Paper Citation Record · LEDGER

When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2401.10510.

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

pith.paper-citation-record.v1
2401.10510 v3

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 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T20:55:41.242558Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T22:32:44.120892Z

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 e7b223b1-444a-448a-8742-56175298fa33 · inbound

Learning Evolution via Optimization Knowledge Adaptation cites this paper.

Learning Evolution via Optimization Knowledge Adaptation When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:45:28.225384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 218243ae-32cd-45e4-abf7-23810fa56e1f · 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 When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T20:55:41.242558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 825d5d43-0743-4dbc-84e1-0eb60562a617 · inbound

An In-depth Study of LLM Contributions to the Bin Packing Problem cites this paper.

An In-depth Study of LLM Contributions to the Bin Packing Problem When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T07:02:51.221934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a98d999-ba71-40ea-82af-136345b054e0 · inbound

EvoGens: A Population-Based Heuristic Search Framework for Scientific Idea Generation cites this paper.

EvoGens: A Population-Based Heuristic Search Framework for Scientific Idea Generation When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:32:44.125585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.