Paper Citation Record · LEDGER

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape

As of 9 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2506.16653.

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

pith.paper-citation-record.v1
2506.16653 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:40:59.671569Z

measured 20 of 20 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

verified exact1
verified fuzzy15
unresolved3
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 16e5286d-a525-4004-8bf7-3f6f01badb62 · outbound

This paper cites Non-Functional Requirements: Examples, Types and Approaches.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Non-Functional Requirements: Examples, Types and Approaches

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:41:00.107796Z

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 e2c49c6f-293f-4e7a-9f0d-f1515b042841 · outbound

This paper cites Big Tech’s AI-powered message to staff: Do more with less.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Big Tech’s AI-powered message to staff: Do more with less

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:41:00.088954Z

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 628375bf-67ba-49a0-b919-a2c5014430d8 · outbound

This paper cites An early look at cryptographic wa- termarks for AI-generated content.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape An early look at cryptographic wa- termarks for AI-generated content

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:41:00.069472Z

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 61d7ba59-117c-4559-a83b-57c697c316c5 · outbound

This paper cites Quantifying GitHub Copilot’s Impact on Developer Productivity and Happiness.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Quantifying GitHub Copilot’s Impact on Developer Productivity and Happiness

Reference 4

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T23:41:00.051271Z

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 499efd94-79c2-4ebb-9dba-6784e48ebd9e · outbound

This paper cites OpenAI reversed an update that made ChatGPT a suck-up—but experts say there’s no easy fix for AI that’s all too eager to please.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape OpenAI reversed an update that made ChatGPT a suck-up—but experts say there’s no easy fix for AI that’s all too eager to please

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:41:00.030051Z

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 66ee74e1-f8e7-482c-9aef-9701c604231f · outbound

This paper cites an unresolved cited work.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:41:00.011346Z

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 fa4af8f7-91fa-4493-9ec9-1ee1c39a2cf3 · outbound

This paper cites From Payrolls to Patents: The Spectrum of Data Leaked to GenAI in 2024.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape From Payrolls to Patents: The Spectrum of Data Leaked to GenAI in 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.992407Z

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 49639375-3b80-491f-9a52-405d0ab8d1cd · outbound

This paper cites Understanding Code Provenance in the Age of Genera- tive AI.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Understanding Code Provenance in the Age of Genera- tive AI

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.978295Z

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 8228bddf-a999-4153-8a83-c6886e09dc8a · outbound

This paper cites Multi-modal Synthetic Data Training and Model Collapse: Insights from VLMs and Diffusion Models.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Multi-modal Synthetic Data Training and Model Collapse: Insights from VLMs and Diffusion Models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.963415Z

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 51835b0a-63c6-439b-b588-53d173141062 · outbound

This paper cites Large Language Models for Code Generation: A Comprehensive Survey of Challenges, Techniques, Evaluation, and Applications.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Large Language Models for Code Generation: A Comprehensive Survey of Challenges, Techniques, Evaluation, and Applications

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.948996Z

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 01476dce-3390-40f6-839d-db13fa269222 · outbound

This paper cites Cybersecurity Risks of AI-Generated Code.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Cybersecurity Risks of AI-Generated Code

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.934217Z

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 e450fc3f-4ecc-42de-b366-3f1da7aab470 · outbound

This paper cites Sycophancy in Large Language Models: Causes and Mitigations.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Sycophancy in Large Language Models: Causes and Mitigations

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:40:59.632434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 031844ba-831d-4830-8af6-ca37cc646b0a · outbound

This paper cites Prioritizing Non-Functional Requirements in Agile Process Using Multi-Criteria Decision Making Analysis.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Prioritizing Non-Functional Requirements in Agile Process Using Multi-Criteria Decision Making Analysis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.919802Z

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 0aec08f3-a511-414f-be30-589b013c4983 · outbound

This paper cites 2023., https://www.nist.gov/itl/ai-risk-management-framework, retrieved 18.05.2025.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape 2023., https://www.nist.gov/itl/ai-risk-management-framework, retrieved 18.05.2025

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.904850Z

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 33441490-3201-480a-8b09-1bab46b89183 · outbound

This paper cites an unresolved cited work.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:40:59.887147Z

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 fe9f7d2c-a438-4547-be86-5236c672f4b6 · outbound

This paper cites Nearly 10% of employee GenAI prompts include sensitive data.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Nearly 10% of employee GenAI prompts include sensitive data

Reference 16

Resolution: verified exact; raw_fallback, observed 2026-08-06T23:40:59.791772Z

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 9c1906ce-4949-45d9-9389-0cda81a6f407 · outbound

This paper cites Towards Understanding Sycophancy in Language Models.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Towards Understanding Sycophancy in Language Models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.872143Z

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 df5bd12b-a710-4850-85a6-6ed56b10b2bf · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.856634Z

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 5a50f74b-472b-404d-8f53-13ef4c63a111 · outbound

This paper cites 2024 Developer Survey: AI.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape 2024 Developer Survey: AI

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.841560Z

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 a2833a51-9106-42d3-8bc1-98869cdc75d9 · outbound

This paper cites Behind the Curtain: A white-collar bloodbath.

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape Behind the Curtain: A white-collar bloodbath

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:40:59.825793Z

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.

Pith citing papers

No inbound Pith citation observations are available.