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Paper Citation Record · LEDGER

A Neurosymbolic Approach to Natural Language Formalization and Verification

As of 13 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 5 inbound Pith citation observations for arXiv:2511.09008.

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

pith.paper-citation-record.v1
2511.09008 v2

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T22:49:02.222977Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T21:21:45.412616Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:39:45.195102Z

Reference resolution

7 of 7 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eafee65f-b3e6-4f72-963d-6a636639c193 · outbound

This paper cites an unresolved cited work.

A Neurosymbolic Approach to Natural Language Formalization and Verification Unresolved cited work

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T22:49:02.110502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:49:02.110502Z digest=sha256:8d9ef477cd77e5f484e14e527e568019dc3c560bb3c3e2f2fe03501d483e0146

Observation 5331d9f4-fb05-4e6e-add3-9a02af50a961 · outbound

This paper cites Table 4: Overall logical accuracy detection across types of in-context information for LLM baselines.

A Neurosymbolic Approach to Natural Language Formalization and Verification Table 4: Overall logical accuracy detection across types of in-context information for LLM baselines

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-03T22:49:02.067751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:49:02.067751Z digest=sha256:f0c58ba5b898c40af94faa5a5db0f590a7d02795ad7c3ad47ae8c6157a9e28f7

Observation d630f637-8135-455e-93dc-e275d43d6f36 · outbound

This paper cites Cats Confuse Reasoning LLM: Query Agnostic Adversarial Triggers for Reasoning Models.

A Neurosymbolic Approach to Natural Language Formalization and Verification Cats Confuse Reasoning LLM: Query Agnostic Adversarial Triggers for Reasoning Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-03T22:49:01.873707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:49:01.873707Z digest=sha256:12116a650ab0116c8a6232b0548232ee60b3324ed1c97fb0ea84ddfc4c9896a1

Observation 2819845f-e76e-4830-ae58-514d76b6c8f8 · outbound

This paper cites Each page consists of approximately 500 tokens.

A Neurosymbolic Approach to Natural Language Formalization and Verification Each page consists of approximately 500 tokens

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-03T22:49:02.222977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:49:02.222977Z digest=sha256:3664d0e6674cc9a1bbc73077a892bee19f8549dbf49f668dfc3021490cf88c83

Observation 37edbabd-2be2-43e4-9f1f-16ef4d2e1d81 · outbound

This paper cites Hyun Ryu, Gyeongman Kim, Hyemin S Lee, and Eunho Yang.

A Neurosymbolic Approach to Natural Language Formalization and Verification Hyun Ryu, Gyeongman Kim, Hyemin S Lee, and Eunho Yang

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-03T22:49:01.944436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:49:01.944436Z digest=sha256:2188a9ecfd6469792706e80bf29e7c8e4ed12d722dc3ddd53ebe8345f9ec7057

Observation e7fa6e91-bedc-4052-8660-5c9a2e750fb5 · outbound

This paper cites The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input.

A Neurosymbolic Approach to Natural Language Formalization and Verification The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-03T22:49:01.771793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:49:01.771793Z digest=sha256:e93068d6dfaa0ee5cbbaff9c818724d8b2e2d670bd62bbdfa518fd98d066c724

Observation a4766f61-05d4-4180-a24a-21a32268eab5 · outbound

This paper cites doi: 10.3233/FAIA342.

A Neurosymbolic Approach to Natural Language Formalization and Verification doi: 10.3233/FAIA342

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-03T22:49:01.706984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:49:01.706984Z digest=sha256:7d52b970f9b6e04c8963443fa0e048340e0c3d0a76b0f641c919a281c9fae129

Pith citing papers

Observation e4ecd9da-a918-4ac1-a97f-21c5287a5e72 · inbound

FregeLogic at SemEval 2026 Task 11: A Hybrid Neuro-Symbolic Architecture for Content-Robust Syllogistic Validity Prediction cites this paper.

FregeLogic at SemEval 2026 Task 11: A Hybrid Neuro-Symbolic Architecture for Content-Robust Syllogistic Validity Prediction A Neurosymbolic Approach to Natural Language Formalization and Verification

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-07-15T01:20:49.585649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-10T05:16:21.592833Z digest=sha256:392f9e7c04ff2066f0a1de1ee2000246d653b84d464bfed7232174ce8271ec74

Observation 28694f96-93dc-4f9b-9428-d01d03253334 · inbound

MANTRA: Synthesizing SMT-Validated Compliance Benchmarks for Tool-Using LLM Agents cites this paper.

MANTRA: Synthesizing SMT-Validated Compliance Benchmarks for Tool-Using LLM Agents A Neurosymbolic Approach to Natural Language Formalization and Verification

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-07-15T01:20:49.585649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-08T10:18:08.444296Z digest=sha256:f7d0e948965e4f3b266fc3dfdde8feeecfc0094deb1b9c7bb3857201ddf268b7

Observation 5ce6cf40-2a43-4f72-ac31-ad77245852f7 · inbound

Neurosymbolic Auditing of Natural-Language Software Requirements cites this paper.

Neurosymbolic Auditing of Natural-Language Software Requirements A Neurosymbolic Approach to Natural Language Formalization and Verification

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-15T01:20:49.585649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-14T18:02:20.449404Z digest=sha256:78f71031ca682e896f478992a74169703ba67528f62bb345a1eb4e3395e3cf4d

Observation 54acb188-4c19-4dea-a35d-f262e75636cf · inbound

Managing Uncertainty in LLM-Generated Procedural Knowledge for Virtual Laboratory Planning cites this paper.

Managing Uncertainty in LLM-Generated Procedural Knowledge for Virtual Laboratory Planning A Neurosymbolic Approach to Natural Language Formalization and Verification

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-15T01:20:49.585649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-29T21:21:45.412616Z digest=sha256:a86cca7d238a7a1fa9f1d6eea5770514c1f9e492281a8ba8b4da55e74cbc6416

Observation 80462bf1-69b8-4661-b5bb-91e9c89498dc · inbound

Closing the Loop: Formally Verified Law as a Reward Signal for Self-Improving Legal AI cites this paper.

Closing the Loop: Formally Verified Law as a Reward Signal for Self-Improving Legal AI A Neurosymbolic Approach to Natural Language Formalization and Verification

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-07-15T01:20:49.585649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-26T08:39:23.985069Z digest=sha256:3ffcd265d2eabddd4c7bfa6df9be01c86369d6f695a81e81566d32ec26d2aebe