Paper Citation Record · LEDGER

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems

As of 23 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2507.09854.

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

pith.paper-citation-record.v1
2507.09854 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:50:12.039317Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

verified exact3
verified fuzzy6
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation af126a6b-0a88-443e-a31d-60f1899d6ffb · outbound

This paper cites Blank and Steven T.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Blank and Steven T

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T17:50:11.961980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1dc03fa-7c63-4f5e-ac4e-ebbbceeff9ae · outbound

This paper cites A framework for neurosymbolic robot action planning using large language models.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems A framework for neurosymbolic robot action planning using large language models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T17:50:11.966845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b4b2959-84e2-4045-b727-afff3cbf19a6 · outbound

This paper cites An overview of using large language models for the symbol grounding problem.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems An overview of using large language models for the symbol grounding problem

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:50:12.578983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f014746a-5e3a-4ff9-a4b2-e78245577e1e · outbound

This paper cites Colelough and William Regli.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Colelough and William Regli

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:50:12.562675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bf66adbe-31b4-4eee-82f7-4222cef4c478 · outbound

This paper cites Large language models are neurosymbolic reasoners.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Large language models are neurosymbolic reasoners

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:50:11.981448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6011dc6d-cd0d-4934-91b5-a25ea2740279 · outbound

This paper cites Automated curriculum learning for neural networks.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Automated curriculum learning for neural networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:50:12.548453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7fa04d64-c992-45b5-82fb-465b5ceb4cf1 · outbound

This paper cites Pragmatic norms are all you need -- why the symbol grounding problem does not apply to LLM s.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Pragmatic norms are all you need -- why the symbol grounding problem does not apply to LLM s

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T17:50:11.990675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02946afa-dcd7-471f-ab1a-4c98f41e5cb8 · outbound

This paper cites The symbol grounding problem.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems The symbol grounding problem

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T17:50:11.994972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ce2bedc-8b22-4f59-9c72-fea06c80d3e9 · outbound

This paper cites Negative Feedback System as Optimizer for Machine Learning Systems.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Negative Feedback System as Optimizer for Machine Learning Systems

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:50:12.327929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9d819630-296c-40e2-891a-fe253758e98b · outbound

This paper cites Mathematical Reasoning in Latent Space.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Mathematical Reasoning in Latent Space

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T17:50:12.003600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98d1e05f-96f4-420f-acf1-1a11dab346c1 · outbound

This paper cites Krakauer.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Krakauer

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T17:50:12.008546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 107d2398-f4bc-4642-9c41-23e30f3107a1 · outbound

This paper cites ART: Automatic multi-step reasoning and tool-use for large language models.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems ART: Automatic multi-step reasoning and tool-use for large language models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T17:50:12.013529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff2e6f1e-4a21-4e5a-ba9d-21fa9f28d567 · outbound

This paper cites ToolLLM : Facilitating large language models to master 16000+ real-world APIs.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems ToolLLM : Facilitating large language models to master 16000+ real-world APIs

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:50:12.533739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b577fa00-4967-45ae-8d1b-0954bd99b9f1 · outbound

This paper cites Neurosymbolic ai for enhancing instructability in generative ai.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Neurosymbolic ai for enhancing instructability in generative ai

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:50:12.518670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6fdc271b-d86e-48d8-b154-b81e0e84d46f · outbound

This paper cites Curriculum learning: A survey.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Curriculum learning: A survey

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:50:12.503248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 74b380d9-54de-425e-8a9c-9de4976c0c63 · outbound

This paper cites Wagner and Artur d'Avila Garcez.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Wagner and Artur d'Avila Garcez

Reference 17

Resolution: verified exact; doi, observed 2026-08-06T17:50:12.095954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3d2cf19d-7798-41ee-880e-0efdfc42081c · outbound

This paper cites Large language models and logical reasoning.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Large language models and logical reasoning

Reference 18

Resolution: verified exact; doi, observed 2026-08-06T17:50:12.081204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation edb01e7e-d36d-4ac3-b711-4716f395c88c · outbound

This paper cites Neurosymbolic reinforcement learning and planning: A survey.

Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems Neurosymbolic reinforcement learning and planning: A survey

Reference 19

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T17:50:12.272387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.