Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2308.11148.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:45:04.802522Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T14:40:08.000071Z
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 e8ef9694-c9b8-48c6-a05a-6239cdf94a3c · inbound
BitsAI-CR: Automated Code Review via LLM in Practice cites this paper.
BitsAI-CR: Automated Code Review via LLM in Practice LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T14:40:08.005874Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 56613aa0-9c40-4042-a7c0-3660a92f88ad · inbound
The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models cites this paper.
The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:45:04.802522Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 65c8b42a-8de8-430d-a8f6-452620908bb8 · inbound
Rethinking Training Data for Generating Code Review Comments cites this paper.
Rethinking Training Data for Generating Code Review Comments LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T01:20:08.840636Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.