Paper Citation Record · LEDGER

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs

As of 7 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2512.05906.

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

pith.paper-citation-record.v1
2512.05906 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T18:23:12.890108Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

40 of 40 outbound references displayed

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verified fuzzy0
unresolved39
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External citation measurements

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Outbound references

Observation 683da58c-e37a-4079-a408-a95b2c1acd32 · outbound

This paper cites Cambridge University Press, 2006.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Cambridge University Press, 2006

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.233569Z

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Observation 6577c55b-f6c9-4918-986f-0475593fcb14 · outbound

This paper cites Supervised learning in spiking neural networks with synaptic delay-weight plasticity.Neurocomputing, 409:103–118, 2020.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Supervised learning in spiking neural networks with synaptic delay-weight plasticity.Neurocomputing, 409:103–118, 2020

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.277773Z

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Observation b776fa08-3a05-443a-81ee-4b3f02ad8898 · outbound

This paper cites Homeostatic bidirec- tional plasticity in upbound and downbound micromodules of the olivocerebellar system.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Homeostatic bidirec- tional plasticity in upbound and downbound micromodules of the olivocerebellar system

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.380758Z

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Observation 68cdb978-8fbb-4761-bce2-418ccbb01a03 · outbound

This paper cites The Elements of Differentiable Programming.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs The Elements of Differentiable Programming

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.461381Z

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Observation 625483ed-776c-4c0c-a0d5-a33cf0a75372 · outbound

This paper cites Trick- ing ai chips into simulating the human brain: A detailed performance analysis.Neuro- computing, 598:127953, 2024.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Trick- ing ai chips into simulating the human brain: A detailed performance analysis.Neuro- computing, 598:127953, 2024

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.513551Z

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Observation 5d3fd0ca-b7de-4e63-8076-541c3f1709b6 · outbound

This paper cites A differentiable brain simulator bridging brain simulation and brain-inspired computing.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs A differentiable brain simulator bridging brain simulation and brain-inspired computing

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.581857Z

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Observation fe387d95-eec8-4532-895e-75f8a3f4cb64 · outbound

This paper cites Kadhim, Matthijs Pals, Jonas Beck, Ziwei Huang, Manuel Gloeckler, Janne K.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Kadhim, Matthijs Pals, Jonas Beck, Ziwei Huang, Manuel Gloeckler, Janne K

Reference 7

Resolution: verified exact; doi, observed 2026-08-03T18:23:23.531368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 81d6f7d7-6a67-4bf3-99f9-d65821d4c7fc · outbound

This paper cites an unresolved cited work.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.718771Z

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Observation 08612788-e4b7-4410-ab2d-af731447008e · outbound

This paper cites Saunders, Hassaan Khan, Devdhar Patel, Darpan T.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Saunders, Hassaan Khan, Devdhar Patel, Darpan T

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.796699Z

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Observation 3bfd1ae4-1b9e-41db-b119-b28c63d3e727 · outbound

This paper cites an unresolved cited work.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.856584Z

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Observation 573175fa-a3ad-42cf-990d-a27d0acaabe8 · outbound

This paper cites Nengodl: Combining deep learning and neuromorphic modelling methods.Neuroinformatics, 17(4):611–628, 2019.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Nengodl: Combining deep learning and neuromorphic modelling methods.Neuroinformatics, 17(4):611–628, 2019

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:09.919750Z

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Observation f455f23f-1b8d-49d6-8db8-65b50ebdc44f · outbound

This paper cites Muir, Felix Bauer, and Philipp Weidel.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Muir, Felix Bauer, and Philipp Weidel

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.019506Z

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Observation 502a367c-76b2-4b19-a0b6-7d9a372c10b3 · outbound

This paper cites Spikingjelly.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Spikingjelly

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.243183Z

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Observation 31f3f63a-2a72-48c5-bcd0-b59132b9b509 · outbound

This paper cites Norse - A deep learning library for spiking neural networks, January 2021.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Norse - A deep learning library for spiking neural networks, January 2021

