks,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.760904Z

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=2026-08-07T10:44:39.899883Z digest=sha256:c83429547d1cc5dee42b9799f0947552b732a0dd9960522002fee536a0055324

Observation 7d3fb1c8-d773-43c3-b3ed-6d4d5ab04635 · outbound

This paper cites Modelguard: Information-theoretic defense against model extraction attacks,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Modelguard: Information-theoretic defense against model extraction attacks,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.747911Z

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=2026-08-07T10:44:39.974999Z digest=sha256:aee6a6bb55681446bd549772462cf41ac5ec09979edaa65ed67172124413641d

Observation 2ab41232-eaba-4239-9cc6-391572a825d9 · outbound

This paper cites Plmmark: A secure and robust black-box watermarking framework for pre-trained language models,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Plmmark: A secure and robust black-box watermarking framework for pre-trained language models,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.735272Z

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=2026-08-07T10:44:40.028591Z digest=sha256:7f94baca81e1e22edd2c2add27224c3795a5fba167b0bee3e8c28ae55a21960a

Observation 12dbe15b-2fb2-4056-94d3-2fafc4299c61 · outbound

This paper cites SSL-Auth: An Authentication Framework by Fragile Watermarking for Pre-trained Encoders in Self-supervised Learning.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery SSL-Auth: An Authentication Framework by Fragile Watermarking for Pre-trained Encoders in Self-supervised Learning

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:44:40.373313Z

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=2026-08-07T10:44:40.111089Z digest=sha256:dd8d4dae24cc742a182f58b0c9d449eadd946aacfaf7c5b9e64402ba57062032

Observation b50303af-2aca-4c51-bcda-5d14597ad6d8 · outbound

This paper cites Watermarking Vision-Language Pre-trained Models for Multi-modal Embedding as a Service.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Watermarking Vision-Language Pre-trained Models for Multi-modal Embedding as a Service

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:40.127433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:40.127433Z digest=sha256:624fc460927916cd30cdd8aaf0d0c9442d7a9d46b25263ae6852bf52a84ddc8c

Observation 94b4034d-15f9-441a-82cb-b6d21c1e9513 · outbound

This paper cites Threat modeling ai/ml systems and dependencies,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Threat modeling ai/ml systems and dependencies,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.721028Z

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=2026-08-07T10:44:40.133264Z digest=sha256:174525b26d3a15db760ae300790c6ae2d96a2810ecf00a5009f2ea8170a79086

Observation 471b45a2-f491-4ada-a726-73de39438a94 · outbound

This paper cites Stolenencoder: Stealing pre- trained encoders in self-supervised learning,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Stolenencoder: Stealing pre- trained encoders in self-supervised learning,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.707365Z

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=2026-08-07T10:44:40.137481Z digest=sha256:4816c6748a5229459a42ccae1877d613520b03ee6331c151245bb34892fd8e15

Observation 6360808a-6018-4006-a21c-99387ebe30be · outbound

This paper cites D-DAE: defense- penetrating model extraction attacks,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery D-DAE: defense- penetrating model extraction attacks,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.694383Z

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=2026-08-07T10:44:40.141333Z digest=sha256:8e726965f7564696d0588eaf9e6e245844c571f135d7c12a4f20ab93284023a9

Observation 7a9633b8-5d36-4d2b-8440-b3ad99c7b51e · outbound

This paper cites Magnet: A two-pronged defense against adversarial examples,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Magnet: A two-pronged defense against adversarial examples,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.681735Z

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=2026-08-07T10:44:40.145843Z digest=sha256:04fac658c2adab51d3a8fc841a095ca9cb0eb9eb8f582120c83bd63a0c5478ae

Observation bf1893f4-048f-426d-b9b8-0ce94647753a · outbound

This paper cites Model extraction attacks and defenses on cloud-based machine learning models,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Model extraction attacks and defenses on cloud-based machine learning models,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.669143Z

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=2026-08-07T10:44:40.150321Z digest=sha256:3c79a1d025035f1f6ce1655012a4c28d1dc10a61b77f24a65f383787728e8f61

Observation 8bcd002c-4632-4d0c-8e6b-cfb4a9d93f31 · outbound

This paper cites Inversenet: Augmenting model extraction attacks with training data inversion,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Inversenet: Augmenting model extraction attacks with training data inversion,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.656590Z

