Paper Citation Record · LEDGER

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies

As of 10 August 2026, this Paper Citation Record lists 100 of 106 outbound references and 4 inbound Pith citation observations for arXiv:2506.24048.

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

pith.paper-citation-record.v1
2506.24048 v1

Coverage vector

measured 100 of 106 reference resolution

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measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T20:16:11.965782Z

Reference resolution

100 of 106 outbound references displayed

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External citation measurements

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Outbound references

Observation 4d526672-a09f-4a8c-92fa-04569bfdba9f · outbound

This paper cites Discrete Cosine Transform.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Discrete Cosine Transform

Reference 1

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Observation 6e70f21c-5973-4f18-a08b-fb60a0f62ebb · outbound

This paper cites Natural gradient works efficiently in learning.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Natural gradient works efficiently in learning

Reference 2

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Observation e80f4593-c727-44f1-8e61-54aba70bcea2 · outbound

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

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Square attack: a query-efficient black-box adversarial attack via random search

Reference 3

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This paper cites Sorting out Lipschitz function approximation.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Sorting out Lipschitz function approximation

Reference 4

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This paper cites On the Existence of the Adversarial Bayes Classifier (Extended Version).

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies On the Existence of the Adversarial Bayes Classifier (Extended Version)

Reference 5

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Observation 54b184e1-60bc-4fe7-a59c-d0d738f78c21 · outbound

This paper cites Evolutionary computation 1: Basic algorithms and operators.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Evolutionary computation 1: Basic algorithms and operators

Reference 6

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Observation 059b7005-df18-433e-b49c-e848d707c574 · outbound

This paper cites A constrained consensus based optimization algorithm and its application to finance.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A constrained consensus based optimization algorithm and its application to finance

Reference 7

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Observation edf9a586-a392-475d-b3ca-033aef9e8cf7 · outbound

This paper cites CBX: Python and Julia Packages for Consensus-Based Interacting Particle Meth- ods.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies CBX: Python and Julia Packages for Consensus-Based Interacting Particle Meth- ods

Reference 8

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This paper cites Constrained consensus-based optimization and numerical heuristics for the few particle regime.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Constrained consensus-based optimization and numerical heuristics for the few particle regime

Reference 9

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This paper cites A discrete consensus-based global optimization method with noisy objective function.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A discrete consensus-based global optimization method with noisy objective function

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Observation fe120b2d-a975-40d3-9c3a-b0e05dad0bca · outbound

This paper cites Evolution strategies–a comprehensive introduction.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Evolution strategies–a comprehensive introduction

Reference 11

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Observation 4fc13ddd-9687-414d-863f-eaa4edfa4434 · outbound

This paper cites Exploring the Space of Black-box Attacks on Deep Neural Networks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Exploring the Space of Black-box Attacks on Deep Neural Networks

Reference 12

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This paper cites A Survey of Black-Box Adversarial Attacks on Computer Vision Models.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A Survey of Black-Box Adversarial Attacks on Computer Vision Models

Reference 13

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This paper cites Consensus-based algorithms for stochastic optimization prob- lems.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Consensus-based algorithms for stochastic optimization prob- lems

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Observation 9c97a8fd-7b74-4e74-82f8-55d522647f98 · outbound

This paper cites Constrained Consensus-Based Optimiza- tion.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Constrained Consensus-Based Optimiza- tion

Reference 15

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Observation 86d9289f-4ecd-49b3-a9cf-82e679081f2a · outbound

This paper cites A particle consensus approach to solving nonconvex-nonconcave min-max problems.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A particle consensus approach to solving nonconvex-nonconcave min-max problems

Reference 16

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Observation d3fddb2f-c963-420b-b20d-ba1ad0567a01 · outbound

This paper cites A mean curvature flow arising in adversarial training.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A mean curvature flow arising in adversarial training

Reference 17

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This paper cites Polarized consensus-based dynamics for optimization and sampling.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Polarized consensus-based dynamics for optimization and sampling

Reference 18

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Observation 362f91e4-3d03-43f0-a5d2-8e3e470ff783 · outbound

This paper cites Gamma-convergence of a nonlocal perimeter arising in adversarial machine learning.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Gamma-convergence of a nonlocal perimeter arising in adversarial machine learning

Reference 19

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies CLIP: Cheap Lipschitz training of neural networks

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This paper cites MirrorCBO: A consensus-based optimization method in the spirit of mirror descent.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies MirrorCBO: A consensus-based optimization method in the spirit of mirror descent

Reference 21

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Discrete Consensus-Based Optimization

Reference 22

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Towards evaluating the robustness of neural networks

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies An analytical framework for consensus-based global optimization method

Reference 24

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A consensus-based global optimization method for high dimensional machine learning problems

