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Paper Citation Record · LEDGER

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks

As of 18 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2505.12292.

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

pith.paper-citation-record.v1
2505.12292 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:43:26.054845Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

53 of 53 outbound references displayed

  • verified exact2
  • verified fuzzy34
  • unresolved14
  • parse uncertain0
  • malformed identifier3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 15d6057f-ec32-4653-b8cc-c5edca5e19e8 · outbound

This paper cites Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7f8a52d4-7833-4ee1-9658-d4a5e3f9467a · outbound

This paper cites A low power, fully event-based gesture recognition system,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks A low power, fully event-based gesture recognition system,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a3096bbd-0c3e-4286-89d2-ad65cb71ea18 · outbound

This paper cites A low power, fully event-based gesture recognition system,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks A low power, fully event-based gesture recognition system,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 1b41b68f-5a6b-4655-b2e9-c8eeee5ab1fe · outbound

This paper cites Hard- ware/software co-design with adc-less in-memory computing hardware for spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Hard- ware/software co-design with adc-less in-memory computing hardware for spiking neural networks,

Reference 5

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raw_fallback, observed 2026-08-15T20:43:28.120942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 967a8740-1768-4d6e-84b7-7c75fdbd665e · outbound

This paper cites Are snns truly energy-efficient?—a hardware perspective,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Are snns truly energy-efficient?—a hardware perspective,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.958259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.149823Z digest=sha256:123be17525af46994611d2286925d01777609738c5085ec396b2cb4adadae003

Observation f803fabf-d005-46eb-8e6e-d4b3807ac418 · outbound

This paper cites Efficient biologically-plausible training of spiking neural networks with precise timing,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Efficient biologically-plausible training of spiking neural networks with precise timing,

Reference 7

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raw_fallback, observed 2026-08-15T20:43:27.947605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 51f4a5b4-eba6-425b-bb4b-ef0606ce35ab · outbound

This paper cites Comparison of classifier methods: a case study in handwritten digit recognition,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Comparison of classifier methods: a case study in handwritten digit recognition,

Reference 8

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raw_fallback, observed 2026-08-15T20:43:27.934352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f01f2aae-fdee-4693-b8ec-00f3d4bbea4a · outbound

This paper cites Eyeriss: An energy- efficient reconfigurable accelerator for deep convolutional neural net- works,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Eyeriss: An energy- efficient reconfigurable accelerator for deep convolutional neural net- works,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e6bd069e-e7b0-4970-8ee9-7248e0ccdbca · outbound

This paper cites Taking neuromorphic computing to the next level with loihi 2,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Taking neuromorphic computing to the next level with loihi 2,

Reference 10

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raw_fallback, observed 2026-08-15T20:43:27.764480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation cc930a45-3bf2-4ce9-b736-15bfd90341e9 · outbound

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

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.691635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b309531f-051b-460a-afe5-c19ad14f4f14 · outbound

This paper cites A large-scale model of the functioning brain,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks A large-scale model of the functioning brain,

Reference 12

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no resolver link, observed 2026-08-15T20:43:25.293410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.293410Z digest=sha256:db8b53d83c2370953f2842a5c5d82f14deacffc1cd6a057787fc74c5190c162f

Observation f906718f-b981-4430-b91b-8eaeb34f826a · outbound

This paper cites Neural architecture search: A survey,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Neural architecture search: A survey,

Reference 13

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no resolver link, observed 2026-08-15T20:43:25.301002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.301002Z digest=sha256:121d5490f2dfb0785960802b389fb0480f84e92ea8e8dc8f484b59cb82bb3253

Observation afec5264-abf5-4739-8757-5afc6ea30d83 · outbound

This paper cites Audio and image cross-modal intelligence via a 10tops/w 22nm soc with back-propagation and dynamic power gating,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Audio and image cross-modal intelligence via a 10tops/w 22nm soc with back-propagation and dynamic power gating,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.666391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.305229Z digest=sha256:f53cb688a819f044a58d8bdb5c173f82aec9c3f8a5e6d7a38c5eab61e737edc3

