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Paper Citation Record · LEDGER

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies

As of 6 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 2 inbound Pith citation observations for arXiv:2604.15919.

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

pith.paper-citation-record.v1
2604.15919 v3

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T19:30:55.726068Z

measured 53 of 53 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T01:49:51.435769Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved50
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8b875043-f489-49b8-853b-c38fb78b5143 · outbound

This paper cites Software in Science Is Ubiquitous yet Overlooked.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Software in Science Is Ubiquitous yet Overlooked

Reference 1

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verified exact
doi, observed 2026-07-12T19:39:02.251380Z

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.

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Observation d6719ede-24cf-4b80-ae7e-8587879d3164 · outbound

This paper cites Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID- 19 Response Team.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID- 19 Response Team

Reference 2

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Observation 8ade297b-6028-4f3c-bb07-d3c3472d5003 · outbound

This paper cites MODELLING THE PANDEMIC The simulations driving the world’s response to COVID- 19.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies MODELLING THE PANDEMIC The simulations driving the world’s response to COVID- 19

Reference 3

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Observation d5285375-67a9-4e54-b090-7f650f1b23ed · outbound

This paper cites Lee et al.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Lee et al

Reference 4

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:48aee41e74c201851d19aedeb12b01c88e457aab399a03c932871d8e4c77822a

Observation 031b1ff3-7e05-45d9-b22d-ed7e7568be28 · outbound

This paper cites The research software engineer.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies The research software engineer

Reference 5

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:e03d1252bbf46cf1abb7df7b4fdd43f56dfde8953f84e2060c58e791092daa98

Observation b06e9202-4680-46a2-92db-2970b5a3a0f5 · outbound

This paper cites Research Software Engi- neering.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Research Software Engi- neering

Reference 6

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:38dadbc29823fba4237edebaedb30aa1bc5d9dd30891c7aa26f0f9afbee60da4

Observation 83db25ea-1fe6-47aa-adda-fee1be15b360 · outbound

This paper cites an unresolved cited work.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Unresolved cited work

Reference 7

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:d65728110bfce27667d8b7f472c27bcb4867c2b2ffad9ac3512b21425141ce77

Observation fa851a87-0678-49f1-949c-32957b2f899e · outbound

This paper cites Continuous Integration, Delivery and Deployment: A System- atic Review on Approaches, Tools, Challenges and Practices.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Continuous Integration, Delivery and Deployment: A System- atic Review on Approaches, Tools, Challenges and Practices

Reference 8

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:a6a55d6c4bed495081800b4656c0b1260abba5031ebdc2abf06de969eca20108

Observation 2fc14a5c-b00c-492d-b0c3-dfd5fd545ac2 · outbound

This paper cites More Is Different.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies More Is Different

Reference 9

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:872f8fb7869b29c833bfd9ed9ab80da00ca432aab96667f5caf7d453d5e4ee62

Observation 0b7c6918-fff1-4b37-a2f7-d19073bbd09c · outbound

This paper cites Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Con- nectivity and Correlations.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Con- nectivity and Correlations

Reference 10

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:7237e36c3ec76bf8eab6a9d0193e78a5f19fddd08e1188457949bdf3a1b9e2ca

Observation 8771a3e5-5d26-418f-9e77-16ff142a0754 · outbound

This paper cites A Modular Workflow for Perfor- mance Benchmarking of Neuronal Network Simu- lations.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies A Modular Workflow for Perfor- mance Benchmarking of Neuronal Network Simu- lations

Reference 11

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:7e513d251fa4a16e7b35e9dc56a423ff01ba50b80a0bb37717015271ec2b75ed

Observation c8129d7a-13a1-4e01-99a5-dbcdbe08c640 · outbound

This paper cites NEST (NEural Simulation Tool).

