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Paper Citation Record · LEDGER

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores

As of 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.22790.

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

pith.paper-citation-record.v1
2607.22790 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T05:19:34.555832Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

24 of 24 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ad60825-9566-4d55-a067-d6fff0cbd817 · outbound

This paper cites Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration,

Reference 1

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source=pdf_text observed=2026-08-01T05:19:31.919448Z digest=sha256:39be1eb9b8f9defd3127de38bf91f5c60e8c556241ad05a0a03d71ccbc2ff7ed

Observation 1ea91ca2-3377-4766-a852-d2c9b28c8b9f · outbound

This paper cites µbrain: An event-driven and fully synthesizable architecture for spiking neural networks,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores µbrain: An event-driven and fully synthesizable architecture for spiking neural networks,

Reference 2

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source=pdf_text observed=2026-08-01T05:19:32.056720Z digest=sha256:cce4c865a6fa5106e22c64c35c6df2f3ea80ea0d18a2297c5ec9641e8e8338c6

Observation 98a3d049-85d8-4788-a5c1-e819684bfdce · outbound

This paper cites Neuron- flow: a neuromorphic processor architecture for live ai applications,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Neuron- flow: a neuromorphic processor architecture for live ai applications,

Reference 3

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source=pdf_text observed=2026-08-01T05:19:32.160897Z digest=sha256:2e6e911f648216b55a3ebdcb6d032a34ba2fef1b810878f5f2cb3b8829c0a8f9

Observation f4d0397a-9eb0-42d1-9143-cbb2a401508b · outbound

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

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 4

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source=pdf_text observed=2026-08-01T05:19:32.322004Z digest=sha256:6c62fbc154a623e21ea8c7fbe63123dc11773cdcf0688ff47c99d8f76eefc63e

Observation 05bdc0f9-d470-4bbc-8dec-4eaa29c17d9b · outbound

This paper cites Hybrid neural network, an efficient low- power digital hardware implementation of event-based artificial neural network,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Hybrid neural network, an efficient low- power digital hardware implementation of event-based artificial neural network,

Reference 5

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source=pdf_text observed=2026-08-01T05:19:32.428787Z digest=sha256:6207842e33f82c5e59b567b57c5d567bcdc4ab2357cc98700289c367cea2cab6

Observation dc9f8a1e-95e2-4680-b65f-fe43538bac1a · outbound

This paper cites Performance comparison of time- step-driven versus event-driven neural state update approaches in spin- naker,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Performance comparison of time- step-driven versus event-driven neural state update approaches in spin- naker,

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T05:19:32.511638Z digest=sha256:2fac1749a683e7769189704e509a3e9ae2cc2519751b520c8a53b3f4f55b6d61

Observation b35c0c03-9bff-441b-bd59-7dad5a0da17f · outbound

This paper cites Efficient neuromorphic signal processing with loihi 2,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Efficient neuromorphic signal processing with loihi 2,

Reference 7

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source=pdf_text observed=2026-08-01T05:19:32.574749Z digest=sha256:56d6017b2dc40457117bb484b2104174e8ebadf2ceb28768a5eca9e5d76a08c1

Observation 5d872f14-e0d5-46b4-95f6-ed36c179fccd · outbound

This paper cites The State of Sparsity in Deep Neural Networks.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores The State of Sparsity in Deep Neural Networks

Reference 8

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source=pdf_text observed=2026-08-01T05:19:32.695733Z digest=sha256:1877335d64f6f1e11cb0e11f877750a86a4ef111f4d0941b52304f769b221997

Observation 6dcc427f-e547-45c9-b3a7-ae6c378f5a77 · outbound

This paper cites Eie: Efficient inference engine on compressed deep neural network,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Eie: Efficient inference engine on compressed deep neural network,

Reference 9

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source=pdf_text observed=2026-08-01T05:19:32.827846Z digest=sha256:f217246cfd0109aa7369b36ffb7a697ff75006ddc99fd92228d798ed50d9781d

Observation 839646c5-4995-492b-9400-88ad0a09985e · outbound

This paper cites Cambricon-s: Addressing irregularity in sparse neural networks through a cooperative software/hardware approach,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Cambricon-s: Addressing irregularity in sparse neural networks through a cooperative software/hardware approach,

Reference 10

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source=pdf_text observed=2026-08-01T05:19:32.959581Z digest=sha256:a09465e7f0f3dcffad0ebf95a9ae71ccdbb27bf0fafc38a81d8588044e15f923

Observation 42bd6df3-2c7b-49fa-be4a-7de9cc185bde · outbound

This paper cites Scnn: An accelerator for compressed-sparse convolutional neural networks,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Scnn: An accelerator for compressed-sparse convolutional neural networks,

Reference 11

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source=pdf_text observed=2026-08-01T05:19:33.119449Z digest=sha256:509c95624730f965aa6c70b6be6da47422099825386bcedea81dcc9d3e4bfac1

Observation f07e6afd-01d3-48c2-a36c-1f99a5c9b7c6 · outbound

This paper cites Seneca: building a fully digital neuromorphic processor, design trade-offs and challenges,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Seneca: building a fully digital neuromorphic processor, design trade-offs and challenges,

