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Paper Citation Record · LEDGER

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks

As of 21 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2508.16216.

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

pith.paper-citation-record.v1
2508.16216 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:30:26.522441Z

measured 38 of 38 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 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

38 of 38 outbound references displayed

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  • verified fuzzy0
  • unresolved18
  • parse uncertain0
  • malformed identifier1
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External citation measurements

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Outbound references

Observation d9cabca7-71d0-4670-8bfe-4b9d0635cb1a · outbound

This paper cites Bi, M.-m.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Bi, M.-m

Reference 1

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Observation 3e58afeb-837b-4bb4-95f6-b39cbc1ee4a2 · outbound

This paper cites Markram, J.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Markram, J

Reference 2

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Observation 0621af76-d42f-4a81-aef8-0f70367388e0 · outbound

This paper cites Bi, M.-M.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Bi, M.-M

Reference 3

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Observation 33c591aa-afa4-4ac4-90ff-50e43c5ad00a · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 4

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Observation c9811a49-97cd-4441-923b-b1d5f98c00ff · outbound

This paper cites Masquelier, S.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Masquelier, S

Reference 5

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Observation d0ae40c9-96e4-4050-a980-e7dfaa687ca8 · outbound

This paper cites Ferr \'e , F.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Ferr \'e , F

Reference 6

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Observation cf0f462f-0247-4210-a26f-919f5a3d0af1 · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 7

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Observation 970a06e9-3564-4823-b51c-5760461f3116 · outbound

This paper cites A change of direction in pairwise neutrino conversion physics: The effect of collisions.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks A change of direction in pairwise neutrino conversion physics: The effect of collisions

Reference 8

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Observation 50511051-da3e-4675-bf6c-eb32aab20d5b · outbound

This paper cites Phase Transition Between Flat Space Cosmology and Hot Flat Spacetimes in GMMG and EGMG Models.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Phase Transition Between Flat Space Cosmology and Hot Flat Spacetimes in GMMG and EGMG Models

Reference 9

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Observation 90667224-a8e6-4405-a943-c44f9989526e · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 10

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Observation 3e33aeb0-02cd-49a3-9282-47106bb6a018 · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 11

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Observation d03db614-bf06-417b-88fa-83d78d257c40 · outbound

This paper cites Foncelle, A.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Foncelle, A

Reference 12

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Observation 6572df41-5934-4435-9d06-0e8dd6e6cc5e · outbound

This paper cites Clopath, L.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Clopath, L

Reference 13

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Observation b10ea154-75b1-4bff-b6c1-3c1919cc0f28 · outbound

This paper cites Pfister, W.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Pfister, W

Reference 14

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Observation 7e9e7701-d933-4f57-809d-f0143a1b5671 · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 15

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Observation 463ed887-e3c1-4fd5-99a9-6495f2c621bb · outbound

This paper cites Oja, A simplified neuron model as a principal component analyzer, Journal of mathematical biology 15 (3) (1982) 267--273.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Oja, A simplified neuron model as a principal component analyzer, Journal of mathematical biology 15 (3) (1982) 267--273

Reference 16

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Observation 8ecd579f-1fdb-4d8f-b9eb-451d78215cd8 · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 17

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Observation f27b1502-9749-4186-935a-f67a7bf2e20d · outbound

This paper cites Gerstner, W.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Gerstner, W

Reference 18

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Observation 91174fdc-1dfe-42dd-8a97-e52e242559bc · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 19

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Observation 63b980ab-4496-4f66-812a-da66c786eac5 · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 20

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

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Observation c4578c1c-4c1e-4e53-bffc-8d7ef3580594 · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 21

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Observation 640db858-02fc-4d1d-9fbd-465cf57d7249 · outbound

This paper cites Causal Spike Timing Dependent Plasticity Prevents Assembly Fusion in Recurrent Networks.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Causal Spike Timing Dependent Plasticity Prevents Assembly Fusion in Recurrent Networks

