Paper Citation Record · LEDGER

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack

As of 22 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2411.12071.

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

pith.paper-citation-record.v1
2411.12071 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:00:27.410355Z

measured 42 of 42 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

42 of 42 outbound references displayed

verified exact1
verified fuzzy32
unresolved9
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 62d75834-ed94-47db-8218-740bb40bd4f6 · outbound

This paper cites IEEE transactions on Computers , 100(1):90–93, 1974.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack IEEE transactions on Computers , 100(1):90–93, 1974

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.733160Z

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.

Observation e18853f7-3297-452c-b28a-ad45ae9a90fa · outbound

This paper cites Square attack: a query-eﬃcient black-box adversaria l attack via random 16 search.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Square attack: a query-eﬃcient black-box adversaria l attack via random 16 search

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.702770Z

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.

Observation f414bfc9-bbdf-44ac-9cdb-a4bce13d7d6a · outbound

This paper cites Obfu scated gradients give a false sense of security: Circumventing defenses to advers arial examples.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Obfu scated gradients give a false sense of security: Circumventing defenses to advers arial examples

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.661731Z

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.

Observation 9fa1e37d-e554-4db8-b2ad-026b1e190a0b · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack BEiT: BERT Pre-Training of Image Transformers

Reference 4

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Source-reported events for the cited work

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Observation e66bed57-6be2-4a7e-be77-9e5a06921c9e · outbound

This paper cites Dec ision-based adver- sarial attacks: Reliable attacks against black-box machin e learning models.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Dec ision-based adver- sarial attacks: Reliable attacks against black-box machin e learning models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.634497Z

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.

Observation 7b065a2d-4ea7-4876-a62b-0e9aa82b0047 · outbound

This paper cites Towards evaluating t he robustness of neural networks.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Towards evaluating t he robustness of neural networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.611576Z

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.

Observation c285f546-123c-4c6c-b341-27f19373a170 · outbound

This paper cites H opskipjumpattack: A query-eﬃcient decision-based attack.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack H opskipjumpattack: A query-eﬃcient decision-based attack

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.585373Z

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.

Observation 4b48bbcc-66e0-4d36-85a6-80f4f37dc33e · outbound

This paper cites Zoo: Zeroth order optimization based black-box attacks to deep n eural networks with- out training substitute models.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Zoo: Zeroth order optimization based black-box attacks to deep n eural networks with- out training substitute models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.560439Z

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.

Observation 7959e538-c28f-421a-b260-efe097ed2d37 · outbound

This paper cites Query-eﬃcient hard-label black-box attack: An o ptimization-based approach.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Query-eﬃcient hard-label black-box attack: An o ptimization-based approach

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.528526Z

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.

Observation faea15d1-99e4-4ebf-9609-b6f522c0a3d5 · outbound

This paper cites Sign-OPT: A Query-Efficient Hard-label Adversarial Attack.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Sign-OPT: A Query-Efficient Hard-label Adversarial Attack

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T18:00:27.197288Z

Source-reported events for the cited work

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Observation 035d3f78-e346-45bd-a31c-9845b43e731f · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Explaining and Harnessing Adversarial Examples

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T18:00:27.202536Z

Source-reported events for the cited work

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Observation c6656ab9-66cc-4034-8efd-b834af796782 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T18:00:27.209507Z

Source-reported events for the cited work

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Observation 9be425fb-3a56-4ee5-ba93-6dbe3d4ec34b · outbound

This paper cites D eep residual learning for image recognition.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack D eep residual learning for image recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.493504Z

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.

Observation 2ca2b907-4c3d-445d-8a85-be5937249dd9 · outbound

This paper cites Densely connected convolutional networks.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Densely connected convolutional networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.469205Z

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.

Observation 2bc13463-2db3-4071-8653-9f466d7d8c77 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T18:00:27.228337Z

Source-reported events for the cited work

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Observation bafc02b5-d6b6-4ff7-a5c8-f9c366a7ecf0 · outbound

This paper cites Reinforcement learning: A survey.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Reinforcement learning: A survey

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.445906Z

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.

Observation 24f04f29-55c2-4b8e-a2f6-6fda62aa88b5 · outbound

This paper cites Robust d ecision-based black-box adversarial attack via coarse-to-ﬁne random sea rch.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Robust d ecision-based black-box adversarial attack via coarse-to-ﬁne random sea rch

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.420673Z

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.

Observation 89fa69b4-5c73-43d1-8725-e052e75ee754 · outbound

This paper cites Big transfer (bit): Genera l visual representation learning.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Big transfer (bit): Genera l visual representation learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.393869Z

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.

Observation 9b1557c3-8d15-4019-8ad0-6d10e519290d · outbound

This paper cites Adve rsarial examples in the physical world.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Adve rsarial examples in the physical world

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.369544Z

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.

Observation d398ed80-934f-465a-8167-9ccb7d3f4218 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T18:00:27.264845Z

Source-reported events for the cited work

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Observation a618ed5c-71ee-4a4b-8bc4-167d2da737e3 · outbound

This paper cites Qeba: Query- eﬃcient boundary-based blackbox attack.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Qeba: Query- eﬃcient boundary-based blackbox attack

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.321435Z

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.

