Paper Citation Record · LEDGER

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems

As of 8 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2507.13095.

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

pith.paper-citation-record.v1
2507.13095 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:34:09.657105Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

16 of 16 outbound references displayed

verified exact2
verified fuzzy8
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5991bc6c-c3b7-4502-99c2-6231007f0a39 · outbound

This paper cites Large Language Models as Software Components: A Taxonomy for LLM-Integrated Applications.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Large Language Models as Software Components: A Taxonomy for LLM-Integrated Applications

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:09.590591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ae0c0cc-9d09-4b9e-b770-b5dc2ac78faa · outbound

This paper cites Large Language Model Agent: A Survey on Methodology, Applications and Challenges.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:09.595922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e93dcf82-5fdf-4c12-a085-c5e0d582e7a2 · outbound

This paper cites MARE: Multi-Agents Collaboration Framework for Requirements Engineering.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems MARE: Multi-Agents Collaboration Framework for Requirements Engineering

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:09.600993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation faf7a0f8-ec0a-4592-aca0-d19dbc09f97e · outbound

This paper cites Social simulacra: Creating populated prototypes for social computing systems,.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Social simulacra: Creating populated prototypes for social computing systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:10.004132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2f3cf78e-14f8-429a-8d58-92374732a030 · outbound

This paper cites Can large language models transform computational social science?.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Can large language models transform computational social science?

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:09.984810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3711dea3-d7e7-4754-818c-7d8603876218 · outbound

This paper cites Self-collaboration code generation via chatgpt,.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Self-collaboration code generation via chatgpt,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:09.963971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2f798c7f-53e3-4b27-af43-be435dcb3d75 · outbound

This paper cites Architectural tactics to achieve quality attributes of machine-learning-enabled systems: A systematic literature review,.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Architectural tactics to achieve quality attributes of machine-learning-enabled systems: A systematic literature review,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:09.934280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 69b5a0ef-14d0-4054-87cb-d1499b3b3125 · outbound

This paper cites What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:09.624223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1974fb4-0467-4444-a65f-edeb9a807c7d · outbound

This paper cites Lora: Low-rank adaptation of large language models.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Lora: Low-rank adaptation of large language models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:09.628689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5f03071-a01a-4ff4-96c6-38c04a853f1d · outbound

This paper cites A comparison between three sdlc models waterfall model, spiral model, and incremental/iterative model,.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems A comparison between three sdlc models waterfall model, spiral model, and incremental/iterative model,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:09.896623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b5212db2-f999-4588-a995-6f52da87d503 · outbound

This paper cites an unresolved cited work.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:34:09.880130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b9ac38cd-dd0d-4d87-8a7e-f2b5003ac925 · outbound

This paper cites Status quo and problems of requirements engineering for machine learning: Results from an international survey,.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Status quo and problems of requirements engineering for machine learning: Results from an international survey,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:09.863839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4b4f5d85-9c75-4d69-b2b6-d7dccb841353 · outbound

This paper cites Requirements engineering for machine learning: A review and reflection,.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Requirements engineering for machine learning: A review and reflection,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:09.845618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c99acf34-7988-4623-9977-bc6bd109a9bb · outbound

This paper cites Automatic Multi-level Feature Tree Construction for Domain-Specific Reusable Artifacts Management.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Automatic Multi-level Feature Tree Construction for Domain-Specific Reusable Artifacts Management

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:34:09.728785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5a901aca-aa5b-4d57-8a2c-8234b9666cfe · outbound

This paper cites Causal Models in Requirement Specifications for Machine Learning: A vision.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems Causal Models in Requirement Specifications for Machine Learning: A vision

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:34:09.704054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a760c8d0-5688-4950-b5e9-a1f8b4ce46b5 · outbound

This paper cites A first look at package- to-group mechanism: An empirical study of the linux distributions,.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems A first look at package- to-group mechanism: An empirical study of the linux distributions,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:09.826932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.