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Paper Citation Record · LEDGER

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems

As of 8 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2506.03450.

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

pith.paper-citation-record.v1
2506.03450 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:06:01.554032Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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 exact10
  • verified fuzzy39
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fc0f8a93-546c-472e-a99e-60f4e76e4504 · outbound

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

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems SpiNNaker 2: A 10 Million Core Processor System for Brain Simulation and Machine Learning,

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a705cc82-6b7d-4168-90e3-121220ad8b71 · outbound

This paper cites A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs),.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs),

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.258790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 44d50dd2-c722-4733-9b4d-1fed75c6413c · outbound

This paper cites Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations,

Reference 3

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raw_fallback, observed 2026-08-07T11:06:02.245875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:05:59.593641Z digest=sha256:6f7b5d675ca01e104fd824652146a4f7ab5fb2d495f06206f897e6b07171a9de

Observation dbfb302d-50c9-434c-ba1f-092ab6feb2f5 · outbound

This paper cites Gyro: A Digital Spiking Neural Network Architecture for Multi-Sensory Data Analytics,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Gyro: A Digital Spiking Neural Network Architecture for Multi-Sensory Data Analytics,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.232635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:05:59.717828Z digest=sha256:e36133b099f4042bdf1bab6ed22cf6ba3c9c723a99831be59e142bea9a8c9abd

Observation 2e437113-3051-4fb1-96d9-ae73efaef741 · outbound

This paper cites Accelerated Analog Neuromorphic Computing.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Accelerated Analog Neuromorphic Computing

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:06:01.816678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:05:59.832612Z digest=sha256:8ed16a632ad6d9e1b1ec6635462183b251c5bccf55ffcff4243e93fbd391c965

Observation f322f470-855d-4e1b-b9c8-cd5a8a1a1612 · outbound

This paper cites Lava Software Framework — Lava documentation.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Lava Software Framework — Lava documentation

Reference 6

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raw_fallback, observed 2026-08-07T11:06:02.220891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:05:59.919569Z digest=sha256:f09eee96b513c5e5081e6c47e57ef616cd123b85e28d72db973743918d5c7163

Observation e4edb763-fd36-47a9-9739-ad7239df6dce · outbound

This paper cites PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:06:01.799803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:05:59.991374Z digest=sha256:3334cf1f2a7c519425f872790b0d59779eb9fea2adcac511e11d14c7add1f1ed

Observation 90547db1-47fe-443c-88ca-1e7e06168208 · outbound

This paper cites Nengo: a Python tool for building large-scale functional brain models,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Nengo: a Python tool for building large-scale functional brain models,

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.208537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.064987Z digest=sha256:7d7454a07647771d7929e023ec20d322257bde3e2dfb63fc807c2cf7ba3e8a07

Observation 72776e93-80f4-4a50-94d8-f3f6f77ed96b · outbound

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

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Networks of spiking neurons: The third generation of neural network models,

Reference 9

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raw_fallback, observed 2026-08-07T11:06:02.196485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.142055Z digest=sha256:0dc089ad10f41b50db7a19bf05895c7917dc55854fb1c65713bd5c67b3482ed8

Observation 6914edcc-e6dc-4359-8a61-10c09e451e33 · outbound

This paper cites Towards artificial general intelligence with hybrid Tianjic chip architecture,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Towards artificial general intelligence with hybrid Tianjic chip architecture,

Reference 10

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raw_fallback, observed 2026-08-07T11:06:02.186276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.234408Z digest=sha256:77a770ca0fdfb02732a77aa3025b844b481fdffad4263e196afa6233852f9aae

Observation 88340813-60ee-4b3e-86d7-3389289d1b3d · outbound

This paper cites Darwin: A neuromorphic hardware co-processor based on spiking neural networks,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Darwin: A neuromorphic hardware co-processor based on spiking neural networks,

Reference 11

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raw_fallback, observed 2026-08-07T11:06:02.175330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.315432Z digest=sha256:7410a4c8d26222bff39b1afc52e45e269917ad02ab57634d3d0f754c6a486b90

Observation 01b5b8ba-d708-419e-8ab7-fa398195d547 · outbound

This paper cites sPyNNaker: A Software Package for Running PyNN Simulations on SpiNNaker,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems sPyNNaker: A Software Package for Running PyNN Simulations on SpiNNaker,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.165934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.412744Z digest=sha256:67b1bac7e0a0b57382770147468fafa1e37c295e2a80688af2e3d188926a6834

