Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Chain-of-Thought in Neural Code Generation: From and For Lightweight Language Models
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2312.05562.
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 2026-08-16T11:17:35.383393Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T20:25:24.622744Z
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 acc4f8c0-7e86-4c0c-a329-a7f487dc51a7 · inbound
Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency cites this paper.
Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency Chain-of-Thought in Neural Code Generation: From and For Lightweight Language Models
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:17:35.383393Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 942887d1-8dad-44fa-9e72-e3a97248f22e · inbound
Adversarial Reasoning for Repair Based on Inferred Program Intent cites this paper.
Adversarial Reasoning for Repair Based on Inferred Program Intent Chain-of-Thought in Neural Code Generation: From and For Lightweight Language Models
Reference 70
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T20:25:24.629582Z
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 f0b328d8-eab7-4945-a3f7-92756bbb47ad · inbound
Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report cites this paper.
Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report Chain-of-Thought in Neural Code Generation: From and For Lightweight Language Models
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:25:40.820336Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.