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Paper Citation Record · LEDGER

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery

As of 9 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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.191629Z digest=sha256:30a81999260a98b1fb63e1558d687953278914d90d5da09400f6dfe9fc863da8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.271897Z digest=sha256:0044359063325fb36497eab764f8aaa80f6cf6eb002e17576592e41bd9ae8687

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.275499Z digest=sha256:e0a921e3e9a61eb22f42c10e4dd98f0bf14d14f4fc310f91cffbc7804a87ba6c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.279936Z digest=sha256:ed61b77dd60e5a7b0d44197c466eb30e7b68b3da3f609539938a1661d0a2159b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.405645Z digest=sha256:e7ec64cec33280342aee9f56cd4d5bb2e610486eb1ed12d93fd7adc00ca4b45b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.499997Z digest=sha256:4ad64e13fd99addfd69963b30bc06b6fd19b14f643d2d38c47c83b64cafbe268

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.627456Z digest=sha256:340406665cf655bf5529fbbe12e3ee79dd81cd79f0a66cc7209cd07321c7df04

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.634529Z digest=sha256:44d7c48aaa29b90d7459e2f740427a1b4a2fb23a1dfe6f82035023834a992b72

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.638965Z digest=sha256:fdd713d3d242795f9e80bde443616b48e0a6ffac00d9144404861cfc8d480321

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.694412Z digest=sha256:38ea7aad4f2d7dbac1714baa5a4c4fe5312986e1ab95ca0bc0a0e2fb8f690682

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.774646Z digest=sha256:efdb5ff5ae4cbb0bae7ebdeb117de2445424b638e11ea08634345020e6ab200a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.834205Z digest=sha256:aff8ff299e2fdf4779abd703a823b4380610524167708055f5bde29f680ac4a8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.899883Z digest=sha256:e003c12b00bf1884e625642b4a8d717162d2d70f1b6b6ca9ccb46525de49c412

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:39.974999Z digest=sha256:981c910c977588b19783ed84837ac9103173cf0dadd956e86086fe49bdf0985f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.028591Z digest=sha256:22cc7024410b8fcc7a6263548b6d826bd88fd3ab75f9cf384e15287aebb5c9f8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.111089Z digest=sha256:39428e2804066ea19ef3f21586ee4f8488331b0b95aa927dfde792aa0bd4fd5c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.133264Z digest=sha256:1d32aa74634da864ac48c31b654778de1f96196973c604a56bf1b17110fed8de

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.137481Z digest=sha256:4f1dbdb27fc9bc27d2903ccb0ee98a5a19f045c654d5ccfa179fce5aa8a4e4ba

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.141333Z digest=sha256:8030b00b158d38e9c7e808eaf3caa50d3b0e0564a118f191ed474ab65525c738

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.145843Z digest=sha256:a95557ae694c6611960acba89b5fe61d707e2ca01e723a4eae79574dfed835a8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.150321Z digest=sha256:ae0958feb0e8d7336509fc1fb7957930449475c998d2a3e3a05e0420d371cd81

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.154830Z digest=sha256:24eb9047467271f637444e969e3531fb851c32f99816fab4a27d23ca0a3f31f4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.159306Z digest=sha256:e5a7a12aa5cabf4531194bf954dcefb678f49649a3309a14443072c180063488

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.163322Z digest=sha256:f22f77101b72f5a5c8b40ed857fb7deb81fb7aa48b6e61275915b44285b9c1ff

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.167952Z digest=sha256:32e234cf99b6147cf6f0d8428b2204e1f0aefaf76443bd2ad4d58784ab426878

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.172344Z digest=sha256:8b3a8033a6d0cf2b38f3f3893f7f50d2058b9e45b676c00b75a8aace05684cb1

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.176624Z digest=sha256:303188e0c43bc60b40e7bcfbdcc72a19c10188772effaa26c9eb8ca3e04bde7a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.180343Z digest=sha256:025a431cff61b15c08ff6e40f8f510961e5e7d9a55ae3612b598f157794f3ed4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.184340Z digest=sha256:869a533bcda688bf95c44fe70a4418c06e82e8a2a615de293b9a2dfbc6f6843c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.192686Z digest=sha256:269dcb5e5ede0aafaa9b340dfbe856be26aa896568f41b42958c6277ed968a41

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.197531Z digest=sha256:279245e126b19d7462f36596e3c9c86c99f40f03eda1bb8943f145dda63f07f7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.202460Z digest=sha256:a5162f99e4523db2bf351d1e25ae65239f61fe816f0dea2d103ca68c74586c1f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.207004Z digest=sha256:41f4844d2eae2c54b7c509732d97d60b3ab62947d31bb2cae642eca0a5c17c0e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.211056Z digest=sha256:3882c7c0995827e0dbcde0d52374188fcf27e6707af17eff8419f8d3adfc62a4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.215276Z digest=sha256:dd6765f9516217c0f8d249d39abeebf1ec56e8462adcda2bb4968b1620d71338

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.220741Z digest=sha256:1f8f087ea4a0aafdddcf7d497792ab66de4885faae4fcdbd2f590cbf94e4c1c0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.225203Z digest=sha256:7f59d9485b8e9637b1dae126a96a5c7aa4b73f559ae5e88a8a32834bb4e01c17

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.233217Z digest=sha256:abf2156a907e695b1fff33b0f31800d8b06b01893ed585dad06d243d00ebc34e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.237561Z digest=sha256:06ab36f31328a20bb2c984a249d9539e0df6cd5547bded1a8779e46a73106225

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.242357Z digest=sha256:59c5e7e4514fbd3d382c54b749578a2557c02a740e6248ed190c5205dd5997d0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:44:40.246326Z digest=sha256:3d65ec33db1ecccf31e105b22e50d3415345d1e6eaebb38b1385db9e07c082d2

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.