Observation fffd024d-d6af-4cc0-89be-5e62a3be303e · outbound

This paper cites Aimmi: Audio and image multi-modal intelligence via a low-power soc with 2-mbyte on- chip mram for iot devices,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Aimmi: Audio and image multi-modal intelligence via a low-power soc with 2-mbyte on- chip mram for iot devices,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.656026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 17228c92-3c50-4937-8cd8-f5f5d24de167 · outbound

This paper cites Sparse coding,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Sparse coding,

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.644955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 10fdbc4f-875a-46cd-9bcf-15438c72ded0 · outbound

This paper cites The spinnaker project,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks The spinnaker project,

Reference 17

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raw_fallback, observed 2026-08-15T20:43:27.635246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5640cb90-8b79-499d-88ac-5f93ef549c36 · outbound

This paper cites The spinnaker project,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks The spinnaker project,

Reference 18

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no resolver link, observed 2026-08-15T20:43:25.321765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 028cfa3d-e80a-42e9-a39b-b66cc09582f9 · outbound

This paper cites Highly efficient neuromorphic learning system of spiking neural network with multi-compartment leaky integrate-and-fire neurons,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Highly efficient neuromorphic learning system of spiking neural network with multi-compartment leaky integrate-and-fire neurons,

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.615033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 483eea61-9f19-4bf4-b6f6-3405ff763d43 · outbound

This paper cites A survey of fpga-based neural network accelerator,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks A survey of fpga-based neural network accelerator,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.552978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.507721Z digest=sha256:024620381af5e4a154270aa8055fccc001df470bdec1027572ffbb8001ed4442

Observation 88e8846d-fa26-4fa1-825a-930e33275256 · outbound

This paper cites A quantitative description of membrane current and its application to conduction and excitation in nerve,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks A quantitative description of membrane current and its application to conduction and excitation in nerve,

Reference 21

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no resolver link, observed 2026-08-15T20:43:25.550534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.550534Z digest=sha256:87cb99ce0ab52a3707374a8348876aabcd7a55ba613ac5e8ae605a4f0e5ff1d8

Observation 0563e945-d259-4411-9e0d-8a9557af1415 · outbound

This paper cites Hybrid macro/micro level backpropagation for training deep spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Hybrid macro/micro level backpropagation for training deep spiking neural networks,

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.425456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5b450f61-63a6-4a6a-b816-337876b8c13e · outbound

This paper cites In-datacenter performance analysis of a tensor processing unit,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks In-datacenter performance analysis of a tensor processing unit,

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6d5c9b5c-90f9-4519-bf3c-a44651cc2a55 · outbound

This paper cites Understanding reuse, performance, and hardware cost of dnn dataflow: A data-centric approach,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Understanding reuse, performance, and hardware cost of dnn dataflow: A data-centric approach,

Reference 24

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unresolved
no resolver link, observed 2026-08-15T20:43:25.587324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.587324Z digest=sha256:a884ebfb121c93cfcdef4c61c3a42772c598100d3a914d2c2d8c267e27b0c456

Observation 96ade45c-8b7c-411a-92bd-e42864f2fcbb · outbound

This paper cites Reconfigurable dataflow optimization for spatiotem- poral spiking neural computation on systolic array accelerators,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Reconfigurable dataflow optimization for spatiotem- poral spiking neural computation on systolic array accelerators,

Reference 25

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unresolved
no resolver link, observed 2026-08-15T20:43:25.590456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.590456Z digest=sha256:ac0db3a3601d637f81492672ecd074634be7403f26b9856723cededee75903cb

