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Paper Citation Record · LEDGER

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification

As of 8 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2507.23197.

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

pith.paper-citation-record.v1
2507.23197 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:04:59.627489Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T03:57:46.650349Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy27
  • unresolved6
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b2d1e37-6066-421c-99b0-bebf4d76af78 · outbound

This paper cites an unresolved cited work.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Unresolved cited work

Reference 1

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 07edfac5-b59d-4fbf-8d87-d2cb76e2ab70 · outbound

This paper cites nnenum: Verification of relu neural networks with optimized abstrac- tion refinement.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification nnenum: Verification of relu neural networks with optimized abstrac- tion refinement

Reference 2

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Source-reported events for the cited work

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Observation a1301b00-246b-4217-a665-14c70f33b7e6 · outbound

This paper cites Adversarial training and provable de- fenses: Bridging the gap.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Adversarial training and provable de- fenses: Bridging the gap

Reference 3

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Observation eb012e74-9249-4c53-bd48-f0fc7aecc816 · outbound

This paper cites an unresolved cited work.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7aa4a2cf-74ac-48a6-afee-58227181818e · outbound

This paper cites Johnson, David Shriver, and Haoze (Andrew) Wu.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Johnson, David Shriver, and Haoze (Andrew) Wu

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 334aee2c-d4de-4c5c-a9be-cb105d2fba03 · outbound

This paper cites Johnson, and Changliu Liu.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Johnson, and Changliu Liu

Reference 6

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Source-reported events for the cited work

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Observation 47577947-0e13-41b6-9290-0698feebb809 · outbound

This paper cites Pawan Kumar, Alessandro De Palma, and Robert Stanforth.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Pawan Kumar, Alessandro De Palma, and Robert Stanforth

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 916a2003-ed58-4b06-bea5-40aa09a19faa · outbound

This paper cites Branch and bound for piecewise linear neural network verifica- tion.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Branch and bound for piecewise linear neural network verifica- tion

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b3de3d99-cb29-437f-897b-133cad272f3d · outbound

This paper cites Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming.Advances in Neural In- formation Processing Systems, 33:5318–5331, 2020.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming.Advances in Neural In- formation Processing Systems, 33:5318–5331, 2020

Reference 9

Resolution
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Source-reported events for the cited work

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Observation 2dbffe98-1c41-4fe4-ade5-59cb69a220a8 · outbound

This paper cites Scaling the convex barrier with active sets.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Scaling the convex barrier with active sets

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c919df03-248c-48e4-accb-55d306fe93ee · outbound

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

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 54557291-22e6-4fdc-b979-092f69b41ec5 · outbound

This paper cites Reciph: Relational coefficients for input partitioning heuristic.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Reciph: Relational coefficients for input partitioning heuristic

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6a69dd90-4449-4509-afcd-990d5d9e7249 · outbound

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

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Formal verification of piece-wise linear feed-forward neural net- works

Reference 13

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d68e8853-667f-454a-b34d-1fe6a31b558a · outbound

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

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Formal verification of piece-wise linear feed-forward neural net- works

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:04:59.936844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 2b74b0fd-b9bb-4838-b85b-333d74d8bc82 · outbound

This paper cites Com- plete verification via multi-neuron relaxation guided branch-and-bound.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Com- plete verification via multi-neuron relaxation guided branch-and-bound

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ef65fe25-82f6-4f70-991f-677d951880a0 · outbound

This paper cites Divide and slide: Layer-wise refinement for output range analysis of deep neural networks.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Divide and slide: Layer-wise refinement for output range analysis of deep neural networks

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation bdcc0b85-81c5-4b3d-a721-36a9aab59660 · outbound

This paper cites Dill, Kyle Julian, and Mykel J.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Dill, Kyle Julian, and Mykel J

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1634b5fd-da2b-4054-a4c8-7110e097609e · outbound

This paper cites Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zeljić, David L.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zeljić, David L

Reference 18

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Source-reported events for the cited work

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Observation 0f6c511d-77e4-46c9-8d4c-750ba5f7aa09 · outbound

This paper cites Prima:Generalandpreciseneuralnetworkcertificationviascalable convex hull approximations.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Prima:Generalandpreciseneuralnetworkcertificationviascalable convex hull approximations

