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Paper Citation Record · LEDGER

SpikeFI: A Fault Injection Framework for Spiking Neural Networks

As of 13 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2412.06795.

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

pith.paper-citation-record.v1
2412.06795 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:49:27.965402Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

52 of 52 outbound references displayed

  • verified exact0
  • verified fuzzy51
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a82fdaae-108a-43fe-8ddb-44ca26824044 · outbound

This paper cites Towards spike-based machine intelligence with neuromorphic computing,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Towards spike-based machine intelligence with neuromorphic computing,

Reference 1

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raw_fallback, observed 2026-08-12T14:49:29.049367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.546678Z digest=sha256:532f02f203ee9b543525aaf1e97b19f73563d3a943ecdec49bfae7cd13f6219f

Observation 4d74ebf6-ed9c-4ef5-b366-c507520e6276 · outbound

This paper cites Opportunities for neuromorphic computing algorithms and applications,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Opportunities for neuromorphic computing algorithms and applications,

Reference 2

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raw_fallback, observed 2026-08-12T14:49:29.032484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.551887Z digest=sha256:7cb78befd7349945d2a659f717d6b5c7b8ea54f19000b02bfb9f90ee4d202eb9

Observation 746eaf0e-7e02-4eb7-94d1-f09903b0a5a9 · outbound

This paper cites The SpiNNaker Project,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks The SpiNNaker Project,

Reference 3

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unresolved
no resolver link, observed 2026-08-12T14:49:27.559796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:49:27.559796Z digest=sha256:effafd509a13b7f9066690df5e9329ae4b15767ecf01faa157b66ea144377097

Observation aa45a333-24b9-4d3b-86a1-61c152957c8d · outbound

This paper cites A million spiking-neuron integrated circuit with a scalable communication network and interface,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A million spiking-neuron integrated circuit with a scalable communication network and interface,

Reference 4

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raw_fallback, observed 2026-08-12T14:49:29.006919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.564949Z digest=sha256:58f9e9838120b647026a7553d911fec911774cb5b7498fa4f50b719506a26c30

Observation 76a24d39-0ce8-43da-8c14-76b212909d1f · outbound

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

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 5

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raw_fallback, observed 2026-08-12T14:49:28.991413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.575953Z digest=sha256:057873c56e42a3336f135ed61e637ffcba909372b0651db6084d466038bd40ca

Observation 5040ed34-a43f-4c54-9e90-949e978c5ae7 · outbound

This paper cites A wafer-scale neuromorphic hardware system for large-scale neural modeling,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A wafer-scale neuromorphic hardware system for large-scale neural modeling,

Reference 6

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raw_fallback, observed 2026-08-12T14:49:28.972666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.582015Z digest=sha256:32a96c86bcd0a3da1316782cfc9e2169e7665c6cbc7881184e4ff57b43868aa8

Observation 0e1ba9a8-d719-4529-ba2c-a59d047db139 · outbound

This paper cites Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations,

Reference 7

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raw_fallback, observed 2026-08-12T14:49:28.948234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.594478Z digest=sha256:a0fc8a7be26d611005fbb93fc2aa7227eb100609e72b05e2a1c3ff4a475ca09e

Observation 7402b30c-e5b7-41f8-a31f-92e1c5b5fc70 · outbound

This paper cites Machine learning-based test pattern generation for neuromorphic chips,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Machine learning-based test pattern generation for neuromorphic chips,

Reference 8

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raw_fallback, observed 2026-08-12T14:49:28.919231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.602282Z digest=sha256:5432879f5892f5ed03fda5ef3669d816515f9ac7ef14ea334b002cdb9a05a4c6

Observation aab91c56-74e3-4998-be77-8a6d077f08a6 · outbound

This paper cites Automatic test configuration and pattern generation (atcpg) for neuromorphic chips,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Automatic test configuration and pattern generation (atcpg) for neuromorphic chips,

Reference 9

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raw_fallback, observed 2026-08-12T14:49:28.900801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.608918Z digest=sha256:b1e355b6280535d5325909fca10d6cb610f71581ef3b4ed5db215167b40bf0aa

Observation 6e3befd9-a50d-4568-b5ef-4b052a5e7249 · outbound

This paper cites Compact functional testing for neuromorphic computing circuits,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Compact functional testing for neuromorphic computing circuits,