Observation 37b965d5-20df-47ba-845f-5980273cf56f · outbound

This paper cites Parallel time batching: Systolic-array acceleration of sparse spiking neural computation,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Parallel time batching: Systolic-array acceleration of sparse spiking neural computation,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.395429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 917d8de1-51f7-4275-a080-63c277bebfa2 · outbound

This paper cites Cifar10-dvs: An event-stream dataset for object classification,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Cifar10-dvs: An event-stream dataset for object classification,

Reference 27

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unresolved
no resolver link, observed 2026-08-15T20:43:25.598894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.598894Z digest=sha256:bb2278c006528627f0a2df6487b3d46671e1240da675f676daaed045cd634ad7

Observation 5e383068-6501-4673-91b7-327701de206a · outbound

This paper cites H2learn: High-efficiency learning accelerator for high-accuracy spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks H2learn: High-efficiency learning accelerator for high-accuracy spiking neural networks,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.377741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.605815Z digest=sha256:55f1ea220f19b354cb11f29ee338efad94092f5e603e35b98ecc237582faf38e

Observation 98455a6d-bc34-4ee7-82f6-d737512230a5 · outbound

This paper cites Sparse compressed spiking neural network accelerator for object detection,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Sparse compressed spiking neural network accelerator for object detection,

Reference 29

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malformed identifier
no resolver link, observed 2026-08-15T20:43:25.609868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.609868Z digest=sha256:b1bb2bba25aa29b0928d5d7c01a9b115a81a621a7b100e95e632148888b234ba

Observation f97e4466-1baa-486c-b27d-a8b38159d02d · outbound

This paper cites Networks of spiking neurons: The third generation of neural network models,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Networks of spiking neurons: The third generation of neural network models,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.366064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.613863Z digest=sha256:51c6cd679e37b26025668f38122470c807f77894098b127e6217f453fd44d358

Observation 2eddbe42-62cc-4abd-a44b-662ef3168a6e · outbound

This paper cites SpiNNaker 2: A 10 Million Core Processor System for Brain Simulation and Machine Learning.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks SpiNNaker 2: A 10 Million Core Processor System for Brain Simulation and Machine Learning

Reference 31

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no resolver link, observed 2026-08-15T20:43:25.711003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6e392ced-f7e6-4e2c-a619-61bd539023ca · outbound

This paper cites Cacti 6.0: A tool to model large caches,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Cacti 6.0: A tool to model large caches,

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.312767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.795931Z digest=sha256:796cd779efd256e22c8f6e4e68bec03f2fe726523e08c03cb25e364a356216e2

Observation a3d49c80-c6c3-4ad8-b606-ef0e1100e0ff · outbound

This paper cites Spinalflow: An architecture and dataflow tailored for spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Spinalflow: An architecture and dataflow tailored for spiking neural networks,

Reference 33

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no resolver link, observed 2026-08-15T20:43:25.819751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.819751Z digest=sha256:53fbcc83044cd386e22c51273ede7da66bdc3ee6cc9c0528cbd70299d6d42049

Observation e9ea37eb-69ab-47a6-a9e7-777f90df1e46 · outbound

This paper cites Converting static image datasets to spiking neuromorphic datasets using saccades,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Converting static image datasets to spiking neuromorphic datasets using saccades,

Reference 34

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no resolver link, observed 2026-08-15T20:43:25.832428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.832428Z digest=sha256:0a82e536eb30194d1c8aa221826b71cd45280b1a3f485afe05b007d909e25822

Observation 910ae573-ef2f-44a0-b0cc-f904cc802326 · outbound

This paper cites Spinnaker: A 1-w 18-core system-on-chip for massively-parallel neural network simulation,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Spinnaker: A 1-w 18-core system-on-chip for massively-parallel neural network simulation,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.196354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.836867Z digest=sha256:ec63023e1f3aa7a9001c92259868b2a74114bc408fd72fcd583965d4894b972a