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=2026-08-07T10:44:40.154830Z digest=sha256:e491a8cc0c31da8721afe9e8602b8f4c9ccefe219241c9f27bd741c6d8d51d28

Observation ef7d6b50-b01f-48fd-af60-d9fe7c274184 · outbound

This paper cites Stealing machine learning models via prediction apis,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Stealing machine learning models via prediction apis,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.643846Z

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=2026-08-07T10:44:40.159306Z digest=sha256:7d6d4dcefe5feb6cb286e1c79e3485db09859e897b2476417f15fe51adfbd43a

Observation 5325badb-2bcb-40a4-85b2-d9c20f1daed1 · outbound

This paper cites Black-box attacks on sequential recommenders via data-free model extraction,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Black-box attacks on sequential recommenders via data-free model extraction,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.630471Z

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=2026-08-07T10:44:40.163322Z digest=sha256:6a168c15e75644db9fde7f83683c5c60aed46458a49de1d628961e465c67f3cb

Observation e70c0880-a877-4b19-85b5-95c222df059e · outbound

This paper cites Divtheft: An ensemble model stealing attack by divide-and-conquer,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Divtheft: An ensemble model stealing attack by divide-and-conquer,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.617105Z

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=2026-08-07T10:44:40.167952Z digest=sha256:8af7151c8a3af43995885737acffa2b2d9765a3bef0ac1c259600f47de6cdd09

Observation 503d7391-ae9a-4587-80bb-a36f8682390d · outbound

This paper cites Data-Free Model Extraction Attacks in the Context of Object Detection.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Data-Free Model Extraction Attacks in the Context of Object Detection

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:44:40.339775Z

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=2026-08-07T10:44:40.172344Z digest=sha256:43e7b94cae1fdf6763f7f496462a55501d2aefaeef02bb699377f4c512e17145

Observation 9606e46e-7216-4d6d-9adf-c544653fdb50 · outbound

This paper cites MAZE: data-free model stealing attack using zeroth-order gradient estimation,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery MAZE: data-free model stealing attack using zeroth-order gradient estimation,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.602888Z

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=2026-08-07T10:44:40.176624Z digest=sha256:7555e05f68da774e2780a52d6b0666d9ef2b60069fdbeeb2d26d16acf9aeb3d3

Observation 88db8f25-a96b-43d5-8cb5-aafc6052c0cc · outbound

This paper cites Data-free model extraction,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Data-free model extraction,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.589527Z

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=2026-08-07T10:44:40.180343Z digest=sha256:00420ff29d3ba6f2c58d4338f7579bfd190b88e9636973c11c5102c9c560aeb1

Observation 9871662b-44ed-42bd-9136-2c65fc569b84 · outbound

This paper cites Entangled watermarks as a defense against model extraction,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Entangled watermarks as a defense against model extraction,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.575613Z

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=2026-08-07T10:44:40.184340Z digest=sha256:01719153fbc05b81086815319396c0ca099505a2dc042388e44f20b8b44da4b0

Observation 5503ccc1-de81-491f-bdfe-d3f1d2d07408 · outbound

This paper cites Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Models.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:40.188346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:40.188346Z digest=sha256:5b2c9f012e7d27b746b305207bc970cce1c9665dd86fbcd91ed903638470ddb7

Observation ca3535f7-2d6c-4be6-be0a-3248c1d85630 · outbound

This paper cites Fe-dast: Fast and effective data-free substitute training for black-box adversarial attacks,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Fe-dast: Fast and effective data-free substitute training for black-box adversarial attacks,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.562280Z

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=2026-08-07T10:44:40.192686Z digest=sha256:befbd074af067ba57a5498310a9de03412285b7928965c22cc1df68400fed036

Observation 904e3f69-5826-4f43-b5b5-7644cdcaee13 · outbound

This paper cites QUDA: query-limited data-free model extraction,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery QUDA: query-limited data-free model extraction,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.546732Z

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=2026-08-07T10:44:40.197531Z digest=sha256:dbecf7c62b277ea96cea0be0c5732ca5bac7761397a63611d1b477b4d3582c38

Observation 6021d8ab-09c2-47ff-ba67-77efd9957f7e · outbound

This paper cites Knockoff nets: Stealing func- tionality of black-box models,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Knockoff nets: Stealing func- tionality of black-box models,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.534463Z

