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Paper Citation Record · LEDGER

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees

As of 7 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 0 inbound Pith citation observations for arXiv:2507.17453.

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

pith.paper-citation-record.v1
2507.17453 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:54:44.332411Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

65 of 65 outbound references displayed

  • verified exact12
  • verified fuzzy26
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e04bee5-d4c7-4f72-8ab8-f81a649b9020 · outbound

This paper cites Optimization and abstraction: a synergistic approach for analyzing neural network robustness.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Optimization and abstraction: a synergistic approach for analyzing neural network robustness

Reference 1

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Observation 4cb794c6-01a2-43fa-ab8a-fb2b26456b84 · outbound

This paper cites Strong convex relaxations and mixed-integer programming formulations for trained neural networks (2018), 1811.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Strong convex relaxations and mixed-integer programming formulations for trained neural networks (2018), 1811

Reference 2

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Observation 8549a5d5-2f66-47c6-b2eb-0d9993d1b448 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Square attack: a query-efficient black-box adversarial attack via random search

Reference 3

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Observation d382cb40-30d4-4585-a7f3-ed89d0d1a810 · outbound

This paper cites Branch and Bound for Piecewise Linear Neural Network Verification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Branch and Bound for Piecewise Linear Neural Network Verification

Reference 4

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source=arxiv_source observed=2026-08-06T14:54:44.133910Z digest=sha256:2c7fcaccbce09be6bf7a21d47889088ef4a429179c66ed26f87cb8b15f0fd948

Observation ad51bae3-ca1d-4ab8-96f2-b10b6abc5dd3 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Branch and bound for piecewise linear neural network verification

Reference 5

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Observation 2d832d43-b319-439b-9c47-d1c64053f533 · outbound

This paper cites Towards evaluating the robustness of neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Towards evaluating the robustness of neural networks

Reference 6

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Observation 0268fe9a-65ad-4486-9d2f-1bf7530c8180 · outbound

This paper cites Maximum resilience of artificial neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Maximum resilience of artificial neural networks

Reference 7

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Observation 923e071e-b430-4c69-8bc4-32f52e8dc73d · outbound

This paper cites A survey of algorithms for black-box safety validation of cyber-physical systems.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees A survey of algorithms for black-box safety validation of cyber-physical systems

Reference 8

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Observation fce475f3-dc33-42a5-9949-547eb9b50a16 · outbound

This paper cites Fast Falsification of Neural Networks using Property Directed Testing.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Fast Falsification of Neural Networks using Property Directed Testing

Reference 9

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Observation 3869d7b5-641e-4e92-8dfb-9032fb88ec37 · outbound

This paper cites Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming

Reference 10

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Observation 024baced-ad56-48f9-aaf9-e4d28adf75fe · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition

Reference 11

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Observation bfe69a1a-28ef-4971-b661-9c21ca7a8ab6 · outbound

This paper cites A DPLL(T) Framework for Verifying Deep Neural Networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees A DPLL(T) Framework for Verifying Deep Neural Networks

Reference 12

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Observation 36e36ca2-ff43-4913-b78b-0927dcfa2eca · outbound

This paper cites Harnessing neuron stability to improve dnn verification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Harnessing neuron stability to improve dnn verification

Reference 13

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verified exact
doi, observed 2026-08-06T14:54:44.488119Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 588dd4b4-3bc2-476e-ab54-97b31ec97f5d · outbound

This paper cites Efficient neural network verification with exactness characterization.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Efficient neural network verification with exactness characterization

Reference 14

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Observation c61e2f35-6bef-40de-b0c9-654b333111b8 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Formal verification of piece-wise linear feed-forward neural networks

Reference 15

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Observation 810fbc08-1480-4dc8-b80c-9601cd1f3cea · outbound

This paper cites Safety verification and robustness analysis of neural networks via quadratic constraints and semidefinite programming.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Safety verification and robustness analysis of neural networks via quadratic constraints and semidefinite programming

Reference 16

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4484d752-00be-4c52-b057-eaaccc33bb96 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound

Reference 17

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Observation 3a0593cf-dff9-4dca-9c66-84e677ad514f · outbound

This paper cites Shared certificates for neural network verification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Shared certificates for neural network verification

Reference 18

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Observation 60f20f14-0597-40ea-8ae6-ab9ded12680b · outbound

This paper cites Adaptive branch-and-bound tree exploration for neural network verification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Adaptive branch-and-bound tree exploration for neural network verification