Observation 23eb0063-19d0-4f1d-b7fb-60d4443b839b · outbound

This paper cites Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:43:26.145906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.841245Z digest=sha256:ce0197e15973d553e22f4b870a9c155b31ff285618f1a25b7b881c4ff89d550e

Observation 5414afc8-bece-4dae-9a6c-af5d71b704ac · outbound

This paper cites Scale- sim: Systolic cnn accelerator,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Scale- sim: Systolic cnn accelerator,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.150787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.845692Z digest=sha256:296174c0ca2cf08fdc2290c8571de0e5003eff92be26b4a769cea4afd8d71047

Observation 8851d5fe-8967-4087-8d4e-e3c715739cd1 · outbound

This paper cites SLAYER: Spike Layer Error Reassignment in Time.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks SLAYER: Spike Layer Error Reassignment in Time

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T20:43:25.848709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.848709Z digest=sha256:a01887a8b06fb168cafa2cd5b0c496dd0cd186697fc2761c9d84f01dd8d7413e

Observation 425c36e0-c64e-4ddb-afcf-880c26325ecf · outbound

This paper cites Deep learning in spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Deep learning in spiking neural networks,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.139818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.852736Z digest=sha256:79d55e9a98f7bc57290311a360990a95e86b8a3240f54bba77adb10b475389a3

Observation 2ad3f946-8e0b-4384-bfbf-ec67b1808e9b · outbound

This paper cites Sies: A novel implementation of spiking convolutional neural network inference engine on field-programmable gate array,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Sies: A novel implementation of spiking convolutional neural network inference engine on field-programmable gate array,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.117111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.856352Z digest=sha256:c3c786cd139e02b60e744bbbfcfebadeb9009f34ca3c7400073dbf8db37f3b9a

Observation 5f499132-b400-41c5-9a72-16b55d987805 · outbound

This paper cites Compsnn: A lightweight spiking neural network based on spatiotemporally compressive spike features,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Compsnn: A lightweight spiking neural network based on spatiotemporally compressive spike features,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.010222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.860034Z digest=sha256:6d5d03692b17c851e7444183c03860da16be3182ee193cb8b8b4fef0ccf6c402

Observation 44137f63-3935-4626-8447-11ab85be0b4d · outbound

This paper cites Spiking Transformer Hardware Accelerators in 3D Integration.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Spiking Transformer Hardware Accelerators in 3D Integration

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T20:43:25.863110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.863110Z digest=sha256:eb2ef9daf3fbad0618e9594932425ac0a8c4827d2f535e62fa23dd2415431902

Observation 8aa85490-e6c9-4ede-adb9-6bb8a5c07066 · outbound

This paper cites Towards 3D Acceleration for low-power Mixture-of-Experts and Multi-Head Attention Spiking Transformers.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Towards 3D Acceleration for low-power Mixture-of-Experts and Multi-Head Attention Spiking Transformers

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T20:43:25.901211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.901211Z digest=sha256:79122875b3cfcc27927935540164907fb5ad085594785e3deba2039982e17d20

Observation b173eae0-0614-497f-9179-fd7e815aedde · outbound

This paper cites Trimming Down Large Spiking Vision Transformers via Heterogeneous Quantization Search.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Trimming Down Large Spiking Vision Transformers via Heterogeneous Quantization Search

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:43:26.100119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.940678Z digest=sha256:588d8eb3c2eb50b074da216d2dff1b741c3ed586d198a17be1472f7bb87922c2

Observation 20c5c2f3-a060-428f-a02a-cf6f92ed53b0 · outbound

This paper cites Workload-balanced pruning for sparse spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Workload-balanced pruning for sparse spiking neural networks,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:26.946969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:26.004443Z digest=sha256:b718595afed2a5ac0556470dc9b90c77aba8b1937b2fe038c7c98eafdd25cf59