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies NEST (NEural Simulation Tool)

Reference 12

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:2c067ebb2cab7f342669a76b092c951cd9f6d6989b1229e5ae8794f04a5f9fe5

Observation 43a5f180-7893-4045-8220-9185f53ecab6 · outbound

This paper cites Metadata practices for simula- tion workflows.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Metadata practices for simula- tion workflows

Reference 13

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:4130d7ca7cce55bfbc55f35f5e8d6e9ccf74f7863b7447022b1ada16c977154b

Observation ee218b21-9e95-4dba-9d00-a81fc7f31723 · outbound

This paper cites “You Don’t Meet Anybody When Walking from the Living Room to the Kitchen.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies “You Don’t Meet Anybody When Walking from the Living Room to the Kitchen

Reference 14

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:f1b9b00ba62b8610d38475e04ce7b58475b602d6f88ef3119c32693098553c87

Observation 51d3b7a0-3135-4cb3-80a4-ed168aa78904 · outbound

This paper cites Leveraging DevOps for Scientific Computing.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Leveraging DevOps for Scientific Computing

Reference 15

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:4d6ab5162e8c3fb92db81f889fd9cf8587bab6fec85f3c2de29d92d620a24865

Observation 6733102b-1077-4e25-9fab-787b436a06f7 · outbound

This paper cites GOVERNING BOARD OF THE EuroHPC JOINT UNDERTAKING No 11/2024 Amending the Joint Undertaking’s Work Programme and Budget for the year 2024 (Amendment no 1).

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies GOVERNING BOARD OF THE EuroHPC JOINT UNDERTAKING No 11/2024 Amending the Joint Undertaking’s Work Programme and Budget for the year 2024 (Amendment no 1)

Reference 16

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:48e54c49976369045f3ae8d85ed335f50d1c33c8043ac86b68a42e16d8539dcc

Observation aeba1a7e-026a-44e1-8795-a632d0bbbf36 · outbound

This paper cites Towards continuous benchmarking: An automated performance evaluation framework for high performance software.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Towards continuous benchmarking: An automated performance evaluation framework for high performance software

Reference 17

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:3b8bdac17e36466ed56c7d89402c6594554cd78a933fc78ee2dc14e26433557e

Observation df141eb9-1f8c-4fa1-9592-8edebfefa1f6 · outbound

This paper cites Towards Collaborative Continu- ous Benchmarking for HPC.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Towards Collaborative Continu- ous Benchmarking for HPC

Reference 18

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:1cf946653595db43a2b47c49a20c0b0b76d1d1cfb86d6fb1099359ec9f2fcae6

Observation 028388a8-f5ab-419e-bdc7-9816b5287b2f · outbound

This paper cites Badwaik et al.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Badwaik et al

Reference 19

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:3a943dc25147af0d900938cc9a0caecf9177c3b541e8da4cb39cb9c39f5081b6

Observation fe683a66-b770-439b-9952-b640bf24a8a5 · outbound

This paper cites Terhorst et al.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Terhorst et al

Reference 20

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:9fe911aead2b5995520acc020d22b3c4d619d1db46a5b9007293b33704f0274e

Observation c10d72d3-8825-4519-98ed-c565e1a52285 · outbound

This paper cites The impact of continuous inte- gration on other software development practices: a large-scale empirical study.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies The impact of continuous inte- gration on other software development practices: a large-scale empirical study

Reference 21

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:2130695f0e3bbc4171ee0db9d63a3530635d3cf77610d75b2b930476a9fc841e

Observation e584cb99-d02d-4931-ab93-4b490d7f1893 · outbound

This paper cites Hayot-Sasson et al.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Hayot-Sasson et al

Reference 22

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:377b1552a697d3f602563a72a1e50e30fe3804abf8af4c645e91b35dd59e4850

Observation db8e7119-9676-45f7-ad51-b7230e99f9c0 · outbound

This paper cites JUSUF: Modular Tier-2 Su- percomputing and Cloud Infrastructure at J¨ ulich Supercomputing Centre.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies JUSUF: Modular Tier-2 Su- percomputing and Cloud Infrastructure at J¨ ulich Supercomputing Centre

