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Paper Citation Record · LEDGER

Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2310.13976.

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

pith.paper-citation-record.v1
2310.13976 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:48:02.469330Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:18:15.565781Z

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 eda36880-dd04-4a0e-91d6-c06d84737c18 · inbound

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation cites this paper.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:48:02.469330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:48:02.469330Z digest=sha256:86d159dcf398bed73a876f5cf6d6af02b7f3397a5b529d2496c5ee69e98f3703

Observation a5401d19-7786-402c-89f2-fa10a70d2878 · inbound

A Short Survey on Formalising Software Requirements using Large Language Models cites this paper.

A Short Survey on Formalising Software Requirements using Large Language Models Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T01:07:22.899205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:07:22.899205Z digest=sha256:ebbac238e2ae1f48419d7920b9bafc4a4e6410791e27884c48b1fd580d4c6370

Observation 68de5a9c-4265-4639-b445-26b6b9cf15bd · inbound

Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap cites this paper.

Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T18:40:02.047822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:40:02.047822Z digest=sha256:37929c8cd94a199ff77206fb0d28b46bb7a19086bba2d47a08f644a84a2c0cb0

Observation 8ce1213f-5aac-442f-929c-e53fd94efa30 · inbound

Generating Proto-Personas through Prompt Engineering: A Case Study on Efficiency, Effectiveness and Empathy cites this paper.

Generating Proto-Personas through Prompt Engineering: A Case Study on Efficiency, Effectiveness and Empathy Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:18:15.609447Z

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.

source=pdf_text observed=2026-08-06T18:18:08.453139Z digest=sha256:ad6611a32d34c0a579c91624ca85594205e34c09111b41ad0ed45c8aaa624075