Reference 19

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7140c366-8132-4d41-a4c0-59bb6fad5b59 · outbound

This paper cites an unresolved cited work.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Unresolved cited work

Reference 20

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unresolved
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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9349a6e4-15d5-4bc8-8793-16cede6a789d · outbound

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

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Beyond the single neuron convex barrier for neural network certification

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 89b9c80b-f4c7-4c92-91b3-e971ec2e088b · outbound

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

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification An abstract domain for certifying neural networks.Proc

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation cbbf2131-2007-48e3-98d7-98bf4b1ea882 · outbound

This paper cites Robustness certification with refinement.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Robustness certification with refinement

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7ba62257-5dc2-4d85-a71b-02f2908e4374 · outbound

This paper cites Intriguing properties of neural networks.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Intriguing properties of neural networks

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 552c6c76-0101-41ac-bfbc-245495915f97 · outbound

This paper cites an unresolved cited work.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Unresolved cited work

Reference 25

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unresolved
raw_fallback, observed 2026-08-06T11:04:59.792388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f6c70a15-8123-497b-b5d7-f1a302a8cbb6 · outbound

This paper cites Evaluating robustness of neural networks with mixed integer programming.International Conference on Learning Representations (ICLR’19), 2019.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Evaluating robustness of neural networks with mixed integer programming.International Conference on Learning Representations (ICLR’19), 2019

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 14206cd6-e46c-4f7b-96e6-1247dbeafc8a · outbound

This paper cites Zico Kolter.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Zico Kolter

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:04:59.765893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T11:04:59.602258Z digest=sha256:15f3c7d400237b7eccef7dd63033fec0c21df400e82729e748dc670ddd23dd50

Observation 9174e629-33a7-4228-a626-4dfd17f87235 · outbound

This paper cites Efficient global robustness certification of neural networks via interleaving twin-network encoding.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Efficient global robustness certification of neural networks via interleaving twin-network encoding

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:04:59.750646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T11:04:59.606244Z digest=sha256:955f3dd84a119a016217ea420bdfda626a04ce9e0046ee004ea5625cbe254172

Observation ac04dfdc-0d43-4001-b9b7-b927bb09e8dc · outbound

This paper cites Marabou 2.0: A versatile formal analyzer of neural networks.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Marabou 2.0: A versatile formal analyzer of neural networks

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:04:59.736220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T11:04:59.610509Z digest=sha256:a52df8d1cafe7290de318279af848d887f0a6dee9a3a376ef50e34e4010242c5

Observation 2e816194-23f0-43a2-94d4-e335aa8fac9b · outbound

This paper cites an unresolved cited work.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-06T11:04:59.721625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation bf5ab34a-6a38-4b19-ad65-497d24861ad4 · outbound

This paper cites Fast and complete: Enabling complete neural network verification with rapid and massively parallel incomplete verifiers.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Fast and complete: Enabling complete neural network verification with rapid and massively parallel incomplete verifiers

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:04:59.708394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9c447776-2b47-461c-b9b2-e8b85d05ba81 · outbound

This paper cites solver: batch size: 512 beta-crown: iteration: 20.

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification solver: batch size: 512 beta-crown: iteration: 20

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:04:59.694768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T11:04:59.622347Z digest=sha256:a15b07950743bffaa14e3c170b90ce99ee919daee7cb76dfa3e12277eddfcbc6

Observation 75fae802-3436-4d1b-a81c-91b92ba1f7d7 · outbound

This paper cites Notice that this does not lead to a runtime of 20.000s, as 20 threads are used by pMILP in parallel (similar to competing solutions, except α, β-CROWN which uses> 4096 GPU cores).

Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification Notice that this does not lead to a runtime of 20.000s, as 20 threads are used by pMILP in parallel (similar to competing solutions, except α, β-CROWN which uses> 4096 GPU cores)

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:04:59.679797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Fast SDP certification of neural networks : towards large multi-class datasets cites this paper.

Fast SDP certification of neural networks : towards large multi-class datasets Solution-aware vs global ReLU selection: partial MILP strikes back for DNN verification

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