Reference 23

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:645f0f15ff9a101adee5c2c729bf5f73f7488a6767fc412aa4c17699df76da0c

Observation 11c67634-d56d-4573-921b-1f0f49f4932a · outbound

This paper cites JURECA: Data Centric and Booster Modules implementing the Modular Supercomputing Architecture at J¨ ulich Supercomputing Centre.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies JURECA: Data Centric and Booster Modules implementing the Modular Supercomputing Architecture at J¨ ulich Supercomputing Centre

Reference 24

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:ec01c64d185eac5d63f05d986677660b219624d7d054a32c856e2746c0a9b61c

Observation 8614df77-4b21-40b7-b9e4-2716e66bf766 · outbound

This paper cites JUWELS: Modular Tier-0/1 Super- computer at J¨ ulich Supercomputing Centre.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies JUWELS: Modular Tier-0/1 Super- computer at J¨ ulich Supercomputing Centre

Reference 25

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:141887cbd3e89b4e609714c62140b93f590d70e89fc8198c0b4451b6ffb2faa2

Observation 565e0f77-ca00-46bd-8f10-962334220fd7 · outbound

This paper cites Application-Driven Exascale: The JUPITER Benchmark Suite.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Application-Driven Exascale: The JUPITER Benchmark Suite

Reference 26

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:bc8678631862122066e3c7a21c931f7ab407720676459469fe16404493b35661

Observation 14c854a9-1ead-4cad-bd16-e1b7d0ce2b95 · outbound

This paper cites Extremely Scalable Spiking Neu- ronal Network Simulation Code: From Laptops to Exascale Computers.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Extremely Scalable Spiking Neu- ronal Network Simulation Code: From Laptops to Exascale Computers

Reference 27

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:6f2a014a39c69f48cf8bc62b8e63ceb9de45156c2918f62170199db4e03882f5

Observation 48e34655-4bac-4b1b-a2d3-0228bf740116 · outbound

This paper cites Spiking network simulation code for petascale computers.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Spiking network simulation code for petascale computers

Reference 28

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:bd3259a53fd8c65c408314f2211734ace049593e8cadcdfef9b97bb7d533f97c

Observation 711914e0-4e95-4270-8c27-7bd83687c2a0 · outbound

This paper cites The Cell-Type Specific Cortical Microcircuit: Relating Structure and Activity in a Full-Scale Spiking Network Model.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies The Cell-Type Specific Cortical Microcircuit: Relating Structure and Activity in a Full-Scale Spiking Network Model

Reference 29

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:5e633fbec884dcf10e4f716927ce5c4ceabb42d57b65b7fd81a1a2c347046a9a

Observation c04f70b8-9932-477a-b840-3e597464669f · outbound

This paper cites A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas

Reference 30

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:6ef76ae6c15d317cf2909b523fd5478a7fc44b68a27b962d488697d0d435de0a

Observation 18ff88dc-37b0-48f2-83e2-0fd6713cd9b1 · outbound

This paper cites Haug et al.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Haug et al

Reference 31

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:20ae2275bddffbfc2623e007b1791adfd008ddc05de165f8b1e0d22d1e198c40

Observation a209ba6d-f9a7-471d-960c-9c196f3a2831 · outbound

This paper cites Graber et al.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Graber et al

Reference 32

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:5bf29ba76e4893c115a56cb77a09e79e1a26b1236d2f98376ed90c465b1c1f9b

Observation 990144c1-b100-43c8-b988-250e115d3b9d · outbound

This paper cites Usage and Scaling of an Open-Source Spiking Multi-Area Model of Monkey Cortex.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Usage and Scaling of an Open-Source Spiking Multi-Area Model of Monkey Cortex

