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Paper Citation Record · LEDGER

Solving General Natural-Language-Description Optimization Problems with Large Language Models

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2407.07924.

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

pith.paper-citation-record.v1
2407.07924 v1

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 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:51:22.273098Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T06:05:35.960724Z

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 898d0a07-9594-47a3-a55e-0bcd86196552 · inbound

Decision Information Meets Large Language Models: The Future of Explainable Operations Research cites this paper.

Decision Information Meets Large Language Models: The Future of Explainable Operations Research Solving General Natural-Language-Description Optimization Problems with Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T19:51:22.273098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:51:22.273098Z digest=sha256:6c127ab7bc59de97b25a33150b6498f37ef5611d6045538757ae04ec1be4e9a0

Observation 458475b3-1dca-4e6f-8f93-f915a8bc3473 · inbound

Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM cites this paper.

Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM Solving General Natural-Language-Description Optimization Problems with Large Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:37.410144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:43:37.410144Z digest=sha256:b9016c9cd8eb52fc5ef3c4257924888be24b6f88d95ed76cc59cfd5a1283ad3a

Observation 805d322a-1d3c-44e5-ab95-a57eba83dcd5 · inbound

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving cites this paper.

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving Solving General Natural-Language-Description Optimization Problems with Large Language Models

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-04T20:55:41.409776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:55:41.409776Z digest=sha256:f8d2389e6ddcf0e970fdc1f80799ce5d1c8bd5da19beed18cef6baa82965afc6

Observation d9b9e911-7262-444c-ad38-59a23692abb6 · inbound

ORPilot: A Production-Oriented Agentic LLM-for-OR Tool for Optimization Modeling cites this paper.

ORPilot: A Production-Oriented Agentic LLM-for-OR Tool for Optimization Modeling Solving General Natural-Language-Description Optimization Problems with Large Language Models

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:05:35.963137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T18:55:28.204816Z digest=sha256:c807c0ee3dabfcd0329ebaf07eea4546f83ff2d8579fb2985af9fbd68a9a490a