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Paper Citation Record · LEDGER

NeurOptimisation: The Spiking Way to Evolve

As of 11 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2507.08320.

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

pith.paper-citation-record.v1
2507.08320 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:29:12.816543Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

41 of 41 outbound references displayed

  • verified exact3
  • verified fuzzy31
  • unresolved4
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6d2dab44-1173-40b7-9d54-d815ce56dc08 · outbound

This paper cites An electromagnetic perspec- tive of artificial intelligence neuromorphic chips,.

NeurOptimisation: The Spiking Way to Evolve An electromagnetic perspec- tive of artificial intelligence neuromorphic chips,

Reference 1

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0ae5c61d-0401-4565-872f-7d6166e6d4aa · outbound

This paper cites Exploring spiking neural networks: a comprehen- sive analysis of mathematical models and applications,.

NeurOptimisation: The Spiking Way to Evolve Exploring spiking neural networks: a comprehen- sive analysis of mathematical models and applications,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:20.063848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation bd4f6dc1-da49-47cc-aba4-20b7e8df1abd · outbound

This paper cites Spiking Neural Networks: A Survey,.

NeurOptimisation: The Spiking Way to Evolve Spiking Neural Networks: A Survey,

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 8a24fdd8-1f4c-4e6e-85c0-312fe94d7472 · outbound

This paper cites Neuromorphic artificial intelligence sys- tems,.

NeurOptimisation: The Spiking Way to Evolve Neuromorphic artificial intelligence sys- tems,

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ce9a3c01-d9d9-495e-ba7c-35220d85274d · outbound

This paper cites A survey on evolutionary computation for complex continuous optimization,.

NeurOptimisation: The Spiking Way to Evolve A survey on evolutionary computation for complex continuous optimization,

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4f11f938-6cad-4230-8b39-91a88f790f55 · outbound

This paper cites Large-scale evolutionary optimization: A review and comparative study,.

NeurOptimisation: The Spiking Way to Evolve Large-scale evolutionary optimization: A review and comparative study,

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 197c1ece-7d75-436e-a95e-621eb4994c6f · outbound

This paper cites Neuromorphic-based metaheuristics: A new generation of low power, low latency and small footprint optimization algorithms.

NeurOptimisation: The Spiking Way to Evolve Neuromorphic-based metaheuristics: A new generation of low power, low latency and small footprint optimization algorithms

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:29:14.027304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 8f3c4204-a2fd-4f36-ba2f-efc3bd375564 · outbound

This paper cites Lava: A software framework for neuromorphic computing,.

NeurOptimisation: The Spiking Way to Evolve Lava: A software framework for neuromorphic computing,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:19.231945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6f5b79c3-fe4d-4807-bad5-1d23ec90a33b · outbound

This paper cites COCO: A platform for comparing continuous optimizers in a black-box setting,.

NeurOptimisation: The Spiking Way to Evolve COCO: A platform for comparing continuous optimizers in a black-box setting,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:19.053437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 9cc20d3c-7293-41c1-aa44-59c600b78e51 · outbound

This paper cites A ferroelectric memristor-based transient chaotic neural network for solving combinatorial optimization problems,.

NeurOptimisation: The Spiking Way to Evolve A ferroelectric memristor-based transient chaotic neural network for solving combinatorial optimization problems,

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2d3f0d42-5322-4850-a576-d06799a0984f · outbound

This paper cites Organic memristor-based flexible neural networks with bio-realistic synaptic plasticity for complex combinatorial optimization,.

NeurOptimisation: The Spiking Way to Evolve Organic memristor-based flexible neural networks with bio-realistic synaptic plasticity for complex combinatorial optimization,

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0215ee75-a901-4004-ac1d-73cea1ad0943 · outbound

This paper cites Neuromorphic swarm on RRAM compute-in-memory processor for solving QUBO problem,.

NeurOptimisation: The Spiking Way to Evolve Neuromorphic swarm on RRAM compute-in-memory processor for solving QUBO problem,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:18.585046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 81841eae-00e3-4c3d-bce5-4cab748fa39d · outbound

This paper cites Solving QUBO on the Loihi 2 Neuromorphic Processor,.

NeurOptimisation: The Spiking Way to Evolve Solving QUBO on the Loihi 2 Neuromorphic Processor,

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3075e61e-f84b-4c74-8eb8-1f40d5ead07c · outbound

This paper cites Towards spike-based machine intelligence with neuromorphic computing,.