Reference 33

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:94ee6e633b91a35f9894ba173cc4a0e857f75fafe0444ee97e31bf1971df0c98

Observation 6eafcf00-3049-499e-b1fc-6b4fdca2c0c8 · outbound

This paper cites Routing Brain Traffic Through the Von Neumann Bottleneck: Parallel Sorting and Refactoring.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Routing Brain Traffic Through the Von Neumann Bottleneck: Parallel Sorting and Refactoring

Reference 34

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:ee42e17580bfc7c2011a39329b4794d0505e0890d08096bdfe881869ccf950e3

Observation 497a8447-3bfb-4f8e-afd8-3bebf910d99e · outbound

This paper cites Routing brain traffic through the von Neumann bottleneck: Efficient cache usage in spiking neural network simulation code on general purpose computers.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Routing brain traffic through the von Neumann bottleneck: Efficient cache usage in spiking neural network simulation code on general purpose computers

Reference 35

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:dcaf36e9a4102c6aa28b27428b829d6f6495a0d1da24359a4c28b6424d2af65f

Observation 494112e4-ea55-46a5-9d4f-9f51baaf2c2c · outbound

This paper cites Sub-realtime simulation of a neu- ronal network of natural density.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Sub-realtime simulation of a neu- ronal network of natural density

Reference 36

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:938df2115580358d21e0bb8b9db36fc8aad53c826869e650a341b0842e8f6106

Observation e2c1d0b5-57ce-465c-bb24-a47556645fc0 · outbound

This paper cites an unresolved cited work.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Unresolved cited work

Reference 37

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:d25a146f83dd01e6430d7a89c5b44707612366566fa8c524a557625ab13b53cd

Observation 2ac805d1-4580-4a87-b1bd-6c3d3284e7ed · outbound

This paper cites Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynap- tic Cell Type.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynap- tic Cell Type

Reference 38

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:9b42373b17d404b939b649406fc58a60d7baeac52b22a197503f133825419ad8

Observation 2c86696c-243d-4b11-9938-64925aad1b06 · outbound

This paper cites Precise spike timing with exact subthreshold integration in discrete time network simulations.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Precise spike timing with exact subthreshold integration in discrete time network simulations

Reference 39

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:93e9586616ab4ee5d2a3b7d4b13e008231e65164be728575247013e171af4996

Observation 61c714ff-cf85-47d2-aac6-fde090c5a569 · outbound

This paper cites Spike- Timing Dependent Plasticity in Balanced Ran- dom Networks.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Spike- Timing Dependent Plasticity in Balanced Ran- dom Networks

Reference 40

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:9be91cff062da7f1fffb22566fd10fb473b31be16214521d2c413cf5f629547c

Observation 8f50994b-852d-45f0-8c56-86fa6e814fe5 · outbound

This paper cites The role of metadata in repro- ducible computational research.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies The role of metadata in repro- ducible computational research

Reference 41

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:4c8ac04afda207c0208634b8fc352dc94c2ab2071174217a160f679f7e81f22e

Observation 9a20d349-0a87-4cf2-9eae-c897dcdcb230 · outbound

This paper cites Editorial: Neuroscience, com- puting, performance, and benchmarks: Why it mat- ters to neuroscience how fast we can compute.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Editorial: Neuroscience, com- puting, performance, and benchmarks: Why it mat- ters to neuroscience how fast we can compute

Reference 42

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:69bbecc77232d080afb505601d4b9614289528c7db34889e24f9b08c4bb628ce

Observation a7c91de2-3577-49cf-af46-778fb53606ab · outbound

This paper cites Pronold et al.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Pronold et al

Reference 43

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:69744d0cdb2977b18deebd5379c5ef7c1725b54b99060aacb11a95c07726596a

Observation 310f5606-a558-4bc9-a557-3f09c74690ed · outbound

This paper cites Phe- nomenological models of synaptic plasticity based on spike-timing.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Phe- nomenological models of synaptic plasticity based on spike-timing