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Consensus-based sampling

Reference 26

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Carrillo et al

Reference 27

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Consensus-based Optimization and En- semble Kalman Inversion for Global Optimization Problems with Constraints

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A Consensus-Based Global Optimization Method with Adaptive Momentum Estimation

Reference 29

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Zoo: Zeroth order optimization based black-box attacks to deep neural net- works without training substitute models

Reference 30

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies ImageNet: A large-scale hierarchical image database

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This paper cites There are No Bit Parts for Sign Bits in Black-Box Attacks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies There are No Bit Parts for Sign Bits in Black-Box Attacks

Reference 32

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Certified robustness via dynamic margin maximization and improved lipschitz regularization

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Lipschitz regularized Deep Neural Networks generalize and are adversarially robust

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Convergence of anisotropic consensus-based optimization in mean-field law

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Consensus-based optimization methods con- verge globally

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A pde framework of consensus-based optimization for objectives with multiple global minimizers

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Regularity and positivity of solutions of the Consensus-Based Optimization equation: unconditional global convergence

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Consensus-based optimization on hypersurfaces: Well-posedness and mean- field limit

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Anisotropic Diffusion in Consensus-Based Optimization on the Sphere

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies CB$^2$O: Consensus-Based Bi-Level Optimization

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Defending against diverse attacks in federated learning through consensus- based bi-level optimization

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Exponential natural evolution strategies

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Explaining and Harnessing Adversarial Examples

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Mean-field particle swarm optimization

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Simple black-box adversarial attacks

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies The CMA evolution strategy: a comparing review

Reference 47

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Completely derandomized self-adaptation in evolution strategies

Reference 48

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Delving deep into rectifiers: Surpassing human-level performance on ImageNet clas- sification

Reference 49

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Micro-Macro Decomposition of Particle Swarm Optimization Methods

Reference 50

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Consensus-based optimization for saddle point prob- lems

Reference 51

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Training certifiably robust neural networks with efficient local lipschitz bounds

Reference 52

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Evoba: An evolution strategy as a strong baseline for black-box adversarial attacks

Reference 53

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This paper cites Prior convictions: Black-box adversarial attacks with bandits and priors.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Prior convictions: Black-box adversarial attacks with bandits and priors

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:07.045646Z

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Observation a084afd5-d2a5-4659-8473-5145c87ea5a6 · outbound

This paper cites Black-box adversarial attacks with limited queries and information.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Black-box adversarial attacks with limited queries and information

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:07.003957Z

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Observation 36254b46-615a-4cbf-b288-335c36be5242 · outbound

This paper cites The discrete cosine transform (DCT): theory and application.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies The discrete cosine transform (DCT): theory and application

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.970269Z

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Observation 1732a3e7-3260-4e10-b9f9-45244df3dc9d · outbound

This paper cites Convergence analysis of the discrete consensus-based optimization algorithm with random batch interactions and heterogeneous noises.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Convergence analysis of the discrete consensus-based optimization algorithm with random batch interactions and heterogeneous noises

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.950078Z

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Observation 294a47fd-8ffe-4d6c-81bf-3635931c37b6 · outbound

This paper cites One weird trick for parallelizing convolutional neural networks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies One weird trick for parallelizing convolutional neural networks

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:54.085392Z

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Observation 1905a8fb-27a7-4021-b7d2-77053e21ad2a · outbound

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

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Learning multiple layers of features from tiny images

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.913143Z

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Observation 565a2c9c-d4bf-4ba6-95ea-35dba096223a · outbound

This paper cites ImageNet classification with deep convo- lutional neural networks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies ImageNet classification with deep convo- lutional neural networks

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.868457Z

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Observation 05db5baa-be2d-467f-8528-2dfd43318cbf · outbound

This paper cites Gradient-based learning applied to document recognition.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Gradient-based learning applied to document recognition

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.829889Z

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Observation 97f85b7d-5f46-42d9-be59-21b1c60c1aa6 · outbound

This paper cites Visualizing the loss landscape of neural nets.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Visualizing the loss landscape of neural nets

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.795671Z

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Observation 5bacac52-2923-4eae-af0b-637132b38fa8 · outbound

This paper cites Nattack: Learning the distributions of adversarial examples for an improved black- box attack on deep neural networks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Nattack: Learning the distributions of adversarial examples for an improved black- box attack on deep neural networks

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.751831Z

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Observation 8926b1f7-1027-4255-abf7-c87c99447659 · outbound

This paper cites Stein variational gradient descent: A general purpose bayesian inference algorithm.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Stein variational gradient descent: A general purpose bayesian inference algorithm

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.717109Z

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Observation 0ee0909f-78ed-415e-90fb-01babd51c159 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:54.783773Z

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Observation 723179bb-598e-4f38-9794-8f808a30aee4 · outbound

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Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies MNIST Challenge

