Pith. sign in

Paper Citation Record · LEDGER

Assured Automatic Programming via Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.18494.

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

pith.paper-citation-record.v1
2410.18494 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:10:19.502790Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6073b738-31f2-4d1c-9042-a9549d87fde2 · inbound

Can Large Language Models Help Students Prove Software Correctness? An Experimental Study with Dafny cites this paper.

Can Large Language Models Help Students Prove Software Correctness? An Experimental Study with Dafny Assured Automatic Programming via Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:19.502790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:10:19.502790Z digest=sha256:64fc5881ae742263c307444fe25a37434d9fcbff5ce496af3ac95ba096cf5f09

Observation 0cc529eb-cddc-46e5-ac52-ef8d0ea04ec9 · inbound

SpecRL: Reinforcement Learning with Test-Based Completeness Rewards for Formal Specification Synthesis cites this paper.

SpecRL: Reinforcement Learning with Test-Based Completeness Rewards for Formal Specification Synthesis Assured Automatic Programming via Large Language Models

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-10T19:35:45.849564Z

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.

source=pdf_text observed=2026-05-10T19:06:10.718673Z digest=sha256:7a4a54812040ac5d98d51ae7b6364d7bea9873cc81dd0f88b042ab3b107989ce