Reference 19

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Observation ded05a70-b57b-48ed-b2ac-f715b0b3bdbc · outbound

This paper cites Fuzz testing based data augmentation to improve robustness of deep neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Fuzz testing based data augmentation to improve robustness of deep neural networks

Reference 20

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Observation 07c603d4-9cfe-47c0-9692-26b84c5336ba · outbound

This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Goodfellow, Jonathon Shlens, and Christian Szegedy

Reference 21

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Observation c9c3d047-9c22-4203-bd23-03150c29353e · outbound

This paper cites Eager falsification for accelerating robustness verification of deep neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Eager falsification for accelerating robustness verification of deep neural networks

Reference 22

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Observation 0473fdef-d90e-438b-a728-5dbcaa2f6a7f · outbound

This paper cites Gurobi Optimizer Reference Manual , 2023.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Gurobi Optimizer Reference Manual , 2023

Reference 23

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Observation 3d241bcb-0219-44ac-b13f-271c410a77ac · outbound

This paper cites Iterative counter-example guided robustness verification for neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Iterative counter-example guided robustness verification for neural networks

Reference 24

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Observation fa051654-890e-49cb-a09a-95d7b536ac97 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Deepsplit: An efficient splitting method for neural network verification via indirect effect analysis

Reference 25

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Observation e5b1df30-827c-46ac-bc1a-8b13440504e9 · outbound

This paper cites Safety verification of deep neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Safety verification of deep neural networks

Reference 26

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Reluplex: An efficient SMT solver for verifying deep neural networks

Reference 27

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Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Optimization by simulated annealing

Reference 28

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Observation 0c88b65f-0c2e-43cc-b3cb-854d1f288e49 · outbound

This paper cites Algorithms for verifying deep neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Algorithms for verifying deep neural networks

Reference 29

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Observation c4b8dfa9-824c-4081-ac19-185660e21524 · outbound

This paper cites Neural Network Branching for Neural Network Verification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Neural Network Branching for Neural Network Verification

Reference 30

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Observation 60d24cee-aa16-4ab6-a9dd-f2f178a8c262 · outbound

This paper cites Relu hull approximation.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Relu hull approximation

Reference 31

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Observation 23c28493-dd4a-4d0c-908c-8cde3d1c18b1 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Towards deep learning models resistant to adversarial attacks

Reference 32

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raw_fallback, observed 2026-08-06T14:54:45.271191Z

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Observation 43d2691c-555d-4678-84a5-a805b1e605a3 · outbound

This paper cites Scaling Polyhedral Neural Network Verification on GPUs.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Scaling Polyhedral Neural Network Verification on GPUs

Reference 33

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Observation 2a4a9049-a355-4f78-a263-b974bec88754 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results

Reference 34

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Observation 6e17f5c1-8c82-481f-b011-a26df1861cae · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations

Reference 35

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Observation 3cc405ec-3328-42e2-b4f8-79957374f5f7 · outbound

This paper cites u ller, Gleb Makarchuk, Gagandeep Singh, Markus P \.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees u ller, Gleb Makarchuk, Gagandeep Singh, Markus P \

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.240816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.240816Z digest=sha256:0ded97f5815b4a7aeb953981c2d59f29b5d760d532825cae884f423678bcdc4e

Observation 991166a1-5972-481e-aa76-3f5add011f49 · outbound

This paper cites Tensorfuzz: Debugging neural networks with coverage-guided fuzzing.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Tensorfuzz: Debugging neural networks with coverage-guided fuzzing

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.262773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.244233Z digest=sha256:54036e05f08033bbcabc2326ecc7e717e92942110c72c10d36058c7d150d6d24

Observation 3fdf4355-2b96-4510-927b-2e306017b4a2 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees An abstraction-refinement approach to verifying convolutional neural networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.247478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.247478Z digest=sha256:e0f492c04a49a17839f6933d2eb44991aa3a9e942287e3922a142d4cdf098a0d

Observation fca71369-1fff-45db-bc2e-c1713ba70847 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Deepxplore: Automated whitebox testing of deep learning systems

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.250679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.250679Z digest=sha256:140e9e797ac5833b0cf5b8bae69dad0e2139619293982200e194ab5b978e5e33

Observation 21ed128b-3ea5-4e32-87ef-7ef5eb1b25f1 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Semidefinite relaxations for certifying robustness to adversarial examples

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.253862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.253903Z digest=sha256:618227cec9c0c4fb4a2a81638ae82665be9ac69f56662b6d2d1f3463d9560dfd