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.313945Z

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Observation 06b53d6e-4435-4ac2-89a2-3ba8b9fbf124 · outbound

This paper cites Training Spiking Neural Networks Using Lessons From Deep Learning.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Training Spiking Neural Networks Using Lessons From Deep Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.388178Z

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Observation 3fe79449-27b4-40f5-b4f0-a1e8091db009 · outbound

This paper cites Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.458532Z

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Observation e1574b4d-dc84-493c-8004-81f05eb653c0 · outbound

This paper cites Event-based backpropagation can compute exact gradients for spiking neural networks.Scientific Reports, 11(1):12829, 2021.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Event-based backpropagation can compute exact gradients for spiking neural networks.Scientific Reports, 11(1):12829, 2021

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.606150Z

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Observation a630b0b3-8740-4255-9994-b6f16e61ae27 · outbound

This paper cites DelGrad: Exact event-based gradients for training delays and weights on spiking neuromorphic hardware.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs DelGrad: Exact event-based gradients for training delays and weights on spiking neuromorphic hardware

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.745377Z

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Observation 3c3e2332-fb88-4538-bdce-e1c8693d111f · outbound

This paper cites jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.881585Z

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Observation 8bdb876f-c01f-4831-bd42-6b2cd989a5a9 · outbound

This paper cites mlgenn: accelerating snn inference using gpu-enabled neural networks.Neuromorphic Computing and Engineering, 2(2):024002, 2022.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs mlgenn: accelerating snn inference using gpu-enabled neural networks.Neuromorphic Computing and Engineering, 2(2):024002, 2022

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.044895Z

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Observation ffe67d7c-b4ff-4538-bd2e-fc5a7c15f17b · outbound

This paper cites Cam- bridge University Press, 2009.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Cam- bridge University Press, 2009

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.121051Z

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Observation a5929ef1-f69f-4f52-9abb-5744e5ce2335 · outbound

This paper cites Arbor—a morphologically-detailed neural net- work simulation library for contemporary high-performance computing architectures.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Arbor—a morphologically-detailed neural net- work simulation library for contemporary high-performance computing architectures

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.235416Z

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Observation d1c6ab24-0fff-44fe-91b9-223a3e33b104 · outbound

This paper cites The groq software- defined scale-out tensor streaming multiprocessor: From chips-to-systems architectural overview.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs The groq software- defined scale-out tensor streaming multiprocessor: From chips-to-systems architectural overview

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.343524Z

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Observation 748d0aed-771e-405b-8ad4-119da320080c · outbound

This paper cites Eden: a high-performance, general-purpose, neuroml-based neural simula- tor.Frontiers in neuroinformatics, 16:724336, 2022.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Eden: a high-performance, general-purpose, neuroml-based neural simula- tor.Frontiers in neuroinformatics, 16:724336, 2022

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.466011Z

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Observation 9fb7736f-fbad-4e26-9de1-82017a34520e · outbound

This paper cites Efficient Event-based Delay Learning in Spiking Neural Networks.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Efficient Event-based Delay Learning in Spiking Neural Networks

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.543153Z

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Observation 10c050c4-05fc-40f9-bd5e-2e52c7eb7f55 · outbound

This paper cites MIT press, 2007.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs MIT press, 2007

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.606929Z

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Observation a50840dd-93d9-4fe4-8fa4-77009d858311 · outbound

This paper cites Gradient diffusion: Enhancing multicompartmental neuron models for gradient-based self-tuning and homeostatic control.arXiv preprint arXiv:2412.07327, 2024.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Gradient diffusion: Enhancing multicompartmental neuron models for gradient-based self-tuning and homeostatic control.arXiv preprint arXiv:2412.07327, 2024

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.712632Z

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Observation 451673fb-f362-44b7-a392-8269f1b6abb2 · outbound

This paper cites Fast and energy-efficient neuromorphic deep learning with first-spike times.Nature machine intelligence, 3(9):823–835, 2021.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Fast and energy-efficient neuromorphic deep learning with first-spike times.Nature machine intelligence, 3(9):823–835, 2021