Observation a24185a2-5aad-48d6-b9bd-0bb2c46cd68c · outbound

This paper cites Mapping Spiking Neural Networks to Neuromorphic Hardware,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Mapping Spiking Neural Networks to Neuromorphic Hardware,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.156148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.501959Z digest=sha256:ee9ea9dcc98c1ee803a80016d84a22144ad26aacea567f2e601689df1cdbe307

Observation f077d744-caf9-4aea-83e4-a1663619e9de · outbound

This paper cites DFSynthesizer: Dataflow-based Synthesis of Spiking Neural Networks to Neuromorphic Hardware.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems DFSynthesizer: Dataflow-based Synthesis of Spiking Neural Networks to Neuromorphic Hardware

Reference 14

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verified exact
local_arxiv, observed 2026-08-07T11:06:01.783473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.593551Z digest=sha256:653182c9a56f0f764f19988b3b879b8e7b72c42e5db942223450814d78870a6c

Observation db07958a-dd77-47d2-8870-d8ac8d481897 · outbound

This paper cites Deep Spiking Networks.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Deep Spiking Networks

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:06:01.769114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.670196Z digest=sha256:dae2614668c0c5ec9ece78d6f50d6fe43d76543d2c3ce0535454de8c1eab818e

Observation e9cf6b80-fd3a-4b04-a2bd-d5c8880ed5a2 · outbound

This paper cites Going Deeper With Directly-Trained Larger Spiking Neural Networks.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Going Deeper With Directly-Trained Larger Spiking Neural Networks

Reference 16

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local_arxiv, observed 2026-08-07T11:06:01.754389Z

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source=pdf_text observed=2026-08-07T11:06:00.735004Z digest=sha256:97b249798b48ef1fff6e19823c448dcff5fe2247d71f81569f3e11e6ff01c667

Observation 2545957c-d4a0-40ed-a3cb-2d9ff89f7900 · outbound

This paper cites Spiking Deep Residual Network,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Spiking Deep Residual Network,

Reference 17

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raw_fallback, observed 2026-08-07T11:06:02.145563Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.830160Z digest=sha256:979ee9d97c1b1d91ace344cc68e729bdbae9b81d6fbcf52a01cc23ab404989a8

Observation 2b49777e-f236-4240-8b25-2790d1463ec5 · outbound

This paper cites Deep Residual Learning for Image Recognition.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Deep Residual Learning for Image Recognition

Reference 18

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no resolver link, observed 2026-08-07T11:06:00.928647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:06:00.928647Z digest=sha256:53c842c6b6a96376c00f1dfdc3fbc1f5a450bef6961b7e6fc3b0b18e4d50f63b

Observation 263df979-8731-47f2-b16a-2ec9080aacfa · outbound

This paper cites SENSIM: An Event- driven Parallel Simulator for Multi-core Neuromorphic Systems,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems SENSIM: An Event- driven Parallel Simulator for Multi-core Neuromorphic Systems,

Reference 19

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.098930Z digest=sha256:d871b69d302e8321c46522b089166e2b6ee968dcd4878b7981522a65ac8d7cef

Observation 82775c19-f15f-456c-9a8b-87de72f7d64a · outbound

This paper cites Yousefzadeh, G.-J.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Yousefzadeh, G.-J

Reference 20

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.277536Z digest=sha256:ae993ef088b3ff52b96f193aff33e4b54ddfcbd1f83df5017c4943cff9e1ed3e

Observation b0582845-6fad-47aa-87f5-70e381d9b85c · outbound

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

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems SENECA: building a fully digital neuromorphic processor, design trade- offs and challenges,

Reference 21

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.434859Z digest=sha256:2f6735256ad9df7945f276ab06c5aef6b397b1e1de913b7624b514c6a7b163d6

Observation e0085244-80a7-4dc7-9dba-dfd757c8a611 · outbound

This paper cites Open the box of digital neuromorphic processor: Towards effective algorithm-hardware co-design.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Open the box of digital neuromorphic processor: Towards effective algorithm-hardware co-design

Reference 22

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local_arxiv, observed 2026-08-07T11:06:01.697132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.446160Z digest=sha256:ad26a9b7b3b21979ebfbc5add7235c6f75000a3f33e8e2049a9464bfc52dcb6d

