Paper Citation Record · LEDGER

Large Language Models can Learn Rules

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2310.07064.

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

pith.paper-citation-record.v1
2310.07064 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:37:57.031312Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T23:37:15.484224Z

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 ff8feeaf-0ccb-4814-9a84-fc354279b985 · inbound

Large Language Model-Brained GUI Agents: A Survey cites this paper.

Large Language Model-Brained GUI Agents: A Survey Large Language Models can Learn Rules

Reference 264

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T11:08:27.870400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2fea80ef-6685-45a6-aba4-794c1068d36e · inbound

LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers cites this paper.

LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers Large Language Models can Learn Rules

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:37:15.489646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 91179be4-2945-4384-9c99-fe1cb80a9f3f · inbound

Interactive Reasoning: Visualizing and Controlling Chain-of-Thought Reasoning in Large Language Models cites this paper.

Interactive Reasoning: Visualizing and Controlling Chain-of-Thought Reasoning in Large Language Models Large Language Models can Learn Rules

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-06T21:37:57.031312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ae8fe59-4f67-4a19-944f-d1f1ae18f29b · inbound

Lifted State Hypothesis in Large Language Models cites this paper.

Lifted State Hypothesis in Large Language Models Large Language Models can Learn Rules

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T12:35:23.748574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.