Observation 8857b105-e914-47c4-b6ec-b2ed8998cffc · outbound

This paper cites Mint: Multiplier-less integer quantization for energy efficient spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Mint: Multiplier-less integer quantization for energy efficient spiking neural networks,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:26.936627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:26.023169Z digest=sha256:bece5af8f93e4a08b0a0847f190e07a3efd637d5f0cb23aa0afb10d29715ef01

Observation 6e892d05-8784-47a7-82c1-5997801e5e4f · outbound

This paper cites Sata: Sparsity-aware training accelerator for spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Sata: Sparsity-aware training accelerator for spiking neural networks,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:26.924093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:26.035562Z digest=sha256:c88d37e90aa8a8447e08aad9b891f7b93c65b786fb6eb569370a30db4a7010dc

Observation bc94e5f4-1151-4265-a15a-ee1434910f2a · outbound

This paper cites Gpu-based simulation of spiking neural networks with real-time performance & high accuracy,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Gpu-based simulation of spiking neural networks with real-time performance & high accuracy,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:26.906790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:26.044668Z digest=sha256:fecca7b9d1b53a5e114ec4bac42a99e7c80182e3fb9b30a8bb3f32029a7dcb00

Observation 5682c1f0-059a-4288-b662-96d78aa7e9f8 · outbound

This paper cites Spike-train level backpropagation for training deep recurrent spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Spike-train level backpropagation for training deep recurrent spiking neural networks,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:26.873653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:26.048299Z digest=sha256:739805bb11b04baf2f2d4c310cb7542e96a0a9b5b5b9cc8d0ae5c8c3e48a3c9a

Observation f6748b35-6805-4acd-8336-62f25142d579 · outbound

This paper cites Temporal spike sequence learning via backpropagation for deep spiking neural networks,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Temporal spike sequence learning via backpropagation for deep spiking neural networks,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:26.728893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:26.051825Z digest=sha256:77ac0d1114d75a014b1c5b03350e2aebdd3c513fc0ad446dc252dd4dd5278f33

Observation a0f29458-ca84-42c1-8c79-d6dfc1665f40 · outbound

This paper cites A digital liquid state machine with biologically inspired learning and its application to speech recognition,.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks A digital liquid state machine with biologically inspired learning and its application to speech recognition,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:26.708192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:26.054845Z digest=sha256:3a43302183749c460a5c129a662e6bf585e0e2d22b832c04395c13f429ab9d1d

Observation 3ed6cd85-4e03-4b43-a598-92a23aa1f08a · outbound

This paper cites Available: https://www.sciencedirect.com/science/article/ pii/S0893608097000117 13.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Available: https://www.sciencedirect.com/science/article/ pii/S0893608097000117 13

Reference 1997

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:43:27.346772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.642103Z digest=sha256:b9afb3603c17c8c86d22c789ca66b2cbbd09785f8d4196e18e68888496f40657

Observation 864cc58b-bf7f-4928-998b-a1ecfc4c12cf · outbound

This paper cites Available: https://www.frontiersin.org/articles/10.3389/ fnins.2017.00309.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Available: https://www.frontiersin.org/articles/10.3389/ fnins.2017.00309

Reference 2017

Resolution
malformed identifier
no resolver link, observed 2026-08-15T20:43:25.602781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:25.602781Z digest=sha256:d9eb5f2840e50c83b9e4026259f98fa862e9dd483500651c4ea00de894fb4433

Observation 3ffb8db4-a008-49b3-89fd-d6e88e503c37 · outbound

This paper cites Available: https://www.frontiersin.org/articles/10.3389/ fnins.2022.929644.

SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks Available: https://www.frontiersin.org/articles/10.3389/ fnins.2022.929644

Reference 2022

Resolution
malformed identifier
raw_fallback, observed 2026-08-15T20:43:26.650261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:43:25.433875Z digest=sha256:ed5bee6f4940590b45ee55615fb7e553cda6cf6c1eeb093c7309ac6ce5dc7812

Pith citing papers

No inbound Pith citation observations are available.