Observation f9691285-6626-4d4a-ab92-e6495ca91c9c · outbound

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

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration,

Reference 23

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raw_fallback, observed 2026-08-07T11:06:02.100074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.452069Z digest=sha256:fa0c32a1d4cd2036373ba186cbc82e02678d928452965b67a81261772f474247

Observation a10e26b7-b4aa-488b-9248-cd512970eead · outbound

This paper cites CARLsim 3: A user-friendly and highly optimized library for the creation of neurobiologically detailed spiking neural networks,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems CARLsim 3: A user-friendly and highly optimized library for the creation of neurobiologically detailed spiking neural networks,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.088366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.455845Z digest=sha256:bab9fc512b65a73dfd5dead7006e5cf82bdb6f22cd80e693d2ebf3972e089762

Observation 84730157-d6ed-42b1-bc9d-f9d916fc88d8 · outbound

This paper cites Mapping spiking neural networks onto a manycore neuromorphic architecture,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Mapping spiking neural networks onto a manycore neuromorphic architecture,

Reference 25

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raw_fallback, observed 2026-08-07T11:06:02.076804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.459361Z digest=sha256:7f7450c87ebc0edef4268b3a86039c7e4b329c724de82e37128374d907e04555

Observation 2f80fbe2-d418-451d-b3f5-d02c39bd5a8f · outbound

This paper cites SNEAP: A Fast and Efficient Toolchain for Mapping Large-Scale Spiking Neural Network onto NoC-based Neuromorphic Platform.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems SNEAP: A Fast and Efficient Toolchain for Mapping Large-Scale Spiking Neural Network onto NoC-based Neuromorphic Platform

Reference 26

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verified exact
local_arxiv, observed 2026-08-07T11:06:01.672674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.462696Z digest=sha256:45de8ac73a6b394b512b1a846288e94a48cf5eb51cc6a00a40524da2122911df

Observation 2ed971d0-d776-4557-b590-6a1e73ef37b4 · outbound

This paper cites Mapping Deep Neural Networks on SpiNNaker2,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Mapping Deep Neural Networks on SpiNNaker2,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.065543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.466362Z digest=sha256:8beaf156e2ef70504b5b854d824f81573225768b7d9badb5abd89b39920a97ed

Observation 8326bda5-341f-4069-8791-c01ec64eac61 · outbound

This paper cites Run-time Mapping of Spiking Neural Networks to Neuromorphic Hardware.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Run-time Mapping of Spiking Neural Networks to Neuromorphic Hardware

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:06:01.650653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.469339Z digest=sha256:18fe61092a5c341ee357655583a7a38cb954e36d6806e73d63359594d0240fe5

Observation b10d8b28-66ab-4e28-a475-768498be007a · outbound

This paper cites Compiling Spiking Neural Networks to Neuromorphic Hardware.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Compiling Spiking Neural Networks to Neuromorphic Hardware

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:06:01.626089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.472729Z digest=sha256:6ca0d15f9dab0f8fb16b918909e7ab83c79959d3dc683f2746378ceeb38f9284

Observation 7209b07a-6b27-48f2-ba4f-4c47ffa20e82 · outbound

This paper cites Mapping of Spiking Neural Network Topologies on Neuromorphic Hardware|TU Delft Repository,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Mapping of Spiking Neural Network Topologies on Neuromorphic Hardware|TU Delft Repository,

Reference 30

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raw_fallback, observed 2026-08-07T11:06:02.055292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.476219Z digest=sha256:7a2082b9341b9d31d76f84c633e9701d604bdff945f0570ff75e6017a2e3a5b9

Observation f41a2a7f-a033-41f6-85f4-f326189e67a8 · outbound

This paper cites Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.044797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.479897Z digest=sha256:e58bfba86b240d163617181ad63ad15a30876b0eb84ebda86c52760ba65d4330

Observation 7e6f79ee-cbb4-4676-ab3b-a4d3e0ded650 · outbound

This paper cites Optimal Mapping of Spiking Neural Network to Neuromorphic Hardware for Edge-AI,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Optimal Mapping of Spiking Neural Network to Neuromorphic Hardware for Edge-AI,