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=2026-08-07T10:44:40.202460Z digest=sha256:7b27322a4a08f90ffa9c2424a8e043b20f216d981f48636452eebd6107ff17e6

Observation 7a3d500a-dd37-46d9-af58-74e13cbb743a · outbound

This paper cites Practical black-box attacks against machine learning,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Practical black-box attacks against machine learning,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.520561Z

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=2026-08-07T10:44:40.207004Z digest=sha256:cdd6e37b1e1505cd10d368a8b06f7dfc59ba850a61d6dd696293a1d418c84693

Observation 1b5fc14d-e842-474e-a0e4-a7b4c7685f28 · outbound

This paper cites DST: dynamic substitute training for data-free black-box attack,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery DST: dynamic substitute training for data-free black-box attack,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.854014Z

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=2026-08-07T10:44:40.211056Z digest=sha256:4d690f8c8e9e7ea9f718fa011dc191e32f86f90b99a9742908f51f55c0e2b094

Observation afded011-ba85-4769-bd15-6edc62414950 · outbound

This paper cites Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:44:40.305995Z

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=2026-08-07T10:44:40.215276Z digest=sha256:3efaf1a66ab3b4213996b4dfabc0fa20646b510899014248e0b4637d9ea68067

Observation 2067a111-30ce-47ed-9a6a-3a127c0f112d · outbound

This paper cites Sslguard: A watermarking scheme for self-supervised learning pre-trained encoders,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Sslguard: A watermarking scheme for self-supervised learning pre-trained encoders,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.506898Z

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=2026-08-07T10:44:40.220741Z digest=sha256:e02d80616480bedd248627bb50a4f57323a19769689845b97e15d371995c92d6

Observation d39e61ed-ff2f-45ac-a010-2545811f8cab · outbound

This paper cites Are you copying my model? protecting the copyright of large language models for eaas via backdoor watermark,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Are you copying my model? protecting the copyright of large language models for eaas via backdoor watermark,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.492840Z

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=2026-08-07T10:44:40.225203Z digest=sha256:6cac0541f2cb564e65c4943f83794022ba8b2bb69d1b949cdfb694456ef6a7cf

Observation 07ef47bd-57c7-4299-9bd5-563c5e8b3902 · outbound

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

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Learning multiple layers of features from tiny images

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:40.229281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:40.229281Z digest=sha256:de1c85cf18d1a438cdbeb7f06aacc438cdc94b5ff096488fcabfd61bda1b44bf

Observation 7811dbd1-7b69-4de1-bdd9-ff9e35c4ac76 · outbound

This paper cites Reading digits in natural images with unsupervised feature learning,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Reading digits in natural images with unsupervised feature learning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.470364Z

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=2026-08-07T10:44:40.233217Z digest=sha256:18bac60c526f547c17e0a6bbf5f525ced2da0c48325197b3f1930ab380d99e03

Observation 8e446698-81aa-4f40-bd60-53065f104730 · outbound

This paper cites Auto-encoding variational bayes,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Auto-encoding variational bayes,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.455139Z

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=2026-08-07T10:44:40.237561Z digest=sha256:1980d3c904843e1cb82385e8ba5550b658087aec43a33df8d3c7c64a6b3e0f90

Observation f2bc344f-709b-445a-ad7b-dc58065ea460 · outbound

This paper cites Generative adversarial nets,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Generative adversarial nets,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.440446Z

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=2026-08-07T10:44:40.242357Z digest=sha256:dc2b09d853eecd19d7ff18a7bc95685919f9d81815724d1d1c175cd4fded4cdc

Observation 456b8959-77c2-4bbe-b80d-c21ebfd3a579 · outbound

This paper cites Rectifier nonlinearities improve neural network acoustic models,.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery Rectifier nonlinearities improve neural network acoustic models,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:40.426108Z

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=2026-08-07T10:44:40.246326Z digest=sha256:3a75c41c4c395b9baaf23c7cf132e625ff998df4a9aeb37e0933966c35633be5

Observation c43b6982-a793-4316-a584-b5e715dd4ef7 · outbound

This paper cites A Survey of Machine Unlearning.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery A Survey of Machine Unlearning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:40.250400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:40.250400Z digest=sha256:202831c690322a1af15fe21ae20566e3ac81e3cb13a63c26a37b68ab21827522

Pith citing papers

No inbound Pith citation observations are available.