Observation da425636-542a-4c60-8ece-3bcc3c5b4be0 · outbound

This paper cites Fast Neural Network Verification via Shadow Prices.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Fast Neural Network Verification via Shadow Prices

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:54:44.796173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.256955Z digest=sha256:dac86235a1be1dc69fadc7cf4abb6f402f7fc5f5ec9556bf8d285fbbefdcb82a

Observation d631dc46-40b4-4e3b-aec4-aaaff1299cb4 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Neural Network Verification with Branch-and-Bound for General Nonlinearities

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.260070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.260070Z digest=sha256:068b2f1ea45b121b1e8dcc6374e9fff67f5af97bf222ed8b1e1ab96a0626b137

Observation eb664778-9464-4ecf-994c-5e4eafeabb0c · outbound

This paper cites Efficiently computing local lipschitz constants of neural networks via bound propagation.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Efficiently computing local lipschitz constants of neural networks via bound propagation

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.244722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.263097Z digest=sha256:7eba2312999247ee4d138a3c2029532be26ab91be795ff078528206c96b5ec1b

Observation 0a005240-f7a9-43cd-b069-1ce991adb216 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Beyond the single neuron convex barrier for neural network certification

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.236113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.266237Z digest=sha256:494a8e9a20ff8c7a3de2d7cf114fadd1234324215ac15d14d43cadb83104a2eb

Observation 922032d3-44dc-4963-86fb-f885076acf65 · outbound

This paper cites Fast and effective robustness certification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Fast and effective robustness certification

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.227648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.269163Z digest=sha256:f8dc626e9eb8fc4239c7ff7764a63ab4e4db8ef1329c4575a29b56aae6489d78

Observation 85d7d93c-dcd4-497f-8387-0293a5a6fd3a · outbound

This paper cites Fast and effective robustness certification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Fast and effective robustness certification

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.219215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.271893Z digest=sha256:96a5fd633d105c0af94ba8a0b01ae2f0bbbf665ad39b68ac184a4ad1ee338c68

Observation 0a371369-5b93-4a6e-a136-6a4906fb437f · outbound

This paper cites Boosting robustness certification of neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Boosting robustness certification of neural networks

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.210028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.274696Z digest=sha256:5a48ff096611ae877fd7c9edb70d43eec9c77847a15a6527cede400f7b48f486

Observation 0af9617f-d662-4deb-aaa2-018359a5e0ab · outbound

This paper cites An abstract domain for certifying neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees An abstract domain for certifying neural networks

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.277594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.277594Z digest=sha256:1a2576a0b31f4d020882240f903cbb584eda369b7627696240107ae78d72165f

Observation 32f90b07-882e-4a27-82de-18317f4ba849 · outbound

This paper cites Deeptest: Automated testing of deep-neural-network-driven autonomous cars.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Deeptest: Automated testing of deep-neural-network-driven autonomous cars

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.280577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.280577Z digest=sha256:2cff637872cec17c15db9267e9c9982d538a6fa0bb26d83884026b558b2aa6f7

Observation e7b14479-ed8e-418b-a656-e5e9f26c8299 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees The convex relaxation barrier, revisited: Tightened single-neuron relaxations for neural network verification

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.200883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.283656Z digest=sha256:471706b5e15ef2f952de7d8c6fa89ca775a6a128ef02fbbeabc31a90210f9df4

Observation 8ed4b09d-9136-4d7d-be80-b7a9022814c9 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Evaluating robustness of neural networks with mixed integer programming

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.192167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.286829Z digest=sha256:92f817a6e45a89c8f377487bab071abe15ab6e65f4a9a50abac055b878c55ae4

Observation 11cf4181-1cee-4340-8080-3b7c2b05b1da · outbound

This paper cites Incremental verification of neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Incremental verification of neural networks

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.290305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.290305Z digest=sha256:bb7c7b15af44e2fb48630714bbca476237b3bc5946c93c91b315617d70a297ea

Observation 2b4d0781-34ca-486d-9675-d1b9f8b489f8 · outbound

This paper cites Efficient formal safety analysis of neural networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Efficient formal safety analysis of neural networks

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.183337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.293214Z digest=sha256:2a0d5e6f9e465b4e539eb2c8be9f3dede2d9271c307a19acfc7de895e1a6dd70

Observation 26cd30e4-6697-4ebf-89f8-46861ce152cc · outbound

This paper cites Formal security analysis of neural networks using symbolic intervals.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Formal security analysis of neural networks using symbolic intervals

