Pith. sign in

Paper Citation Record · LEDGER

Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2205.11739.

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

pith.paper-citation-record.v1
2205.11739 v1

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 2026-08-16T05:21:43.117870Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T20:18:06.521677Z

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 3914b6b1-2d49-45aa-9aab-2032e8422e35 · inbound

A Survey on Large Language Models for Code Generation cites this paper.

A Survey on Large Language Models for Code Generation Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code

Reference 198

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:18:06.523412Z

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=2026-05-13T20:18:06.304134Z digest=sha256:7ebd74c5bda6d451ea1f1c9aea7c9be52e881fce8ef6563c3c3f1d849c5ca270

Observation 2ad96797-5601-4341-9079-ec72f77e2a28 · inbound

A Systematic Literature Review of Parameter-Efficient Fine-Tuning for Large Code Models cites this paper.

A Systematic Literature Review of Parameter-Efficient Fine-Tuning for Large Code Models Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code

Reference 102

Resolution
unresolved
no resolver link, observed 2026-08-16T05:21:43.117870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:21:43.117870Z digest=sha256:6b58337a039de0f3ef93169aa4d332113f80eb11fa7d94a00922586520c0b4be