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Paper Citation Record · LEDGER

DeepProbLog: Neural Probabilistic Logic Programming

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1805.10872.

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

pith.paper-citation-record.v1
1805.10872 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:55:58.899909Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T07:47:45.189120Z

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 8d104485-9930-4967-89dc-ef4a41c35f4c · inbound

Semi-Supervised Learning using Differentiable Reasoning cites this paper.

Semi-Supervised Learning using Differentiable Reasoning DeepProbLog: Neural Probabilistic Logic Programming

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-14T13:38:12.951792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:38:12.951792Z digest=sha256:c1f1c32d06595c09f591cc1701bbb5f2e9fd3fd0150664cf29daeaedcdae3b88

Observation d067b25a-35e6-4945-9e0e-7be5be86b9af · inbound

Relational Programming with Foundation Models cites this paper.

Relational Programming with Foundation Models DeepProbLog: Neural Probabilistic Logic Programming

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:21.477796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:13:21.477796Z digest=sha256:2f601024cf387d26c0fea70ca2295c12faf2e67d87c5f7f8f66a584d3869e8bc

Observation b7c9f07a-b08c-4b2d-82f1-850936e07a34 · inbound

Foundation Models for CPS-IoT: Opportunities and Challenges cites this paper.

Foundation Models for CPS-IoT: Opportunities and Challenges DeepProbLog: Neural Probabilistic Logic Programming

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-10T16:30:41.690062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:30:41.690062Z digest=sha256:ba04ef5d3efc19cb59045e84452e3b03d4fd6b88d1375cbd6e31192f8e6b6ee7

Observation 07d1db9c-85c4-464e-b325-3278afd8d161 · inbound

Enhancing Symbolic Machine Learning by Subsymbolic Representations cites this paper.

Enhancing Symbolic Machine Learning by Subsymbolic Representations DeepProbLog: Neural Probabilistic Logic Programming

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T19:55:58.899909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:55:58.899909Z digest=sha256:4d0a51d83220c1b4dd67874a2bac9eced4e4120502e1e4d61096ce4f10f3e843

Observation 7522d7f9-0870-4216-845f-cc01fe41a9c9 · inbound

A Neuro-Symbolic Framework for Accountability in Public-Sector AI cites this paper.

A Neuro-Symbolic Framework for Accountability in Public-Sector AI DeepProbLog: Neural Probabilistic Logic Programming

Reference 83

Resolution
verified exact
local_arxiv, observed 2026-05-16T23:28:40.945850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T23:24:56.685420Z digest=sha256:0fb1804ff1f1025c0a397dc0fa4cb80bdf6ac04d826f3a7f6f7ef37c2bde3a19

Observation ef0a4450-1ff0-4538-921c-297175e23b98 · inbound

A Neurosymbolic Prolog Skill for LLM-Driven Service Placement cites this paper.

A Neurosymbolic Prolog Skill for LLM-Driven Service Placement DeepProbLog: Neural Probabilistic Logic Programming

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-07-03T07:47:45.190243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T11:43:57.602045Z digest=sha256:61bd4bcd6945bb2c304758e62e803c1da11d39750a1c5993f39ffd15d7d93382

Observation 8f114eaa-5dbb-4f77-a158-e0ca1572f069 · inbound

SoftReason: A Fully Differentiable Neuro-Soft-Symbolic Deductive Reasoning Architecture over High-Dimensional Perceptual Data cites this paper.

SoftReason: A Fully Differentiable Neuro-Soft-Symbolic Deductive Reasoning Architecture over High-Dimensional Perceptual Data DeepProbLog: Neural Probabilistic Logic Programming

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-01T09:59:08.001159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T09:59:08.001159Z digest=sha256:d560811eb55827fee4db123f549197f7fd73997890bf4c47c96fcb3899d845bd

Observation 4bb752f9-4d30-4ac6-ba39-bd0723d92aa2 · inbound

Grounding Investor Views: Neural Predicates in the Black-Litterman Model cites this paper.

Grounding Investor Views: Neural Predicates in the Black-Litterman Model DeepProbLog: Neural Probabilistic Logic Programming

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-02T07:41:10.542560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:41:10.542560Z digest=sha256:5fb7747efcef7b31afd67308578e0afdb31e309b9c4f9d3be6449c8b19b4bb25

Observation 5d5b43cd-fa9e-4daa-9e8e-c6d6ad722a55 · inbound

The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning cites this paper.

The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning DeepProbLog: Neural Probabilistic Logic Programming

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T14:43:46.890220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:43:46.890220Z digest=sha256:934f723e94fca12d33928e2ba3626d01d60a328317de3b88aa3ca34c047551f8