Paper Citation Record · LEDGER

Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2311.07989.

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

pith.paper-citation-record.v1
2311.07989 v7

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:10:38.991652Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

17
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a443e119-8987-407d-b456-34cff9e5173a · inbound

Process-Supervised Reinforcement Learning for Code Generation cites this paper.

Process-Supervised Reinforcement Learning for Code Generation Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.991652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c50acac-f42a-4d39-bb0a-8244e4c3ea5c · inbound

CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs cites this paper.

CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 15

Resolution: malformed identifier; arxiv_id, observed 2026-05-23T02:02:23.060595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 58699f42-8b93-4da7-b856-e9c99ec43f55 · inbound

A Study of LLMs' Preferences for Libraries and Programming Languages cites this paper.

A Study of LLMs' Preferences for Libraries and Programming Languages Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 86

Resolution: malformed identifier; arxiv_id, observed 2026-05-22T22:55:12.409672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5b47a1ca-36ae-49b8-a77a-da8f5770eb7f · inbound

OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research cites this paper.

OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:35:20.045808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7cfc0821-ea5f-40ff-b2c2-26c0ab8b2ae0 · inbound

Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits cites this paper.

Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:19.315103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bab77ff3-568d-41f8-9017-dbb0cfde314f · inbound

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review cites this paper.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T12:13:31.535259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11bdea32-8364-4bfc-a271-dcea1f1ff04a · inbound

MGC: A Compiler Framework Exploiting Compositional Blindness in Aligned LLMs for Malware Generation cites this paper.

MGC: A Compiler Framework Exploiting Compositional Blindness in Aligned LLMs for Malware Generation Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:53.381111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0842354d-1f9c-4446-9397-630469681301 · inbound

GRACE: Graph-Guided Repository-Aware Code Completion through Hierarchical Code Fusion cites this paper.

GRACE: Graph-Guided Repository-Aware Code Completion through Hierarchical Code Fusion Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-05T04:48:39.805301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4d83618-e72e-4741-816c-b7e280eb88b9 · inbound

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding cites this paper.

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 109

Resolution: verified exact; arxiv_id, observed 2026-05-16T08:32:36.523773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 581909d1-14dc-4851-954c-d7705edd0092 · inbound

An Empirical Study on Influence-Based Pretraining Data Selection for Code Large Language Models cites this paper.

An Empirical Study on Influence-Based Pretraining Data Selection for Code Large Language Models Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-10T18:15:41.969237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fcf2ce2a-14ad-4632-9030-96ca0129dd84 · inbound

RepoDoc: A Knowledge Graph-Based Framework to Automatic Documentation Generation and Incremental Updates cites this paper.

RepoDoc: A Knowledge Graph-Based Framework to Automatic Documentation Generation and Incremental Updates Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:21:24.833213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bcc127e5-6633-4497-a644-25aa6382ea5e · inbound

AutoVecCoder: Teaching LLMs to Generate Explicitly Vectorized Code cites this paper.

AutoVecCoder: Teaching LLMs to Generate Explicitly Vectorized Code Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 96

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:43:14.965945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3cd012a2-a9e6-4fce-8b62-e61efee98cfa · inbound

Prompt Optimization for LLM Code Generation via Reinforcement Learning cites this paper.

Prompt Optimization for LLM Code Generation via Reinforcement Learning Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 36

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T08:53:10.301424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 07c14f6b-14ea-45e0-b0b0-febf3de08479 · inbound

What makes a harness a harness: necessary and sufficient conditions for an agent harness cites this paper.

What makes a harness a harness: necessary and sufficient conditions for an agent harness Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 66

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T15:21:00.773592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.