Reference 32

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raw_fallback, observed 2026-08-07T11:06:02.033949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.483508Z digest=sha256:fa325e7833f27e0f867225912594ce18529d515dd4f698b29bb227a0c2302e7a

Observation 8a433e11-7f3e-4054-9321-6ffda7410b45 · outbound

This paper cites Mapping Very Large Scale Spiking Neuron Network to Neuromorphic Hardware,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Mapping Very Large Scale Spiking Neuron Network to Neuromorphic Hardware,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.022132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.487207Z digest=sha256:5f2b266b42bdd031bbb2ef405b516231f4618d3c0710a63740be9b071b382474

Observation 08bc033b-81d0-4a89-81a1-f42483fed388 · outbound

This paper cites R-MaS3N: Robust Mapping of Spiking Neural Networks to 3D-NoC-Based Neuromorphic Systems for Enhanced Reliability,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems R-MaS3N: Robust Mapping of Spiking Neural Networks to 3D-NoC-Based Neuromorphic Systems for Enhanced Reliability,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:02.009710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.491304Z digest=sha256:b347a1dd2d702a89f7def41fb4db66f8c1ac435b72c6f2d29bd8ad0653d4bc8a

Observation e280fffa-3c8e-43c5-bede-277f54f9bd9f · outbound

This paper cites EdgeMap: An Optimized Mapping Toolchain for Spiking Neural Network in Edge Computing,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems EdgeMap: An Optimized Mapping Toolchain for Spiking Neural Network in Edge Computing,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.997408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.495359Z digest=sha256:e1be68dbdfd6e70d1fee3785c82120cf34530a246eb6b387bd3c6da5b5af3fad

Observation 7beb55bf-bc76-4894-bf28-28b5dcae8f70 · outbound

This paper cites Pymoo: Multi-Objective Optimization in Python,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Pymoo: Multi-Objective Optimization in Python,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.986359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.500503Z digest=sha256:706e1e174385e634d40d24bba5458ea3325b830f4dffa621d9d1b80a59c7f8a9

Observation 4f506609-eb17-4c52-9c04-063174d7b979 · outbound

This paper cites Search biases in constrained evolutionary optimization,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Search biases in constrained evolutionary optimization,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.975891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.503725Z digest=sha256:bc352cccbd8de8c098a711c0eaadb1753bd5b1d2616786ba8c2afe2823e834ab

Observation 80f0d398-ba03-46fd-90a3-aa7d361a792b · outbound

This paper cites Reference Point Based NSGA-III for Preferred Solutions,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Reference Point Based NSGA-III for Preferred Solutions,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.965577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.507845Z digest=sha256:8d47dc5b53370936177773226ede75857dd755756c3bd73e7c2e851245f10ef2

Observation 2c8beba8-6e59-404d-a927-1931328a16a9 · outbound

This paper cites MOEA/D: A Multiobjective Evolu- tionary Algorithm Based on Decomposition.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems MOEA/D: A Multiobjective Evolu- tionary Algorithm Based on Decomposition

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.955213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.512206Z digest=sha256:6123b3de9df62dc5fde7a9656cb619d5e2cb8c14a9f645d2e03f6f69ef692e9a

Observation debfd9c8-cb91-4438-a80c-166153cb1c11 · outbound

This paper cites jMetalPy: A Python framework for multi-objective opti- mization with metaheuristics,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems jMetalPy: A Python framework for multi-objective opti- mization with metaheuristics,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.944125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.516105Z digest=sha256:c8b51d487dd399ac1d31ff71e468d1ce776f2ec4c758c566f32469e010f3ab8b

Observation 89aae513-7c32-4539-adab-2b6d2cf6b3b5 · outbound

This paper cites A parallel global multiobjective framework for optimization: pagmo,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems A parallel global multiobjective framework for optimization: pagmo,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.933173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.519573Z digest=sha256:4bf61e9ba40f55e4c1b2a495364acb4ee15420b19fa982362b8947aa34db245b

Observation 5b0e6c4c-3f82-4df1-b14f-55b21ba2b2c9 · outbound

This paper cites Open BEAGLE: a new C++ Evolutionary Computation framework,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Open BEAGLE: a new C++ Evolutionary Computation framework,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.921095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.523166Z digest=sha256:a40ce380c814a66088fc71e312d919e0ec9bd615f852642bd5716135a4412226