NeurOptimisation: The Spiking Way to Evolve Towards spike-based machine intelligence with neuromorphic computing,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T18:29:09.669863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d8d4c935-3ff9-40ef-a9c6-9c541e7ea288 · outbound

This paper cites Evolutionary Spiking Neural Networks: A Survey.

NeurOptimisation: The Spiking Way to Evolve Evolutionary Spiking Neural Networks: A Survey

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:29:13.189229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d1f3a068-a1e0-4cd7-b2cd-82b092affe20 · outbound

This paper cites Evolutionary optimization for neuromorphic systems,.

NeurOptimisation: The Spiking Way to Evolve Evolutionary optimization for neuromorphic systems,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T18:29:09.923414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fba73fa6-d276-4824-83c9-3fda9c88570f · outbound

This paper cites Real-time evolution and deployment of neu- romorphic computing at the edge,.

NeurOptimisation: The Spiking Way to Evolve Real-time evolution and deployment of neu- romorphic computing at the edge,

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation bc6df10c-91f6-43d4-b30e-a5410c87b8cd · outbound

This paper cites A swarm optimization solver based on ferroelectric spiking neural networks,.

NeurOptimisation: The Spiking Way to Evolve A swarm optimization solver based on ferroelectric spiking neural networks,

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e6a1d3e4-809b-4918-ac2d-7b37a23ed464 · outbound

This paper cites Swarm intelligence algorithm based on spiking neural-oscillator networks, coupling interactions and search performances,.

NeurOptimisation: The Spiking Way to Evolve Swarm intelligence algorithm based on spiking neural-oscillator networks, coupling interactions and search performances,

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 212d82b5-a2a7-455b-953b-3089d3e6fed1 · outbound

This paper cites Advancements in algorithms and neuromorphic hard- ware for spiking neural networks,.

NeurOptimisation: The Spiking Way to Evolve Advancements in algorithms and neuromorphic hard- ware for spiking neural networks,

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c6db8995-42e7-4f49-8e09-700412ee2d04 · outbound

This paper cites Neuromorphic bayesian optimization in Lava,.

NeurOptimisation: The Spiking Way to Evolve Neuromorphic bayesian optimization in Lava,

Reference 21

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 49b7aa60-f86a-4a12-8abd-914abc878c6d · outbound

This paper cites Asynchronous neuromorphic optimization in Lava,.

NeurOptimisation: The Spiking Way to Evolve Asynchronous neuromorphic optimization in Lava,

Reference 22

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:29:13.482364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 768c2c1a-ee03-4fd5-8bee-d55e18f747f8 · outbound

This paper cites Parallelized multi-agent bayesian optimization in Lava,.

NeurOptimisation: The Spiking Way to Evolve Parallelized multi-agent bayesian optimization in Lava,

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 86f77818-c223-409c-8454-895a61b09c8c · outbound

This paper cites Hyper-heuristics to customise metaheuristics for continuous optimisation,.

NeurOptimisation: The Spiking Way to Evolve Hyper-heuristics to customise metaheuristics for continuous optimisation,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:17.242423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c3f5fb50-8da2-48f5-9819-05c7885d6cc6 · outbound

This paper cites Recent advances in selection hyper-heuristics,.

NeurOptimisation: The Spiking Way to Evolve Recent advances in selection hyper-heuristics,

Reference 25

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f1ecfc39-79e2-4179-9092-ae3c2e651f5a · outbound

This paper cites Talbi,Metaheuristics: from design to implementation.

NeurOptimisation: The Spiking Way to Evolve Talbi,Metaheuristics: from design to implementation

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:17.039555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 178a5954-1910-49d4-8bb6-eec6895dde51 · outbound

This paper cites Towards a generalised metaheuristic model for continuous optimisation problems,.

NeurOptimisation: The Spiking Way to Evolve Towards a generalised metaheuristic model for continuous optimisation problems,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:16.854721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 89dd4760-f19d-4f79-bba5-06b27a360680 · outbound

This paper cites Differential evolution mutations: Taxonomy, comparison and convergence analysis,.

NeurOptimisation: The Spiking Way to Evolve Differential evolution mutations: Taxonomy, comparison and convergence analysis,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:16.642193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6a4cf0d3-d800-4a0a-ab0b-3988ce028bf1 · outbound

This paper cites Spiking neural networks and their applications: A review,.