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.787008Z

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Observation 3ba8215d-7ef0-484c-b71e-2daea50f3158 · outbound

This paper cites Nest: An environment for neural systems simulations.Forschung und wisschenschaftliches Rechnen, Beitr¨ age zum Heinz-Billing- Preis, 58:43–70, 2001.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Nest: An environment for neural systems simulations.Forschung und wisschenschaftliches Rechnen, Beitr¨ age zum Heinz-Billing- Preis, 58:43–70, 2001

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:11.893770Z

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Observation 59a4e369-e57e-474a-b909-0f69759cc96e · outbound

This paper cites Brian 2- the second coming: spiking neural network simulation in python with code generation.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Brian 2- the second coming: spiking neural network simulation in python with code generation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.002357Z

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Observation 2c0e1c9f-9bca-42fc-851c-9833bcfad795 · outbound

This paper cites Genn: a code generation framework for accelerated brain simulations.Scientific reports, 6(1):18854, 2016.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Genn: a code generation framework for accelerated brain simulations.Scientific reports, 6(1):18854, 2016

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.074736Z

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Observation 202dd50f-b885-4c3e-82e1-fec7caa29e1a · outbound

This paper cites Loss shaping enhances exact gradient learning with eventprop in spiking neural networks.Neuromorphic Computing and Engineering, 5(1):014001, 2025.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Loss shaping enhances exact gradient learning with eventprop in spiking neural networks.Neuromorphic Computing and Engineering, 5(1):014001, 2025

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.209023Z

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Observation d286dcbf-1012-4008-95a0-6ee01d4ec7f3 · outbound

This paper cites Fast simulations of highly-connected spiking cortical models using gpus.Frontiers in Computational Neuroscience, 15:627620, 2021.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Fast simulations of highly-connected spiking cortical models using gpus.Frontiers in Computational Neuroscience, 15:627620, 2021

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.305280Z

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Observation c34d8a88-b991-48b1-b7da-20e944a87c3a · outbound

This paper cites A proof of a key formula in the error- backpropagation learning algorithm for multiple spiking neural networks.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs A proof of a key formula in the error- backpropagation learning algorithm for multiple spiking neural networks

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.450200Z

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Observation 8b02ff34-8d0b-474a-aa49-0ed4f6832cb3 · outbound

This paper cites Bgpq: A heap-based priority queue design for gpus.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Bgpq: A heap-based priority queue design for gpus

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.581246Z

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Observation 08dcadbb-352c-4826-94c6-742a810838ba · outbound

This paper cites Tpu v4: An optically reconfigurable supercomputer for machine learning with hardware support for embeddings.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Tpu v4: An optically reconfigurable supercomputer for machine learning with hardware support for embeddings

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.651237Z

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Observation 770c3cb1-ba04-42fb-8722-443ec861b408 · outbound

This paper cites Think fast: A tensor streaming processor (tsp) for accelerating deep learning workloads.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Think fast: A tensor streaming processor (tsp) for accelerating deep learning workloads

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.748232Z

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Observation 3a164481-6655-43df-96b4-8a8c91c90141 · outbound

This paper cites Huma: Hetero- geneous, ultra low-latency model accelerator for the virtual brain on a versal adaptive soc.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Huma: Hetero- geneous, ultra low-latency model accelerator for the virtual brain on a versal adaptive soc

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.830641Z

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Observation 35dfc3a7-f3ba-4f18-a32b-d6e9d8beb485 · outbound

This paper cites Efficient and realistic brain simulation: A review and design guide for memristor-based approaches.Advanced Materials Tech- nologies, page e01587, 2025.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Efficient and realistic brain simulation: A review and design guide for memristor-based approaches.Advanced Materials Tech- nologies, page e01587, 2025

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:12.890108Z

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Observation c0362f53-16dd-4abd-b9ea-34d9aaf024f8 · outbound

This paper cites an unresolved cited work.

ADSEQ: A delay-aware autograd-compatible framework for spike-event delivery in SNNs Unresolved cited work

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-03T18:23:10.125855Z

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Pith citing papers

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