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Paper Citation Record · LEDGER

Coarse-Tuning Models of Code with Reinforcement Learning Feedback

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.18341.

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

pith.paper-citation-record.v1
2305.18341 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:47:07.662160Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T22:24:15.215286Z

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 b8322acf-3d55-410d-8b05-bd2d429fbcbf · inbound

Cyber Shadows: Neutralizing Security Threats with AI and Targeted Policy Measures cites this paper.

Cyber Shadows: Neutralizing Security Threats with AI and Targeted Policy Measures Coarse-Tuning Models of Code with Reinforcement Learning Feedback

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-10T22:24:15.221952Z

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.

source=pdf_text observed=2026-08-10T22:24:15.169663Z digest=sha256:149bffe0d22aa5c2514f62c396d702bc20cea8f0b6efd263f10b514a500aa9cd

Observation defd3581-e110-4905-9dc0-8d4a0f74517c · inbound

Tests as Prompt: A Test-Driven-Development Benchmark for LLM Code Generation cites this paper.

Tests as Prompt: A Test-Driven-Development Benchmark for LLM Code Generation Coarse-Tuning Models of Code with Reinforcement Learning Feedback

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T21:47:07.662160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:47:07.662160Z digest=sha256:89d382df48ceb6116ff10868b6f96d6018e07cdc0140a68c671ff61360399c05