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Paper Citation Record · LEDGER

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models

As of 13 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2505.24874.

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

pith.paper-citation-record.v1
2505.24874 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:17:12.000740Z

measured 16 of 16 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 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

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 66b1992f-8788-4edb-ad25-60a6840c2696 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

Resolution
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no resolver link, observed 2026-08-07T12:17:11.148765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e0cdd6cd-63f6-433e-963a-4a5a77ce32c2 · outbound

This paper cites GPT-4o System Card.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models GPT-4o System Card

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T12:17:11.274176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:17:11.274176Z digest=sha256:28701df24ec0fa94070cfa06c8f2a6a6f7895ebbbee95f0f004489b0dcbc207f

Observation d29145a0-daef-456b-b348-15183370ca92 · outbound

This paper cites MNIST handwritten digit database.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models MNIST handwritten digit database

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:17:13.217930Z

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=2026-08-07T12:17:11.416920Z digest=sha256:1c02eac069b4fc78a5fc9d0cbc6f06b0796a48d193cabfd9ac020b90b52228c1

Observation 88b538fa-8a22-4b86-907e-273dab16413a · outbound

This paper cites Faithful Chain-of-Thought Reasoning.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Faithful Chain-of-Thought Reasoning

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:17:13.044963Z

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=2026-08-07T12:17:11.457836Z digest=sha256:8dce1c4810aa962aff27011228b5f9973696ca967fd9573c31907b4cc751184d

Observation 7d8f025b-9874-4e88-87d1-8888790c7dcc · outbound

This paper cites Dolphin: A Programmable Framework for Scalable Neurosymbolic Learn- ing.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Dolphin: A Programmable Framework for Scalable Neurosymbolic Learn- ing

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T12:17:11.637443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:17:11.637443Z digest=sha256:68c0ea7deaa1a59998ef9a2f2a874f0726db6c6637ac75e8629b9065ea3dcee8

Observation 27a1e408-1ea7-4434-8375-a671cc6bd76e · outbound

This paper cites by Houda Bouamor, Juan Pino, and Kalika Bali.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models by Houda Bouamor, Juan Pino, and Kalika Bali

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:17:12.642366Z

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.

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Observation ff6fdd38-b20b-4a89-a48e-229a12fb18a4 · outbound

This paper cites Drum: End-to-end differentiable rule mining on knowledge graphs.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Drum: End-to-end differentiable rule mining on knowledge graphs

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T12:17:11.786462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:17:11.786462Z digest=sha256:20e92529507a45387d6ba94a72a70d6997f4f8bc6ae1319fda52f5b904220add

Observation 7fd8f99c-d40b-4e37-9c3c-d7c1e5995a55 · outbound

This paper cites Right for the right concept: Revising neuro-symbolic concepts by interacting with their explanations.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Right for the right concept: Revising neuro-symbolic concepts by interacting with their explanations

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:17:12.534716Z

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=2026-08-07T12:17:11.830336Z digest=sha256:d21fff3bbcfed00730187a2713601ef11826235f7c67bd3daac079d1278c7998

Observation d0253741-2e5f-437c-b879-b843dfe1c829 · outbound

This paper cites Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:17:12.387182Z

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=2026-08-07T12:17:12.000740Z digest=sha256:b91f0443369bd063cb446e1ea1e6805b3ab84dba4cee6f648f0c8fb856326d7b

Observation da5f7b63-bf69-456a-beef-a02d1ac7decb · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Gemini: A Family of Highly Capable Multimodal Models

Reference 155

Resolution
unresolved
no resolver link, observed 2026-08-07T12:17:11.856808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 770eaf43-e9f8-4729-a16d-c19671df1dcc · outbound

This paper cites Not all neuro-symbolic concepts are created equal: Analysis and mitigation of reasoning shortcuts.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Not all neuro-symbolic concepts are created equal: Analysis and mitigation of reasoning shortcuts

Reference 202

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:17:12.753373Z

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.

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Observation 22eb4399-b9e0-4c8c-bcac-f6660bdcc979 · outbound

This paper cites LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBench.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBench

Reference 2015

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unresolved
no resolver link, observed 2026-08-07T12:17:11.933468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 52e237b8-2a25-49fa-b4c8-244c740dccaf · outbound

This paper cites Learn to Explain Efficiently via Neural Logic Inductive Learning.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Learn to Explain Efficiently via Neural Logic Inductive Learning

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T12:17:11.956190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:17:11.956190Z digest=sha256:accf2cefa4dada01633a23d55c293e05deb86f1867c1908e10b3b58cd4d25506

Observation 233416bd-65b2-48a6-9ad5-63c7f663631c · outbound

This paper cites Deepproblog: Neural probabilistic logic programming.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Deepproblog: Neural probabilistic logic programming

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:17:12.908942Z

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=2026-08-07T12:17:11.544527Z digest=sha256:ccd209f967ef2a20d6fc8d8613895f7d307ccf1fd0f1a0313f80cf5811eda762

Observation 482e33d8-dbb4-4d03-bb5e-35df3e88c7c4 · outbound

This paper cites The Llama 3 Herd of Models.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models The Llama 3 Herd of Models

Reference 2024

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unresolved
no resolver link, observed 2026-08-07T12:17:11.206916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:17:11.206916Z digest=sha256:0c4a874ea9439a4f18d94dce43ef59d794af55fe582b19a43dfd514ff43b3fb2

Observation a9945a92-e04f-44d9-baf6-0664b2306f64 · outbound

This paper cites Scaling Laws for Neural Language Models.

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models Scaling Laws for Neural Language Models

Reference 2025

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unresolved
no resolver link, observed 2026-08-07T12:17:11.340236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:17:11.340236Z digest=sha256:78ff4daa4173a0a732f269106f869cb9fe5703d75e526eb3fb417cd641d147f6

Pith citing papers

No inbound Pith citation observations are available.