Observation e604c534-3a77-4f20-8921-69bbc5083b08 · outbound

This paper cites ML Attack Models: Adversarial Attacks and Data Poisoning Attacks.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack ML Attack Models: Adversarial Attacks and Data Poisoning Attacks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T18:00:27.280507Z

Source-reported events for the cited work

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Observation 8f283728-b53f-4eda-bed9-c0880b92436d · outbound

This paper cites A geometry- inspired decision-based attack.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack A geometry- inspired decision-based attack

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.281203Z

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.

Observation 32023d30-4d03-4139-96b7-90dbc17c2493 · outbound

This paper cites Back in black: A comparative evaluation of recent state-of-the- art black-box attacks.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Back in black: A comparative evaluation of recent state-of-the- art black-box attacks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.250978Z

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.

Observation d8544d71-2a62-41d6-abd8-d4781704e92b · outbound

This paper cites On t he robustness of vision transformers to adversarial examples.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack On t he robustness of vision transformers to adversarial examples

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.222263Z

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.

Observation 03e243cb-fd95-4c59-87ff-17733b9d17a7 · outbound

This paper cites Surfre e: a fast surrogate- free black-box attack.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Surfre e: a fast surrogate- free black-box attack

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.195097Z

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.

Observation 078e4e3a-9fc9-412f-870f-78c4f01a5000 · outbound

This paper cites Convergence of q-learning: A simple p roof.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Convergence of q-learning: A simple p roof

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.171482Z

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.

Observation f1ea7674-7738-4135-9e6d-ec7b42bc6e84 · outbound

This paper cites Human-level control through deep reinfor cement learning.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Human-level control through deep reinfor cement learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.142873Z

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.

Observation 218c58b0-ab4b-4194-964d-bf10811a428c · outbound

This paper cites Practical black-box attacks agai nst machine learning.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Practical black-box attacks agai nst machine learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.107036Z

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.

Observation 5c0a8c8c-00d8-48fa-97f2-c904bf92c270 · outbound

This paper cites Geoda: a geometric framework for black-box adversarial att acks.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Geoda: a geometric framework for black-box adversarial att acks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.072916Z

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.

Observation 4fddfd8d-96a3-4d1e-8bde-5a414af40210 · outbound

This paper cites Cgba: curvature- aware geometric black-box attack.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Cgba: curvature- aware geometric black-box attack

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.042475Z

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.

Observation 4650ed7f-67c4-41a2-b970-471724d8e1c9 · outbound

This paper cites Decision- based query eﬃcient adversarial attack via adaptive bounda ry learning.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Decision- based query eﬃcient adversarial attack via adaptive bounda ry learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:28.005015Z

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.

Observation fc1d788d-0efb-479e-ab37-935c537245d4 · outbound

This paper cites D ecision-based black- box attack against vision transformers via patch-wise adve rsarial removal.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack D ecision-based black- box attack against vision transformers via patch-wise adve rsarial removal

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:27.982005Z

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.

Observation 909b9f32-4878-4f4c-83a5-eafee1e9dfba · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T18:00:27.354361Z

Source-reported events for the cited work

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Observation e4a08276-fc33-4de6-bb78-44b40b890a6d · outbound

This paper cites Bounceat tack: A query-eﬃcient decision-based adversarial attack by bouncing into the wil d.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Bounceat tack: A query-eﬃcient decision-based adversarial attack by bouncing into the wil d

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:27.946614Z

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.

Observation 501b26de-f309-48fa-b1fc-cb82a7e1bc19 · outbound

This paper cites Boosting Adversarial Transferability through Enhanced Momentum.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Boosting Adversarial Transferability through Enhanced Momentum

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-12T18:00:27.511101Z

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.

Observation 89a4ffcc-ed33-4886-b79f-c27c5a8973a0 · outbound

This paper cites Triangle attack: A query-eﬃcient decision- based adversarial attack.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Triangle attack: A query-eﬃcient decision- based adversarial attack

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:27.915361Z

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.

Observation 722a6c35-88ca-4517-b439-6ddc3d4792e4 · outbound

This paper cites Better diﬀusion models further improve adversarial traini ng.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Better diﬀusion models further improve adversarial traini ng

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:27.873641Z

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.

Observation 128fbe44-6a89-489e-8d02-3d7c7ffefd86 · outbound

This paper cites Q-learning.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Q-learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:27.839983Z

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.

Observation c4075266-5b45-4a38-a079-f9d94588a486 · outbound

This paper cites Learning fr om delayed rewards.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Learning fr om delayed rewards

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:27.810790Z

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.

Observation c76907bf-9c5d-4b5a-8561-4abc77fcfd04 · outbound

This paper cites Qe-dba: Q uery-eﬃcient decision-based adversarial attacks via bayesian optimiza tion.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Qe-dba: Q uery-eﬃcient decision-based adversarial attacks via bayesian optimiza tion

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:00:27.789117Z

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.

Observation 217a918f-b974-49c3-8630-8fd0e26ef302 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T18:00:27.410355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

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