Paper Citation Record · LEDGER

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent

As of 22 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2608.11258.

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

pith.paper-citation-record.v1
2608.11258 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:44:31.114157Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

25 of 25 outbound references displayed

verified exact0
verified fuzzy21
unresolved4
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7d046611-3887-4402-9a37-b1b474765ec1 · outbound

This paper cites Particle swarm optimization,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Particle swarm optimization,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.544098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 53419da0-d641-4858-93b1-ca5e14a856e5 · outbound

This paper cites Grey wolf optimizer,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Grey wolf optimizer,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T04:44:30.993517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 481c2d98-2eb3-480f-a450-c26c77c2a588 · outbound

This paper cites Adam: A method for stochastic optimization,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Adam: A method for stochastic optimization,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T04:44:30.998770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7bb6046-50b3-4020-8cc2-43d7ce3d635f · outbound

This paper cites ADADELTA: An Adaptive Learning Rate Method.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent ADADELTA: An Adaptive Learning Rate Method

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T04:44:31.003784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b628b28-37d2-4461-896e-bc87d042a64d · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Adaptive subgradient methods for online learning and stochastic optimization,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.503834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9b3488b4-737d-4542-9ab7-25e349458020 · outbound

This paper cites RMSProp: Divide the gradient by a running average of its recent magnitude,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent RMSProp: Divide the gradient by a running average of its recent magnitude,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.487320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7c753516-da4d-42e9-b717-0d97a670ebdb · outbound

This paper cites Incorporating Nesterov momentum into Adam,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Incorporating Nesterov momentum into Adam,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.471252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c141c209-10bd-4f85-811f-49615d54bb99 · outbound

This paper cites Simulation of a new hybrid particle swarm optimization algorithm,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Simulation of a new hybrid particle swarm optimization algorithm,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.454760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f23988eb-0a1e-4094-9620-45ade30cf18f · outbound

This paper cites A modified particle swarm optimizer,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent A modified particle swarm optimizer,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.438312Z

Source-reported events for the cited work

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Observation 968cc1eb-1c6b-4cc5-b937-36ca2cdf5eeb · outbound

This paper cites Adaptive particle swarm optimization,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Adaptive particle swarm optimization,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.422493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2a84de62-5679-4768-bf0a-6862f690bf27 · outbound

This paper cites Comprehensive learning particle swarm optimizer for global optimization of multimodal functions,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Comprehensive learning particle swarm optimizer for global optimization of multimodal functions,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.405865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a317386c-51d4-42c9-abc1-5f8f5c683126 · outbound

This paper cites The CMA evolution strategy: A comparing review,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent The CMA evolution strategy: A comparing review,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.387781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 32257621-1ed6-4587-84cc-3dbf6d9b59ea · outbound

This paper cites Improving the search performance of SHADE using linear population size reduction,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Improving the search performance of SHADE using linear population size reduction,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.370601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 745a73cb-6f7a-4b41-9336-814094147aa2 · outbound

This paper cites Meta-Lamarckian learning in memetic algorithms,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Meta-Lamarckian learning in memetic algorithms,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.352911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3019f5bd-182c-4833-adf8-8ddcb70be861 · outbound

This paper cites Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.336877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c75ea6af-2e0d-4b3c-9ffe-87ecde9ac7ef · outbound

This paper cites A hybrid particle swarm optimization with local search strategy,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent A hybrid particle swarm optimization with local search strategy,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.320041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 099da709-a396-4fc5-ad69-f8211cf3319f · outbound

This paper cites A simple sequentially rejective multiple test procedure,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent A simple sequentially rejective multiple test procedure,

Reference 17

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Source-reported events for the cited work

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Observation 8dbd2666-9236-4dcb-bc35-a8f69dc90b1b · outbound

This paper cites The use of ranks to avoid the assumption of normality implicit in the analysis of variance,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent The use of ranks to avoid the assumption of normality implicit in the analysis of variance,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.291778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 826694b8-43eb-4db0-9f6a-04685a1f4182 · outbound

This paper cites Use of a self-adaptive penalty approach for engineering optimization problems,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Use of a self-adaptive penalty approach for engineering optimization problems,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.274799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d7bdf566-ba4d-4110-9508-3a83f3056530 · outbound

This paper cites A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.258454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3f837d2f-2ec4-413d-873a-7c33d3cb1b3b · outbound

This paper cites Particle swarm optimization for single objective continuous space problems: A review,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Particle swarm optimization for single objective continuous space problems: A review,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.240298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 058d2e40-01dc-40b4-b8fa-8076cac812c1 · outbound

This paper cites Evolving cog- nitive and social experience in particle swarm optimization through dif- ferential evolution: A hybrid approach,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Evolving cog- nitive and social experience in particle swarm optimization through dif- ferential evolution: A hybrid approach,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.223978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation eb1c60b8-e6fb-457c-a7ae-412b3496c6df · outbound

This paper cites Combining gradient techniques for numerical multi-objective evolutionary optimization,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Combining gradient techniques for numerical multi-objective evolutionary optimization,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.207074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 81093992-6cdd-49e1-9236-fba7bd603485 · outbound

This paper cites Two-layer particle swarm optimization with intelligent division of labor,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent Two-layer particle swarm optimization with intelligent division of labor,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.189579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 560afd22-b9be-475a-846a-3f9b207cec6b · outbound

This paper cites No free lunch theorems for optimization,.

Adaptive Hybrid Particle Swarm Optimization with Gradient Descent No free lunch theorems for optimization,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:44:31.171458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.