Observation a0e6c935-0f1a-4c61-95b7-81cf9b91b51d · outbound

This paper cites Opt4J: a modular framework for meta-heuristic optimization,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Opt4J: a modular framework for meta-heuristic optimization,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.907992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.526533Z digest=sha256:7125162fedd18decac8a7369415a5d112b1cd8dae106c9b5b258287ebe7bbd9c

Observation 07a1576f-90a8-4d4c-ab67-031901d65c5c · outbound

This paper cites Efficient mapping of large scale SNN and rate-based DNN on SENeCA|TU Delft Repository.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Efficient mapping of large scale SNN and rate-based DNN on SENeCA|TU Delft Repository

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.896506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.530191Z digest=sha256:a69a3a5d3b745730ce38151a43d4dca2e0ebfd859031b5ac39c167c3c2604029

Observation b38fce92-0532-4192-b048-4696c3835d31 · outbound

This paper cites Towards Efficient Deployment of Hybrid SNNs on Neuromorphic and Edge AI Hardware.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Towards Efficient Deployment of Hybrid SNNs on Neuromorphic and Edge AI Hardware

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.883863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.534118Z digest=sha256:41bfd11849b2af05521e25acb2f9ebd23d8810ed8296d52951391b099ed2627a

Observation 6aa90141-f718-48dc-8771-856e52a9e3c1 · outbound

This paper cites Efficient Event-Based Object Detection: A Hybrid Neural Network with Spatial and Temporal Attention.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Efficient Event-Based Object Detection: A Hybrid Neural Network with Spatial and Temporal Attention

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T11:06:01.537428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:06:01.537428Z digest=sha256:3aa63612939da01d21c15a5dde4d5fe7096cfc63cbb009f22997e0cc96ab8c1c

Observation 25281cbe-a748-4c5b-9211-47511c7d910f · outbound

This paper cites Particle swarm optimization,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Particle swarm optimization,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.871809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.541301Z digest=sha256:7bc0d8b2fdfa5e3b478097346e9c738ce4c525720b36bc25ec563c9d6997d9d5

Observation 3a3d9e3b-7247-4468-8581-083eb7fcbaea · outbound

This paper cites Dask: Parallel Computation with Blocked algorithms and Task Scheduling,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Dask: Parallel Computation with Blocked algorithms and Task Scheduling,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.860895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.544386Z digest=sha256:5881897ba1d483c8fb406b85cf29c2f4dd9e2665580cd5370fdbbe2ab6b25ab5

Observation 71ff4208-51c0-4b36-a87e-ed3b0f88615e · outbound

This paper cites End to End Learning for Self-Driving Cars.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems End to End Learning for Self-Driving Cars

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T11:06:01.547510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:06:01.547510Z digest=sha256:c2198baefc94a388cf583968b4fbd44797a0e4b64112c7c5182bbb740c1199e6

Observation 02446c46-5a77-4e09-b40c-9efa27158dab · outbound

This paper cites Simple Explanation of the No-Free-Lunch Theorem and Its Implications,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Simple Explanation of the No-Free-Lunch Theorem and Its Implications,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.848970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.550883Z digest=sha256:03ea1470ec4d525d85a2f54f629351eabef27a67923824a1d671da8adb216825

Observation 9fa51d10-f400-4e63-8c2e-706c37e0867c · outbound

This paper cites Challenges and recent prospectives of 3D heterogeneous integration,.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Challenges and recent prospectives of 3D heterogeneous integration,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:06:01.838495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:01.554032Z digest=sha256:204745d57f347c51d82697b054c5756829d81570ce56b279468bd2e420f89ce1

Observation a04c2497-51a8-4fe3-8d39-040625d85292 · outbound

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

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems SpiNNaker 2: A 10 Million Core Processor System for Brain Simulation and Machine Learning

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T11:05:59.354087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:05:59.354087Z digest=sha256:79256dd8cade58295835872315614730aceba183781f6be4e005fccadcac071e

Observation 0120cf0b-8f3c-40f7-8c05-d66c64ae5ab2 · outbound

This paper cites Spiking Deep Residual Network.

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems Spiking Deep Residual Network

Reference 2020

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:06:01.733970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:06:00.854820Z digest=sha256:ede2d8232d06e879b406b415a4e0bf5a495566c1fa5080e179692ad695bcadbe

Pith citing papers

No inbound Pith citation observations are available.