Reference 44

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:9b295c9297679e4b949f7a79e1fa9b3701db4c88445bee7001d43c56d66a4dbc

Observation 7eeabfd7-c4f3-4b96-b16b-bfe44caf8868 · outbound

This paper cites A Fast, Compact Approxima- tion of the Exponential Function.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies A Fast, Compact Approxima- tion of the Exponential Function

Reference 45

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:ebb2a469b4745e0bf3e17741e21c3cf29e46f72e8943aa4bba5fb655253224bd

Observation 52c25c6e-ff1e-4d52-9c4b-352f6a9ad57f · outbound

This paper cites On a Fast, Compact Approximation of the Exponential Function.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies On a Fast, Compact Approximation of the Exponential Function

Reference 46

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:0831ffe9d371de9075415ddb49da92ab581211272da3f71f19cdc9a312e53640

Observation aa5c7c76-94e1-40af-98fe-3c84219daced · outbound

This paper cites Fast exponential compu- tation on simd architectures.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Fast exponential compu- tation on simd architectures

Reference 47

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:aff925f7ad6dbcdbcffca24ac0ec6a91a174610402bbfb0d5a8288b8eba5eb18

Observation acaf350f-d8de-4a07-8cc3-3c1b06afe60a · outbound

This paper cites Accelerating Event-Driven Sim- ulation of Spiking Neurons with Multiple Synaptic Time Constants.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Accelerating Event-Driven Sim- ulation of Spiking Neurons with Multiple Synaptic Time Constants

Reference 48

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:d3af5bdc13f3ace4d9b70fd1999637731d2caabbc548864ead7b37fe66b54fa2

Observation 611ac076-be8c-424b-907f-c29a691b34e2 · outbound

This paper cites A fixed point exponential func- tion accelerator for a neuromorphic many-core sys- tem.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies A fixed point exponential func- tion accelerator for a neuromorphic many-core sys- tem

Reference 49

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:d5d5bbc173a873ebeddb99f8d33399f345c6c11ec344cb9123043960b9ef9932

Observation 9214cdfc-d2ca-459e-9c11-1da02d9a7e5d · outbound

This paper cites Exact Subthreshold Integration with Continuous Spike Times in Discrete-Time Neu- ral Network Simulations.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies Exact Subthreshold Integration with Continuous Spike Times in Discrete-Time Neu- ral Network Simulations

Reference 50

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:c351cd49190cbce87b691911578651dae836cecba395e8f7f9f14d348c8ab2c6

Observation 240bbd23-7d6f-419a-af0e-3699fc887a73 · outbound

This paper cites A general and efficient method for incorporating precise spike times in globally time-driven simulations.

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies A general and efficient method for incorporating precise spike times in globally time-driven simulations

Reference 51

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source=pdf_text observed=2026-07-12T19:30:55.726068Z digest=sha256:f1a8b96905dfb52635d88f8dfd74b406158e98bed9f01afefe72540097243cc2

Pith citing papers

Observation 2e2c2724-f501-4afc-a637-b3d3a0c59779 · inbound

NUMA balancing hampering performance of spiking network simulations cites this paper.

NUMA balancing hampering performance of spiking network simulations Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies

Reference 27

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source=pdf_text observed=2026-08-01T05:17:56.380178Z digest=sha256:a9c9c6367be47cf376b3c6495776c51301c09a0b64d2210a1806eb57d444b286

Observation 991cd54c-febf-4144-a8dd-dc7b7c123eef · inbound

NUMA balancing hampering performance of spiking network simulations cites this paper.

NUMA balancing hampering performance of spiking network simulations Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies

Reference 27

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source=pdf_text observed=2026-08-03T01:49:51.435769Z digest=sha256:cc652a56a0cda429e6d59ef1615a7743f12e28ec301c340b93083387ebd144c4