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Paper Citation Record · LEDGER

Large Language Models for Code Summarization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.19032.

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

pith.paper-citation-record.v1
2405.19032 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T22:09:52.414483Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 f8356b5f-e6b2-4911-be71-f47bbfee1ba6 · inbound

Using Mutation-Analysis to Examine an LLM's Ability to Summarize Code cites this paper.

Using Mutation-Analysis to Examine an LLM's Ability to Summarize Code Large Language Models for Code Summarization

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-02T22:09:52.414483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:09:52.414483Z digest=sha256:db3430c72e7c212ebcd6708fca902efff57ea89b881fda733ed284ba85031d10

Observation 1751263e-8c38-422d-92da-4640138d32f0 · inbound

Large Language Models for Code Generation from Multilingual Prompts: A Curated Benchmark and a Study on Code Quality cites this paper.

Large Language Models for Code Generation from Multilingual Prompts: A Curated Benchmark and a Study on Code Quality Large Language Models for Code Summarization

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-02T01:01:33.522023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T01:01:33.522023Z digest=sha256:9490d2407383744a29bc2f5053a987b725a5745178312ff80e5181685050620b