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Paper Citation Record · LEDGER

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

As of 22 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 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 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: 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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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
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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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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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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

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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

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

Reference 31

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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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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:c1e32158bdfcd66dda388a2ee7f0d4f3648ba48cd4b4508bf8ec4eadad6c4d35

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.244233Z digest=sha256:ca69ca6d4cb2c9e030be20120e3f9da5cac7b8b8572bc92c913a5dbee3209c48

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:cd7c8a44bcd1acf8bdfe15e72b59a5bc3bc2bc74e11a888d68928e3d81ec3416

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:bf9ccaf09422aaf8b47f0141cdd0c7cb07428fbf981d8b078b4dd623fc0ad3cc

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.253903Z digest=sha256:1433688c96c30c80084684741f81c47eef6480e57275ee8f5fa0270743744ff8

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.256955Z digest=sha256:fa67c4df6522d541a7c21fde229a37fc541fd9c8c3ce8de7ebfe5d9a834d53a6

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=sha256:467f4b4295008c9b8bd7d8446e5daddc54bf87afafc925ad6c157bb05a410c29

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.263097Z digest=sha256:1d6d914590d12274095da1e41690df5ecda414b31cb22152b54565bd152f407b

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.266237Z digest=sha256:ecc5064e5a362df8bb3b91ef248225e12babe1e61c2b22cbf5be227e2f95ed6d

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.269163Z digest=sha256:47a52218f19876fb15fc61bc1e60ebd81d125d76c0c885dbc5a523f052ce07bd

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.271893Z digest=sha256:3efcf8e6ad965b9c80aaa9b1ae24a1c328a150776ec5f83c43218dd40bbfb2fd

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.274696Z digest=sha256:1de52c63d65820e470619b217254c2722787cf4c5022c7229cbd04c93d3f5e02

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=sha256:53e3f1ed72361a91367532f624bc35d318bc20f5eae1eaa8a70ca2399d43d7d4

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=sha256:4159e1a60e6653fd86be90420a6b463e9be69a24fc1faf09be0101e7fa4c5963

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.283656Z digest=sha256:a187b580cf82b1e2fc1ef4d6bcb5ee7132dea4ca672a5d466cff94b8ec74628f

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.286829Z digest=sha256:a881ea8fc5f5346c28444cfd4e0c56a6b4a69a51467ae13a6408b1e0d383fc52

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=sha256:8221fc8bbb2cb832e1e5663d4d11c836559778c7e900d37a5cea7a89d855a068

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.293214Z digest=sha256:73b0cb267c671e97631372f3cb0a45d0760117e8ffb2989ccd022cff56f2ef3a

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.296263Z digest=sha256:20e0a83c410ee6d79797308bc68f9a13aeb466f639ea82f177309414bd8f4f90

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.299376Z digest=sha256:cd9858767fe66adb9caa23d2eb0ae7a9b447ec7f46236671f1f82ce4eeae91b9

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=sha256:790b8f3ed26bee0444e17bd0e44c3ff02f3a38fd490e50cc873d9e2e483c53a2

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:c3aa09d4b7360c39b22cc1c7b3711720ebaea0c3153d6457a6caa6e28ebbb145

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.308757Z digest=sha256:55325a351d97a4e1dd161d7f03895a9fccf7a4c458522ac90e5215adea220400

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.311927Z digest=sha256:d8e4588f7b365e221e8db17284136f5c5aafc4d3c72ec1ace199550bfca2c0b3

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.316761Z digest=sha256:d59bb25c7fd58e510e69a2fca3b5978cb88c885c5c060c27c07eb1db39e360c2

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.320001Z digest=sha256:5e91655d89f2c33bf124ac09d98f44e834026a06d8748128e87f1f1e698f6b41

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.323019Z digest=sha256:cc589deff608727066794712605eae875a164a710ba2d154cf8e9fa22a63d4dd

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.326209Z digest=sha256:175ba5708070197851873d1c951f3eae263970d1eaa3cea3b65ca71252e13331

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.329284Z digest=sha256:d773fa6ec6a1028103612bbfa147083ec76128da4348adbcfdea540d2a86a239

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T14:54:44.332411Z digest=sha256:4b24bede45e27a420b1409ba8ee3c892511e389ba4d1a0159557eaa90397d252

Pith citing papers

No inbound Pith citation observations are available.