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Paper Citation Record · LEDGER

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification

As of 17 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2505.00963.

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

pith.paper-citation-record.v1
2505.00963 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:37:13.468613Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

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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

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0933e82c-5f9d-4b85-8dac-19cc5c296fa6 · outbound

This paper cites Algorithms for verifying deep neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Algorithms for verifying deep neural networks,

Reference 1

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Observation c5bf5383-3dfe-4520-9911-e28057ef391f · outbound

This paper cites Explaining and harnessing adversarial examples,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Explaining and harnessing adversarial examples,

Reference 2

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Observation 9ffe11e4-0dc0-4dcd-a969-3d63b4d4c372 · outbound

This paper cites The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results

Reference 3

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Source-reported events for the cited work

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Observation 43ec8f6f-e546-4eca-8b3b-2d921e867198 · outbound

This paper cites Maximum resilience of artificial neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Maximum resilience of artificial neural networks,

Reference 4

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Observation e5557692-b5ba-448f-91d5-1f0c839556bb · outbound

This paper cites Evaluating robustness of neural networks with mixed integer programming,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Evaluating robustness of neural networks with mixed integer programming,

Reference 5

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Observation 5e833c36-716e-42b2-9357-91ba61e997a6 · outbound

This paper cites Fast and effective robustness certification,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Fast and effective robustness certification,

Reference 6

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Observation 6dfbc34a-f007-40af-9441-e9dc2cfb0621 · outbound

This paper cites An abstract domain for certifying neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification An abstract domain for certifying neural networks,

Reference 7

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Observation 63f757f2-bee9-4663-bed6-326f887d6d9a · outbound

This paper cites Efficient neural network robustness certification with general activation functions,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Efficient neural network robustness certification with general activation functions,

Reference 8

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Source-reported events for the cited work

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Observation eee4d005-f4c0-4cad-92ce-df9e937e958a · outbound

This paper cites Provable defenses against adversarial examples via the convex outer adversarial polytope,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Provable defenses against adversarial examples via the convex outer adversarial polytope,

Reference 9

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Source-reported events for the cited work

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Observation 87094487-5271-4f88-8b85-e4df5f0008a8 · outbound

This paper cites Branch and bound for piecewise linear neural network verification,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Branch and bound for piecewise linear neural network verification,

Reference 10

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Source-reported events for the cited work

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Observation b279624b-8c9e-4147-9582-903ee3ec21c7 · outbound

This paper cites A survey of Monte Carlo tree search methods,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification A survey of Monte Carlo tree search methods,

Reference 11

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Source-reported events for the cited work

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Observation 808f6b5b-2cc4-4ce3-a5ee-eedf717957df · outbound

This paper cites Incremental veri- fication of neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Incremental veri- fication of neural networks,

Reference 12

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Source-reported events for the cited work

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Observation fcd552f1-96ca-4204-9398-bf4ac14b2366 · outbound

This paper cites Beta-crown: Efficient bound propagation with per-neuron split constraints for neural network robustness verification,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Beta-crown: Efficient bound propagation with per-neuron split constraints for neural network robustness verification,

Reference 13

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Source-reported events for the cited work

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Observation 98e5257a-5967-4d30-bd3b-b328c3982415 · outbound

This paper cites Deepsplit: An efficient splitting method for neural network verification via indirect effect analysis.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Deepsplit: An efficient splitting method for neural network verification via indirect effect analysis

Reference 14

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Source-reported events for the cited work

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Observation 2b0f6ecb-b834-44a4-b2d2-be8b578064ba · outbound

This paper cites Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition

Reference 15

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Source-reported events for the cited work

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Observation a62fcd78-0f6c-432c-95b6-7ccd36682b1b · outbound

This paper cites Fast and effective robustness certification,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Fast and effective robustness certification,

Reference 16

Resolution
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Source-reported events for the cited work

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Observation 170a95b4-5513-4e67-a9a2-820862e07bbc · outbound

This paper cites Two- layered falsification of hybrid systems guided by monte carlo tree search,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Two- layered falsification of hybrid systems guided by monte carlo tree search,

Reference 17

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Observation 03cff1eb-4bb4-4067-8b97-9cf491fba129 · outbound

This paper cites Reluplex: An efficient SMT solver for verifying deep neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Reluplex: An efficient SMT solver for verifying deep neural networks,

Reference 18

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Source-reported events for the cited work

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Observation f9be1525-c49d-46a0-a3ea-86df5c1512f4 · outbound

This paper cites Formal verification of piece-wise linear feed-forward neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Formal verification of piece-wise linear feed-forward neural networks,

Reference 19

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Source-reported events for the cited work

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Observation 6e6e21eb-77f8-463e-acf2-033e455b71ce · outbound

This paper cites Safety verification of deep neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Safety verification of deep neural networks,

Reference 20

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Source-reported events for the cited work

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Observation 800273c3-4017-43d2-bc71-196f18a59a3d · outbound

This paper cites Scaling Polyhedral Neural Network Verification on GPUs.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Scaling Polyhedral Neural Network Verification on GPUs

Reference 21

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Source-reported events for the cited work

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Observation 831222ad-68f0-44c8-a2fb-fc007e63b7db · outbound

This paper cites Efficient formal safety analysis of neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Efficient formal safety analysis of neural networks,

