Paper Citation Record · LEDGER

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification

As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2502.03274.

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

pith.paper-citation-record.v1
2502.03274 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:24:54.898232Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:40:20.287728Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:40:22.060064Z

Reference resolution

18 of 18 outbound references displayed

verified exact2
verified fuzzy4
unresolved11
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ba1b0b9-dec2-44ca-89e3-e0eb73e01079 · outbound

This paper cites Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.807334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a3b3ff3-26cd-43aa-aa99-4cc8ff0f1931 · outbound

This paper cites Guy Katz, Derek A Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zelji´ c, et al.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Guy Katz, Derek A Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zelji´ c, et al

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.850755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1f41fbf-d1f2-4b29-83a5-60933412f08c · outbound

This paper cites On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.839895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca65f9d6-a6ae-487b-b7e2-c93e6fc3bb95 · outbound

This paper cites BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-09T05:24:55.045238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 985183b7-6d0c-4e5b-a705-3812280bde32 · outbound

This paper cites Certified Training: Small Boxes are All You Need.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Certified Training: Small Boxes are All You Need

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.867717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb72804b-bf9b-44b1-b164-d846c37958c3 · outbound

This paper cites Expressive Losses for Verified Robustness via Convex Combinations.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Expressive Losses for Verified Robustness via Convex Combinations

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.873444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ad90527-ad27-489e-91b8-47421dbe25c1 · outbound

This paper cites Thomas Winters, Giuseppe Marra, Robin Manhaeve, and Luc De Raedt.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Thomas Winters, Giuseppe Marra, Robin Manhaeve, and Luc De Raedt

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:24:55.418876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e1580b16-4c4f-499b-9e06-802e8af5dc41 · outbound

This paper cites Neuro-Symbolic Verification of Deep Neural Networks.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Neuro-Symbolic Verification of Deep Neural Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.883760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 199ef295-1cf3-4c41-b535-eeb0f9959436 · outbound

This paper cites Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks

Reference 19

Resolution: malformed identifier; no resolver link, observed 2026-08-09T05:24:54.824079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d29c3ab-5766-45e7-a0cb-7ff5fb0795e8 · outbound

This paper cites Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.893744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2879b50-df86-437d-9574-d697e5c49377 · outbound

This paper cites Efficient Neural Network Robustness Certification with General Activation Functions.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Efficient Neural Network Robustness Certification with General Activation Functions

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.898232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eae5f08d-a3d9-472b-bd25-42c6585ed606 · outbound

This paper cites An approach to reachability analysis for feed-forward ReLU neural networks.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification An approach to reachability analysis for feed-forward ReLU neural networks

Reference 1998

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.856112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13da60e3-7b09-43ad-ab12-1ce622816e44 · outbound

This paper cites Neurosymbolic markov models.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Neurosymbolic markov models

Reference 2002

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:24:55.451149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6306ae3a-e5ab-4b86-a703-844972f7f918 · outbound

This paper cites Eleonora Giunchiglia, Mihaela C˘ at˘ alina Stoian, Salman Khan, Fabio Cuzzolin, and Thomas Lukasiewicz.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Eleonora Giunchiglia, Mihaela C˘ at˘ alina Stoian, Salman Khan, Fabio Cuzzolin, and Thomas Lukasiewicz

Reference 2018

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T05:24:55.351477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6cc65e27-be8a-46ee-b916-47e735675b47 · outbound

This paper cites Johnson, and Haoze Wu.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Johnson, and Haoze Wu

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:24:55.467938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b3f5b59f-e08f-46f0-81a0-c67854e90e51 · outbound

This paper cites R¨ udiger Ehlers.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification R¨ udiger Ehlers

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.818624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59be52cf-af41-4d0a-ac6c-639a9362a597 · outbound

This paper cites Barrett, David L.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification Barrett, David L

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:24:55.434929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 452b1d94-6d10-4925-9efc-7fe1bf867c34 · outbound

This paper cites The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results.

A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T05:24:54.801060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation c88cc2bc-d5f1-4114-b5f6-f4a8ff32b108 · inbound

Hardware-efficient tractable probabilistic inference for TinyML Neurosymbolic AI applications cites this paper.

Hardware-efficient tractable probabilistic inference for TinyML Neurosymbolic AI applications A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:40:22.196900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.