Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.18507.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:21:21.440371Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-09T06:10:43.061401Z
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 6e7ac507-170d-43a2-aab1-f5b9d1f496a0 · inbound
RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning cites this paper.
RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:21:21.440371Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c33a8e16-3a9f-4459-a57b-fb4995054efc · inbound
Position: How can Graphs Help Large Language Models? cites this paper.
Position: How can Graphs Help Large Language Models? Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models
Reference 64
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T06:10:43.063359Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.