NeurOptimisation: The Spiking Way to Evolve Spiking neural networks and their applications: A review,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:16.430670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 8ac18865-2e3e-48bb-b247-ea7ad8567479 · outbound

This paper cites Opportunities for neuromorphic computing algorithms and applications,.

NeurOptimisation: The Spiking Way to Evolve Opportunities for neuromorphic computing algorithms and applications,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:16.253578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation cdec18df-64ec-4cff-a495-60d02354eb10 · outbound

This paper cites Simple model of spiking neurons,.

NeurOptimisation: The Spiking Way to Evolve Simple model of spiking neurons,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:16.070887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 68561f2c-1e43-4b40-9de2-62b0b09693a5 · outbound

This paper cites an unresolved cited work.

NeurOptimisation: The Spiking Way to Evolve Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:29:15.875509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation f047487b-1440-472b-a068-c04c3449af9f · outbound

This paper cites Tornado: An Autonomous Chaotic Algorithm for Large Scale Global Optimization,.

NeurOptimisation: The Spiking Way to Evolve Tornado: An Autonomous Chaotic Algorithm for Large Scale Global Optimization,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:15.633283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 17cde45e-a3a8-4ea4-8616-099a5120c5c4 · outbound

This paper cites A review of computational models for gamma oscillation dynamics: from spiking neurons to neural masses,.

NeurOptimisation: The Spiking Way to Evolve A review of computational models for gamma oscillation dynamics: from spiking neurons to neural masses,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:15.384528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:29:12.262557Z digest=sha256:a22e7c4f09e493a4307d3f249e58ae8cd23036d6cd46b7b44cbe9762f497d942

Observation 68817eea-7301-41d0-837c-4268eeef63ee · outbound

This paper cites Spiking neural networks for nonlinear regression,.

NeurOptimisation: The Spiking Way to Evolve Spiking neural networks for nonlinear regression,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:15.119927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:29:12.327768Z digest=sha256:aa61caa40dd708fd7aa90ce868cf63c18787328ba8fcefb65549880f594f1ade

Observation 13d01ac7-3292-480e-bf1c-313a544ccbba · outbound

This paper cites Tensor Contraction Layers for Parsimo- nious Deep Nets,.

NeurOptimisation: The Spiking Way to Evolve Tensor Contraction Layers for Parsimo- nious Deep Nets,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:14.777188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:29:12.405989Z digest=sha256:6b5c0aa01e34cda4910700a64264c762db4743642cfc8abd806a39d53216ec24

Observation 0b2b3aa6-d29f-4636-8341-494d105d612f · outbound

This paper cites Neuroptimisation: The spiking way to evolve - experiment codes and dataset,.

NeurOptimisation: The Spiking Way to Evolve Neuroptimisation: The spiking way to evolve - experiment codes and dataset,

Reference 37

Resolution
verified exact
doi, observed 2026-08-06T18:29:13.000093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:29:12.489117Z digest=sha256:4564b60b5ef1027ed0d62364970a92a95471aeea88f12ac4306747978f017644

Observation 0ce65a92-612c-4534-a028-d192f6809345 · outbound

This paper cites Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions,.

NeurOptimisation: The Spiking Way to Evolve Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:14.619389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:29:12.567563Z digest=sha256:dbb51719500c5b4c2079526e1e65cb259e59d940999933ad2fd7be7fbcc25bd9

Observation 36ebe617-8b79-40aa-9c5e-408c420982f2 · outbound

This paper cites IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics.

NeurOptimisation: The Spiking Way to Evolve IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T18:29:12.636496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:12.636496Z digest=sha256:c7980049eb0215d88d7a1b3df4d3c13803cdb812e7c2f5ae7a929d7fe1cc7aa4

Observation 6ddee4e9-92b3-40a8-bc9e-e22d1992db19 · outbound

This paper cites Benchmarking the pure random search on the bbob-2009 testbed,.

NeurOptimisation: The Spiking Way to Evolve Benchmarking the pure random search on the bbob-2009 testbed,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:14.422577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:29:12.714005Z digest=sha256:4f776f16fc92b776f670d7790f4926883506beabec263383a7278912daa89804

Observation a035839e-4168-4750-8ce5-2f9eed05b4ef · outbound

This paper cites Loihi: A neuromorphic manycore processor with on-chip learning,.

NeurOptimisation: The Spiking Way to Evolve Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:29:14.250084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:29:12.816543Z digest=sha256:b967e7cb1901a55bb5b29b1091c7051267689faec5d9528b376bf9b30fc6475a

Pith citing papers

No inbound Pith citation observations are available.