Paper Citation Record · LEDGER

Large Language Models as Evolutionary Optimizers

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2310.19046.

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

pith.paper-citation-record.v1
2310.19046 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:04:34.607658Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T21:03:26.402053Z

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 16b92caf-f390-4179-8dd5-1c5402e12b67 · inbound

Language Models as Efficient Reward Function Searchers for Custom-Environment Multi-Objective Reinforcement cites this paper.

Language Models as Efficient Reward Function Searchers for Custom-Environment Multi-Objective Reinforcement Large Language Models as Evolutionary Optimizers

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-23T21:03:26.405092Z

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 57771152-9693-43bf-ae43-bfad4628c996 · inbound

REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models cites this paper.

REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models Large Language Models as Evolutionary Optimizers

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:32:22.157861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ae6fd86-6e4a-4f93-9c74-48d0f7b5c7b1 · inbound

ACCORD: Autoregressive Constraint-satisfying Generation for COmbinatorial Optimization with Routing and Dynamic attention cites this paper.

ACCORD: Autoregressive Constraint-satisfying Generation for COmbinatorial Optimization with Routing and Dynamic attention Large Language Models as Evolutionary Optimizers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:34.607658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e66dd1d-b2e3-4417-bc66-7e640a7db153 · inbound

On the Convergence of Large Language Model Optimizer for Black-Box Network Management cites this paper.

On the Convergence of Large Language Model Optimizer for Black-Box Network Management Large Language Models as Evolutionary Optimizers

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T20:33:42.534476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb612ac0-93e8-4977-bc73-41ba9367588d · inbound

LLM-Based Instance-Driven Heuristic Bias In the Context of a Biased Random Key Genetic Algorithm cites this paper.

LLM-Based Instance-Driven Heuristic Bias In the Context of a Biased Random Key Genetic Algorithm Large Language Models as Evolutionary Optimizers

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T05:31:06.596475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1a5d70a-cfbf-4802-bf91-85426608dcf7 · inbound

ERFSL: An Efficient Reward Function Searcher via Language Models for Custom-Environment Multi-Objective Optimization (Student Abstract) cites this paper.

ERFSL: An Efficient Reward Function Searcher via Language Models for Custom-Environment Multi-Objective Optimization (Student Abstract) Large Language Models as Evolutionary Optimizers

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T05:08:05.283748Z

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.