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.683714Z

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Observation 6db8c6f5-95b4-4f93-965d-ebe43d99373c · outbound

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

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Back in black: A comparative evaluation of recent state-of-the-art black-box attacks

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.651611Z

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Observation 72f14620-b2e6-4b27-b9a1-8fb03f38e422 · outbound

This paper cites Yet another but more efficient black-box adversarial attack: tiling and evolution strategies.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Yet another but more efficient black-box adversarial attack: tiling and evolution strategies

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:32:00.903109Z

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Observation b0368569-6f89-47ca-83c3-d766e7be4fb7 · outbound

This paper cites Parsimonious black-box adversarial attacks via efficient combinatorial optimization.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Parsimonious black-box adversarial attacks via efficient combinatorial optimization

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.618064Z

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Observation 680d52fe-480e-4965-ab3d-a8b7859f1c2c · outbound

This paper cites Information-geometric optimization algorithms: A unifying picture via invariance principles.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Information-geometric optimization algorithms: A unifying picture via invariance principles

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.574603Z

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Observation b1e042f2-8d21-4670-96b9-09ec638f3a0d · outbound

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

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Practical black-box attacks against machine learning

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.524944Z

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Observation 5c73ff39-9ab2-4636-9ba2-6a222af90121 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:55.557174Z

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Observation 4cda50ca-f103-45e1-b529-145556dbe222 · outbound

This paper cites A consensus-based model for global optimization and its mean-field limit.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies A consensus-based model for global optimization and its mean-field limit

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.487509Z

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Observation 278c6e52-95cf-4d17-a348-513c3ed54984 · outbound

This paper cites Black-box adversarial attacks using evolution strategies.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Black-box adversarial attacks using evolution strategies

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.452607Z

Source-reported events for the cited work

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Observation 43198818-5d39-4b1d-8203-f4e02b21220f · outbound

This paper cites Rapin and O.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Rapin and O

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.407928Z

Source-reported events for the cited work

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Observation baee5fd8-e587-4261-8ecc-05f9d3452bd9 · outbound

This paper cites Evolutionsstrategien.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Evolutionsstrategien

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.380739Z

Source-reported events for the cited work

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Observation 96f0ac1e-4e6c-4ded-bfdb-52bf6c783c19 · outbound

This paper cites Leveraging memory effects and gradient information in consensus-based optimi- sation: On global convergence in mean-field law.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Leveraging memory effects and gradient information in consensus-based optimi- sation: On global convergence in mean-field law

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.355393Z

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Observation 92b9864e-4552-4ab3-a804-53db771c3fa5 · outbound

This paper cites Mathematical Foundations of Interacting Multi-Particle Systems for Optimiza- tion.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Mathematical Foundations of Interacting Multi-Particle Systems for Optimiza- tion

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.329191Z

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Observation bdc0c880-3f7c-4765-8a24-6ea49a40c2f4 · outbound

This paper cites Gradient is All You Need? 2023.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Gradient is All You Need? 2023

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:56.369052Z

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Observation d2af60a9-644a-41ed-b1f9-3bb994531b29 · outbound

This paper cites Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:56.471420Z

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Observation 45854405-d1d8-4d1f-b23c-3a3ef3e920bd · outbound

This paper cites Natural evolution strategies converge on sphere functions.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Natural evolution strategies converge on sphere functions

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.302133Z

Source-reported events for the cited work

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Observation 6e01bcff-c473-4f0e-8a84-21f48622ede5 · outbound

This paper cites Soft prompt threats: Attacking safety alignment and unlearning in open-source llms through the embedding space.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Soft prompt threats: Attacking safety alignment and unlearning in open-source llms through the embedding space

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.224438Z

Source-reported events for the cited work

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Observation ecb3e5bc-80a5-4423-9a0c-96d1f77e4580 · outbound

This paper cites Accessorize to a crime: Real and stealthy attacks on state-of-the-art face recognition.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Accessorize to a crime: Real and stealthy attacks on state-of-the-art face recognition

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:06.033229Z

Source-reported events for the cited work

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Observation cd7ab500-e37b-4f64-acbf-2e115615831b · outbound

This paper cites Simple and efficient hard label black-box adversarial attacks in low query budget regimes.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Simple and efficient hard label black-box adversarial attacks in low query budget regimes

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:05.787205Z

Source-reported events for the cited work

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Observation 59609b39-65e5-46ef-9c7b-dbd9daf09a20 · outbound

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

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:57.247798Z

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Observation fa17a98d-c7a1-41ac-a4f8-33f6c575351e · outbound

This paper cites Evolutionary algorithms and their applications to engineering problems.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Evolutionary algorithms and their applications to engineering problems

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:05.510496Z

Source-reported events for the cited work

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Observation 40631b71-44d2-477b-91b4-962bb0d8c15a · outbound

This paper cites One pixel attack for fooling deep neural networks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies One pixel attack for fooling deep neural networks

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:05.282253Z

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.