Reference 12

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source=pdf_text observed=2026-08-01T05:19:33.222043Z digest=sha256:a684db7d9bd23c69f2cf8b0b749ded99f3f28b2bfe21612d2ab92f17e363109f

Observation 494509ec-a0c6-461c-854f-686625c59921 · outbound

This paper cites SpiNNaker2: A Large-Scale Neuromorphic System for Event-Based and Asynchronous Machine Learning.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores SpiNNaker2: A Large-Scale Neuromorphic System for Event-Based and Asynchronous Machine Learning

Reference 13

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source=pdf_text observed=2026-08-01T05:19:33.345427Z digest=sha256:a387cdd0a326a2dcedf83f7fce65562ab3a1635330d9b52990ef09e99621acd7

Observation b6101c0b-9d3f-4f73-93ae-fee6b57275aa · outbound

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

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Spinalflow: An architecture and dataflow tailored for spiking neural networks,

Reference 14

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source=pdf_text observed=2026-08-01T05:19:33.490852Z digest=sha256:3c5a0465363133f5fb81f6ade4b122c6701378c3d6623643e1ac4ce2806dcf5c

Observation b46252c2-1848-4c1a-96eb-ebc479f12425 · outbound

This paper cites Vsa: Reconfigurable vector- wise spiking neural network accelerator,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Vsa: Reconfigurable vector- wise spiking neural network accelerator,

Reference 15

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source=pdf_text observed=2026-08-01T05:19:33.652612Z digest=sha256:1cb223158dc7e411c0bbfc3f68a45b10c5cc8654a2a2178191f823c467d247b4

Observation 64882e97-86e1-45bc-af5f-e7b19e8c112f · outbound

This paper cites Spare: Spiking neural network acceleration using rom-embedded rams as in-memory-computation prim- itives,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Spare: Spiking neural network acceleration using rom-embedded rams as in-memory-computation prim- itives,

Reference 16

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source=pdf_text observed=2026-08-01T05:19:33.760870Z digest=sha256:5d1bb129fc225173e68ca3be68af717c829f1dc2d9067616e2a2905b43c1433c

Observation fc1bb71c-5704-4802-9fcd-0ff60ca241bc · outbound

This paper cites Spiking transformer hardware accelerators in 3d integration,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Spiking transformer hardware accelerators in 3d integration,

Reference 17

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source=pdf_text observed=2026-08-01T05:19:33.929686Z digest=sha256:6e2908f237c3f7e9ac311fbfccf0dad11e58050ad397095a9a6c147cc0877494

Observation dd2e4c22-7a51-4002-8c12-0e8f61ebefb2 · outbound

This paper cites Prune Once for All: Sparse Pre-Trained Language Models.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Prune Once for All: Sparse Pre-Trained Language Models

Reference 18

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source=pdf_text observed=2026-08-01T05:19:34.039471Z digest=sha256:31de1a0b0c0b2d1c59f2927fd4e6ea368ee8c5173a2abb8498f30a2f3db0e6ae

Observation beed8e1f-a003-4865-b881-5fc1daea44c8 · outbound

This paper cites Neorv32.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Neorv32

Reference 19

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source=pdf_text observed=2026-08-01T05:19:34.166053Z digest=sha256:69604226173c304a7ff7e0bdf88e92fc89b9d5e61d836bc97a7873c473c63cd0

Observation e12d1b36-4dbf-45c3-a3a3-9073b4087e2a · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 20

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source=pdf_text observed=2026-08-01T05:19:34.318159Z digest=sha256:4ffc0f08a5eee438da11b427420a0618dafebfec9b92255b9afb95662cf31251

Observation f85bddca-eb0e-410f-a273-6d33dcb760ce · outbound

This paper cites Learning multiple layers of features from tiny images,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Learning multiple layers of features from tiny images,

Reference 21

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source=pdf_text observed=2026-08-01T05:19:34.368464Z digest=sha256:23846a885e10d85a19bb9ecf38490f38581af8ae0c3f932a4e5eea695a54e085

Observation d873da81-f98d-4f1e-8574-5250e5317586 · outbound

This paper cites A comprehensive review of network pruning based on pruning granularity and pruning time perspectives,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores A comprehensive review of network pruning based on pruning granularity and pruning time perspectives,

Reference 22

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source=pdf_text observed=2026-08-01T05:19:34.412447Z digest=sha256:cd704e3fcb9f77fd693e57db8dda58f52b0d11223cbb9f5d4b757d435671d51b

Observation b4682173-1b5f-49be-8871-a970ca88bbb6 · outbound

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

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip,

Reference 23

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source=pdf_text observed=2026-08-01T05:19:34.485998Z digest=sha256:af7cf58e6d46a62e1f07a66d184923df372a0e262871c331d6a80f42ebb948c2

Observation b63a89d5-24f7-4274-80ce-2c3e88914647 · outbound

This paper cites The spinnaker project,.

The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores The spinnaker project,

Reference 24

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source=pdf_text observed=2026-08-01T05:19:34.555832Z digest=sha256:af6e3034dc50c5f21935cb0363034a3b49b8078a68ea9c3bf8ff773da26e79b2

Pith citing papers

No inbound Pith citation observations are available.