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.174276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.296263Z digest=sha256:700dc62e04eceeaa3f2bebdb251371379329f6c1d3838f42d56cac78576bd76f

Observation b6c7e80c-0e1a-439d-9ef5-20acc07f27a8 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Beta-crown: Efficient bound propagation with per-neuron split constraints for neural network robustness verification

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.165397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.299376Z digest=sha256:f957f2b8504067789041f76dc194306ae0cb8ef8f78e51708ce9a3edc3d7220d

Observation b2a774f9-2e5c-48ff-99c9-4f6244d0466f · outbound

This paper cites Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, and Clark W.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, and Clark W

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.302569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.302569Z digest=sha256:2ac374d6c08da565f91031dffb1fdb3c20f0a86f6f57adc7b1824c9c6fd9fc8c

Observation 75835eed-2c69-48d2-bce6-1966718baea8 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Improving transferability of adversarial examples with input diversity

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T14:54:44.305757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:54:44.305757Z digest=sha256:b3e53d5bfe4410530cb5c79900f60e2e29682fd0a205822def26f08adcbdbc01

Observation 27d751f2-8873-43c7-adf1-fb4031ed68fd · outbound

This paper cites kprop: Multi-neuron relaxation method for neural network robustness verification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees kprop: Multi-neuron relaxation method for neural network robustness verification

Reference 58

Resolution
verified exact
doi, observed 2026-08-06T14:54:44.410257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.308757Z digest=sha256:7598888bcc794dc0529afcbd9ca255c11091f1c39c96a2e7b6a7b46204f13f2e

Observation 88629b8e-5e92-409b-b6d7-ebbb82056e6e · outbound

This paper cites Incremental Satisfiability Modulo Theory for Verification of Deep Neural Networks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Incremental Satisfiability Modulo Theory for Verification of Deep Neural Networks

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:54:44.401230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.311927Z digest=sha256:66b2d74040d43339cfada11de50bce32c680bcb143f91932285ba94a5b849ab8

Observation 4e0d65da-5904-41ea-9c45-47936538a010 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Improving neural network verification through spurious region guided refinement

Reference 60

Resolution
verified exact
doi, observed 2026-08-06T14:54:44.389600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.316761Z digest=sha256:75c46703b4b415b0226b41de67c4dba2645b95ee1977968a657a3839771f6611

Observation f133450e-36b7-4554-a888-c2310d9e40e5 · outbound

This paper cites Derivative-free optimization via classification.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Derivative-free optimization via classification

Reference 61

Resolution
verified exact
doi, observed 2026-08-06T14:54:44.381082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.320001Z digest=sha256:a58d29a4ca49c4676801fd2ae7ed2b0042e31cc186f650e13643dccbe8f467f1

Observation e9cbd83d-214d-46d8-bbf1-d1fbd43cbad8 · outbound

This paper cites Dilum Bandara, Shiping Chen, Jianjun Zhao, and Yulei Sui.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Dilum Bandara, Shiping Chen, Jianjun Zhao, and Yulei Sui

Reference 62

Resolution
verified exact
doi, observed 2026-08-06T14:54:44.372192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.323019Z digest=sha256:ffc00adacb26be0c646fc9a2a4e13d44dc3bf7f1d07bc56630a92898019a4697

Observation a582c4ae-349a-452d-a20c-c860650118f4 · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees A branch and bound framework for stronger adversarial attacks of relu networks

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.151466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.326209Z digest=sha256:0e5b897690da4398ff6d3af5bc47a3ab667f0058a3197c7e76ceaa4a6369dec6

Observation ee637893-d531-4361-89e8-cf14f12fb00d · outbound

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

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Efficient neural network robustness certification with general activation functions

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:54:45.142513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.329284Z digest=sha256:347d587a87bc60c0911ba67afc07e6d0c7ef06148bcb6466bb980234772f45e1

Observation 280f9ba1-4f90-44ef-b026-26c3a358899c · outbound

This paper cites Cleverest: accelerating cegar-based neural network verification via adversarial attacks.

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees Cleverest: accelerating cegar-based neural network verification via adversarial attacks

Reference 65

Resolution
verified exact
doi, observed 2026-08-06T14:54:44.362300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.332411Z digest=sha256:6aa3137da994834f9f2ce229b230aef88fb73b8c2050ad2efaf4fe96064a7935

Pith citing papers

No inbound Pith citation observations are available.