Reference 22

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Observation 5d4ce9d5-7918-4179-96d7-44ad9b9630ef · outbound

This paper cites Chawla, E.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Chawla, E

Reference 23

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Observation 6b0c5755-c2f2-46a7-92e1-e04303a6af73 · outbound

This paper cites Nessler, M.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Nessler, M

Reference 24

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Observation 2e628b6b-ecc2-4b0d-a159-a2fcc97712c8 · outbound

This paper cites Habenschuss, H.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Habenschuss, H

Reference 25

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

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Observation f030bd5a-eb87-46a2-82ff-e595c7ab2a8f · outbound

This paper cites Sagar, K.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Sagar, K

Reference 26

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

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Observation d7a730dc-32e2-4349-b52a-d34ce256dc2d · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 27

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Observation 5e62d474-60f1-41de-ba45-0fcc50b001fc · outbound

This paper cites Mukherjee, et al., Superionic rubidium silver iodide gated low voltage synaptic transistor https://doi.org/10.1063/5.0069478, Applied Physics Letters 119 (25) (2021) 253502.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Mukherjee, et al., Superionic rubidium silver iodide gated low voltage synaptic transistor https://doi.org/10.1063/5.0069478, Applied Physics Letters 119 (25) (2021) 253502

Reference 28

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Observation 7e011ceb-bbce-49b1-b4b3-cf600d93602b · outbound

This paper cites Sagar, A.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Sagar, A

Reference 29

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

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Observation 42c1b6d8-8670-4472-a8fe-29e966e60b80 · outbound

This paper cites van de Burgt, A.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks van de Burgt, A

Reference 30

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Observation d7595830-727c-40fa-af57-a2aed2bafc65 · outbound

This paper cites Hazan, D.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Hazan, D

Reference 31

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Observation 9e80d6b7-2fe9-4ce9-9e03-26ff9afe689c · outbound

This paper cites Davies, N.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Davies, N

Reference 32

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Observation 7f9d765f-62a4-4d40-abc7-275182258353 · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 33

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Observation 4178c14f-c809-4598-9abf-5cb1a42fb5bb · outbound

This paper cites Morrison, M.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Morrison, M

Reference 34

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Observation 57b521d6-8b3a-441c-ace8-d137a5032b69 · outbound

This paper cites Stimberg, R.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Stimberg, R

Reference 35

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Observation 0ff3545e-f87c-4f05-b585-963c77bbb632 · outbound

This paper cites Fermions and baryons as open-string states from brane junctions.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Fermions and baryons as open-string states from brane junctions

Reference 36

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source=arxiv_source observed=2026-08-05T17:30:26.514749Z digest=sha256:bb357f9efae515626c80893fccadc5904743eb90c74507a96c92133935b58850

Observation 5508a53a-cffe-40fd-a1d7-aa64919386ed · outbound

This paper cites Linsker, From basic network principles to neural architecture: Emergence of orientation columns, Proceedings of the National Academy of Sciences 83 (21) (1986) 8779--8783.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Linsker, From basic network principles to neural architecture: Emergence of orientation columns, Proceedings of the National Academy of Sciences 83 (21) (1986) 8779--8783

Reference 37

Resolution
verified exact
doi, observed 2026-08-05T17:30:26.564855Z

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=arxiv_source observed=2026-08-05T17:30:26.518523Z digest=sha256:20b21b04c1ecbcb7f259a51f1504d76874792513b59b22c69b82587b635ba14a

Observation b3d59636-a698-4a7e-9f38-ba0792694d5f · outbound

This paper cites an unresolved cited work.

Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks Unresolved cited work

Reference 38

Resolution
verified exact
doi, observed 2026-08-05T17:30:26.553326Z

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=arxiv_source observed=2026-08-05T17:30:26.522441Z digest=sha256:d7ee9be8fa5defb835b1560e3a5a9d13882def298875f53a6cd03cf055ae0b43

Pith citing papers

No inbound Pith citation observations are available.