Reference 22

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Source-reported events for the cited work

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Observation 6c5793e9-d1c2-4b21-acb3-9c113a86f3e4 · outbound

This paper cites Efficiently computing local lipschitz constants of neural networks via bound prop- agation,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Efficiently computing local lipschitz constants of neural networks via bound prop- agation,

Reference 23

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Observation 61bf27fa-813f-4f29-9186-f04f7e99167e · outbound

This paper cites Strong convex relaxations and mixed-integer programming formulations for trained neural networks (2018),.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Strong convex relaxations and mixed-integer programming formulations for trained neural networks (2018),

Reference 24

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Observation a35e6a2d-1562-4683-8900-6dd1dac36c1f · outbound

This paper cites The convex relaxation barrier, revisited: Tightened single- neuron relaxations for neural network verification,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification The convex relaxation barrier, revisited: Tightened single- neuron relaxations for neural network verification,

Reference 25

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Observation a0bbbace-e15e-4a6e-bb90-0f53781f87f2 · outbound

This paper cites Beyond the single neuron convex barrier for neural network certification,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Beyond the single neuron convex barrier for neural network certification,

Reference 26

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Observation bc74a486-9846-4aa9-8c73-9b2e3c1444c0 · outbound

This paper cites Prima: general and precise neural network certification via scalable convex hull approximations,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Prima: general and precise neural network certification via scalable convex hull approximations,

Reference 27

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Observation 188e4b32-75c0-4255-a785-cc69e872e5d7 · outbound

This paper cites PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations

Reference 28

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Observation bfb31307-8724-41ae-9422-1cab497ff3b7 · outbound

This paper cites Semidefinite relaxations for certifying robustness to adversarial examples,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Semidefinite relaxations for certifying robustness to adversarial examples,

Reference 29

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Source-reported events for the cited work

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Observation 6a97c008-7549-4e0a-aeca-f3260def62f3 · outbound

This paper cites Improving neural network verification through spurious region guided refinement,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Improving neural network verification through spurious region guided refinement,

Reference 30

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Source-reported events for the cited work

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Observation 95361ce7-c50a-4e3f-a355-3fc08ab84d25 · outbound

This paper cites An abstraction-refinement approach to verifying convolutional neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification An abstraction-refinement approach to verifying convolutional neural networks,

Reference 31

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Source-reported events for the cited work

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Observation d168a7e1-74b5-4ec4-8bb5-64ddb3d94dbc · outbound

This paper cites Cleverest: accelerating cegar-based neural network verification via adversarial at- tacks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Cleverest: accelerating cegar-based neural network verification via adversarial at- tacks,

Reference 32

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Source-reported events for the cited work

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Observation 25cdea29-8615-4822-b56b-fb75fbd5409e · outbound

This paper cites Counterexample- guided abstraction refinement,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Counterexample- guided abstraction refinement,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation ab3f89a2-019c-4dfe-b720-6f42759e598f · outbound

This paper cites Neural Network Verification with Branch-and-Bound for General Nonlinearities.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Neural Network Verification with Branch-and-Bound for General Nonlinearities

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 94c73ed6-c683-467d-b077-28c3810af567 · outbound

This paper cites Neural Network Branching for Neural Network Verification.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Neural Network Branching for Neural Network Verification

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4a225650-4edf-448f-9903-e1f4eaa10bc9 · outbound

This paper cites Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound

Reference 36

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no resolver link, observed 2026-08-16T04:37:13.289166Z

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Observation 6cc5e3f0-e62e-411e-8c43-33752120fd66 · outbound

This paper cites Deepxplore: Automated whitebox testing of deep learning systems,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Deepxplore: Automated whitebox testing of deep learning systems,

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-16T04:37:14.155904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 81b40259-2f6d-4826-a285-8379e9765a23 · outbound

This paper cites Tensorfuzz: De- bugging neural networks with coverage-guided fuzzing,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Tensorfuzz: De- bugging neural networks with coverage-guided fuzzing,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-16T04:37:14.056385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation a69c561e-b947-4541-8744-52e65e2b2a7a · outbound

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

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Square attack: a query-efficient black-box adversarial attack via random search,

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-16T04:37:13.949214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 102ea460-5ebf-462c-8a9d-59f3820f119a · outbound

This paper cites Improving transferability of adversarial examples with input diversity,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Improving transferability of adversarial examples with input diversity,

Reference 40

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unresolved
no resolver link, observed 2026-08-16T04:37:13.450928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3b2600cc-2893-4e2c-ac03-f202bca340df · outbound

This paper cites A branch and bound framework for stronger adversarial attacks of relu networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification A branch and bound framework for stronger adversarial attacks of relu networks,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:37:13.882956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:37:13.458698Z digest=sha256:1c2eb305f88479ef81767248ef7fa993c56031d240949782ae79e9a4b566a7d1

Observation 170d03f8-81af-4751-a3b5-8b66dfead642 · outbound

This paper cites Towards evaluating the robustness of neural networks,.

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification Towards evaluating the robustness of neural networks,

Reference 42

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unresolved
no resolver link, observed 2026-08-16T04:37:13.468613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:37:13.468613Z digest=sha256:02dec4f2424c0bd0cea359435d6ce5a259240b9fd0c77af5ae6d24c9a874b60e

Pith citing papers

No inbound Pith citation observations are available.