Paper Citation Record · LEDGER

Can Large Language Models Serve as Evaluators for Code Summarization?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2412.01333.

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

pith.paper-citation-record.v1
2412.01333 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:20:19.753566Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T03:38:57.833957Z

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 4339c255-4ae4-4a99-8527-11901eb565f7 · inbound

Can Large Language Models Understand Intermediate Representations in Compilers? cites this paper.

Can Large Language Models Understand Intermediate Representations in Compilers? Can Large Language Models Serve as Evaluators for Code Summarization?

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.753566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6813f7d-0b7f-4e78-8e46-f4d83a39b5ce · inbound

evalSmarT: An LLM-Based Framework for Evaluating Smart Contract Generated Comments cites this paper.

evalSmarT: An LLM-Based Framework for Evaluating Smart Contract Generated Comments Can Large Language Models Serve as Evaluators for Code Summarization?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T13:17:42.262914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbca0308-c386-41ea-b3d0-3003a1157511 · inbound

Knowledge-Graph-Driven Data Synthesis for Low-Resource Software Development: A HarmonyOS Case Study cites this paper.

Knowledge-Graph-Driven Data Synthesis for Low-Resource Software Development: A HarmonyOS Case Study Can Large Language Models Serve as Evaluators for Code Summarization?

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-17T03:38:57.837063Z

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.

Observation 6c19b454-d264-47db-a20e-6d6c0a437ead · 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 Can Large Language Models Serve as Evaluators for Code Summarization?

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T22:09:52.817688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.