Paper Citation Record · LEDGER

Logical Neural Networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2006.13155.

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

pith.paper-citation-record.v1
2006.13155 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 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 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:19:51.527050Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:56:59.543143Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1779dc75-cbbc-4376-b74b-e3d85ad05d1a · inbound

Standard Neural Computation Alone Is Insufficient for Logical Intelligence cites this paper.

Standard Neural Computation Alone Is Insufficient for Logical Intelligence Logical Neural Networks

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-09T13:19:51.527050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95809e3e-dafb-4445-9859-65e1bb139f6f · inbound

Learning Interpretable Differentiable Logic Networks for Tabular Regression cites this paper.

Learning Interpretable Differentiable Logic Networks for Tabular Regression Logical Neural Networks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:13.245458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9052a884-1f1e-42cf-bcd0-1558417e00aa · inbound

A Comparative Study of Neurosymbolic AI Approaches to Interpretable Logical Reasoning cites this paper.

A Comparative Study of Neurosymbolic AI Approaches to Interpretable Logical Reasoning Logical Neural Networks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T04:33:36.097187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbe1262a-4029-4b24-b96d-9d3aa1356f10 · inbound

Logic of Hypotheses: from Zero to Full Knowledge in Neurosymbolic Integration cites this paper.

Logic of Hypotheses: from Zero to Full Knowledge in Neurosymbolic Integration Logical Neural Networks

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:54:22.978873Z

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 2777ac7a-3d2a-4614-9e47-632dd208404e · inbound

Enabling topography-resolving structural dynamic contact simulation cites this paper.

Enabling topography-resolving structural dynamic contact simulation Logical Neural Networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-13T17:31:33.453728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d40670ee-307b-438e-8d90-8973a907cebe · inbound

THEIA: Learning Complete Kleene Three-Valued Logic in a Pure-Neural Modular Architecture cites this paper.

THEIA: Learning Complete Kleene Three-Valued Logic in a Pure-Neural Modular Architecture Logical Neural Networks

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:06:02.290147Z

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 256be30a-1cf3-440f-8665-3a9cc028cdf4 · inbound

Overmind NSA: A Unified Neuro-Symbolic Computing Architecture with Approximate Nonlinear Activations and Preemptive Memory Bypass cites this paper.

Overmind NSA: A Unified Neuro-Symbolic Computing Architecture with Approximate Nonlinear Activations and Preemptive Memory Bypass Logical Neural Networks

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:12:26.687465Z

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 51c3911d-b317-46d9-ab66-4c8ff63e3bfe · inbound

Structured Abductive-Deductive-Inductive Reasoning for LLMs via Algebraic Invariants cites this paper.

Structured Abductive-Deductive-Inductive Reasoning for LLMs via Algebraic Invariants Logical Neural Networks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:48:01.909707Z

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 9e37d56e-27b1-41a8-850e-78e6d6b3b2b5 · inbound

Auto-Relational Reasoning cites this paper.

Auto-Relational Reasoning Logical Neural Networks

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:31:25.695780Z

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 a1b580d5-5dd0-486c-a415-179dc5d01bd0 · inbound

Temporal Reasoning Is Not the Bottleneck: A Probabilistic Inconsistency Framework for Neuro-Symbolic QA cites this paper.

Temporal Reasoning Is Not the Bottleneck: A Probabilistic Inconsistency Framework for Neuro-Symbolic QA Logical Neural Networks

Reference 72

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:07.878581Z

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 ca109c2e-ba1d-4412-9ab9-091ce2d6fdf0 · inbound

Fairness of Explanations in Artificial Intelligence (AI): A Unifying Framework, Axioms, and Future Direction toward Responsible AI cites this paper.

Fairness of Explanations in Artificial Intelligence (AI): A Unifying Framework, Axioms, and Future Direction toward Responsible AI Logical Neural Networks

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:41:25.283179Z

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 88bc3d87-ec7f-44a0-ba8d-cbde2e770c15 · inbound

Do Fair Models Reason Fairly? Counterfactual Explanation Consistency for Procedural Fairness in Credit Decisions cites this paper.

Do Fair Models Reason Fairly? Counterfactual Explanation Consistency for Procedural Fairness in Credit Decisions Logical Neural Networks

Reference 194

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T20:52:59.080904Z

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 b7a87019-b765-46e0-95cb-bede62eb85fb · inbound

Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines cites this paper.

Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines Logical Neural Networks

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-22T08:06:15.199291Z

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 2bfd1a9a-4536-4711-b572-0035edd69f58 · inbound

AttackPathGNN: Cross-function vulnerability detection in smart contracts using state interference graphs and conjunction pooling cites this paper.

AttackPathGNN: Cross-function vulnerability detection in smart contracts using state interference graphs and conjunction pooling Logical Neural Networks

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:56:59.544567Z

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 c3188ba2-dab9-44f2-a8b3-c9c1961a375d · inbound

First-Order Temporal Logic Tensor Networks cites this paper.

First-Order Temporal Logic Tensor Networks Logical Neural Networks

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-30T06:24:19.313328Z

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 73939d02-f5a4-44c5-b5b6-b99594bf1d08 · inbound

Explicit Fuzzy Logic in the Feed-Forward Layer: Self-Forgetting Quantifiers Discover Legible Grammatical-Licensing Detectors cites this paper.

Explicit Fuzzy Logic in the Feed-Forward Layer: Self-Forgetting Quantifiers Discover Legible Grammatical-Licensing Detectors Logical Neural Networks

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:15:44.371935Z

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 e65547a0-cfad-4e3e-a18c-ceeb33ad870c · inbound

Training, Reading, and Editing Legible Transformers cites this paper.

Training, Reading, and Editing Legible Transformers Logical Neural Networks

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-13T05:35:58.568346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.