Paper Citation Record · LEDGER

Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2302.04662.

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

pith.paper-citation-record.v1
2302.04662 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:47:12.277465Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:49:41.859448Z

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 739ed503-6686-4888-aa18-df11e48b623d · inbound

LLM Contribution Summarization in Software Projects cites this paper.

LLM Contribution Summarization in Software Projects Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:44:30.449092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c20f1547-b53e-4067-b455-d9a1003d0114 · inbound

Navigating Pitfalls: Evaluating LLMs in Machine Learning Programming Education cites this paper.

Navigating Pitfalls: Evaluating LLMs in Machine Learning Programming Education Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:47:12.277465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b90f0f1-84be-4808-9012-aebc429bbe68 · inbound

Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools cites this paper.

Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:44:43.236196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9511c82d-5573-46e5-9537-58ada5d060b4 · inbound

PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs cites this paper.

PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:51:42.740694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7ea8e53b-e22f-43b2-9e6a-1ef99b948df5 · inbound

A Classroom Study of LLM-Generated Feedback Intervention in Introductory Programming cites this paper.

A Classroom Study of LLM-Generated Feedback Intervention in Introductory Programming Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:57:28.640259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cb66279a-9fba-4a45-bd5c-3389a24d55e3 · inbound

Curiosity as Linguistic Intervention: Using LLM Tutoring Dialogues to Influence Exploratory Learning Behavior cites this paper.

Curiosity as Linguistic Intervention: Using LLM Tutoring Dialogues to Influence Exploratory Learning Behavior Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:49:41.861208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.