Observation cc032739-2ecc-44e4-80ee-56a2d2f7450d · outbound

This paper cites Sok: Pitfalls in evaluating black-box attacks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Sok: Pitfalls in evaluating black-box attacks

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.801162Z

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.

Observation 923d94f4-0f83-4a0e-b788-6661215c153a · outbound

This paper cites Intriguing properties of neural networks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Intriguing properties of neural networks

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:57.836186Z

Source-reported events for the cited work

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Observation 5b5ddca7-4b72-43ef-86cc-1f927bf1986f · outbound

This paper cites Rethinking the inception architecture for computer vision.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Rethinking the inception architecture for computer vision

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.592052Z

Source-reported events for the cited work

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Observation ce36519c-2170-41ba-803f-f1889671b97a · outbound

This paper cites An optimal transport approach for computing adversarial training lower bounds in multiclass classification.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies An optimal transport approach for computing adversarial training lower bounds in multiclass classification

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.469591Z

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.

Observation 3a843753-c1d4-4fb6-83bf-8bf4bbcdac59 · outbound

This paper cites The multimarginal optimal transport formu- lation of adversarial multiclass classification.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies The multimarginal optimal transport formu- lation of adversarial multiclass classification

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.340715Z

Source-reported events for the cited work

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Observation f54c6ace-5a36-438a-ac49-425567a30b11 · outbound

This paper cites Black-Box Adversarial Attacks on Deep Neural Networks: A Survey.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Black-Box Adversarial Attacks on Deep Neural Networks: A Survey

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.308347Z

Source-reported events for the cited work

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Observation c579e225-8520-42d7-861e-d95f99d6d2b6 · outbound

This paper cites Mathematical Analysis of the PDE Model for the Consensus-based Optimization.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Mathematical Analysis of the PDE Model for the Consensus-based Optimization

Reference 94

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:32:00.423366Z

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.

Observation 48f54652-7410-4fe0-ac40-20f11cac1354 · outbound

This paper cites Adversarial flows: A gradient flow characterization of adversarial attacks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Adversarial flows: A gradient flow characterization of adversarial attacks

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-06T21:31:58.832095Z

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Observation 7c7d21c2-c9c1-4736-aa86-133676c182ac · outbound

This paper cites Natural evolution strategies.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Natural evolution strategies

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.255205Z

Source-reported events for the cited work

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Observation 0186aeee-976a-4ff8-9d2d-df28e3a06eb7 · outbound

This paper cites Generating adversarial examples with adversarial networks.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Generating adversarial examples with adversarial networks

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.211986Z

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.

Observation 81287f03-30d8-4051-832f-8d41943a5635 · outbound

This paper cites Fast Evolutionary Programming.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Fast Evolutionary Programming

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.172434Z

Source-reported events for the cited work

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Observation d6c15d30-28b3-4474-96dc-b13ebae564ec · outbound

This paper cites Rethinking lipschitz neural networks and certified robustness: A boolean func- tion perspective.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Rethinking lipschitz neural networks and certified robustness: A boolean func- tion perspective

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.141052Z

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.

Observation 88f958ce-e5e7-4701-a8ea-fe184c33f51c · outbound

This paper cites Towards query-efficient black-box adversary with zeroth-order natural gradient de- scent.

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies Towards query-efficient black-box adversary with zeroth-order natural gradient de- scent

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:32:04.112748Z

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.

Pith citing papers

Observation c4967be6-d834-43ac-803e-0d8348d14445 · inbound

Convergence of Consensus-Based Particle Methods for Nonconvex Bi-Level Optimization cites this paper.

Convergence of Consensus-Based Particle Methods for Nonconvex Bi-Level Optimization Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies

Reference 177

Resolution: verified exact; arxiv_id, observed 2026-05-20T04:43:03.637842Z

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.

Observation e1701237-7dfb-4888-8d65-1652d3916cf8 · inbound

From Mean-Field Limits to Semiclassical Concentration: Global Convergence of the Canonical Evolutionary Strategy cites this paper.

From Mean-Field Limits to Semiclassical Concentration: Global Convergence of the Canonical Evolutionary Strategy Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:04:58.227173Z

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.

Observation 4a30d099-6c1d-4e62-bf66-64896d85510e · inbound

A derivative-free particle method for optimization in Hilbert spaces cites this paper.

A derivative-free particle method for optimization in Hilbert spaces Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:16:11.967230Z

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.

Observation 8646f045-5bc7-476c-9f46-bfd6802756da · inbound

Exploiting Structure with Anisotropic Consensus-Based Optimization cites this paper.

Exploiting Structure with Anisotropic Consensus-Based Optimization Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies

Reference 88

Resolution: unresolved; no resolver link, observed 2026-07-14T13:31:32.846894Z

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