Reference 10

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raw_fallback, observed 2026-08-12T14:49:28.875996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.615760Z digest=sha256:3b657cf15386a63ea6244bf4e973b52d6f1c819cc72dc36f5059fe75719d5c08

Observation f5b6c5c1-b24c-429b-b2a8-a5d9b8aa41f3 · outbound

This paper cites On-line testing of neuromorphic hardware,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks On-line testing of neuromorphic hardware,

Reference 11

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raw_fallback, observed 2026-08-12T14:49:28.858958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.621045Z digest=sha256:502774e7cef044e9178190b350f8a0e51fbbc2775cde01f37fdac89fc219b0c4

Observation 73c0ed19-6533-4627-8ce3-295c6d8a00cc · outbound

This paper cites Resilience and robustness of spiking neural networks for neuromorphic systems,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Resilience and robustness of spiking neural networks for neuromorphic systems,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.843243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.627837Z digest=sha256:409617a4315818355de202d297476b433841344a75da017e569d894c1b7fb5db

Observation a7cd905a-0fa0-43c8-81ff-b5b7be4bb361 · outbound

This paper cites Automatic abstraction and fault tolerance in cortical microachitectures,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Automatic abstraction and fault tolerance in cortical microachitectures,

Reference 13

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.827758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.637979Z digest=sha256:8479481e83ffa20f9922ab90a87cb6ea1d056c22691690be6c2553f3a252fe70

Observation f6921932-4945-4279-8297-60a836b3c8f3 · outbound

This paper cites Assessing self-repair on FPGAs with biologically realistic astrocyte-neuron networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Assessing self-repair on FPGAs with biologically realistic astrocyte-neuron networks,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.813762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.646530Z digest=sha256:2f12f267dd6b1ec1cfe9456eb1446588deb0ba260f2c6ae3e13581ff564f8727

Observation 6bf73ac4-b387-4cbc-bb01-9f651f5ed013 · outbound

This paper cites Homeostatic fault tolerance in spiking neural networks: A dynamic hardware perspective,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Homeostatic fault tolerance in spiking neural networks: A dynamic hardware perspective,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.795888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.653363Z digest=sha256:b2646a80db740177c045bb0d9c32c19e6667d18711d7a6c6a0396b134953805a

Observation 9671e3c7-7ba2-47d1-a7dd-f88d12af3007 · outbound

This paper cites SPAN- NER: A self-repairing spiking neural network hardware architecture,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SPAN- NER: A self-repairing spiking neural network hardware architecture,

Reference 16

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.779235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.664737Z digest=sha256:a00d48fd94d0c434c6fb5556806f8c894fe1428e09e543e8f803bfd49a62e4af

Observation db25c855-ebfd-4493-8d41-7a1eeb89dfb2 · outbound

This paper cites Self-testing analog spiking neuron circuit,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Self-testing analog spiking neuron circuit,

Reference 17

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raw_fallback, observed 2026-08-12T14:49:28.758502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.676163Z digest=sha256:c868bab67836d0ae03485d87f85a553e605d83634adcf69f3f4bf8a8c9ee5302

Observation 4e978827-74e2-49b0-ab69-2d1cbeecc66b · outbound

This paper cites Neuron fault tolerance in spiking neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Neuron fault tolerance in spiking neural networks,

Reference 18

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.738432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.687786Z digest=sha256:d1ee781b9292f79085e9a5643095ca30a2ae9b1b238fa3a25effce0ea8dda35a

Observation 784aa545-3f2c-436a-9e79-d570c0f45a94 · outbound

This paper cites SoftSNN: Low-cost fault tolerance for spiking neural network accelerators under soft errors,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SoftSNN: Low-cost fault tolerance for spiking neural network accelerators under soft errors,

Reference 19

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.716601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.704546Z digest=sha256:33b0c336f85e424a4cd2914bcb6247ed7b67c97344f35a178f03a8887fb5780c

Observation 40728d35-c3e2-47e3-9f90-24dc4d85e995 · outbound

This paper cites A resilience framework for synapse weight errors and firing threshold perturbations in RRAM spiking neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A resilience framework for synapse weight errors and firing threshold perturbations in RRAM spiking neural networks,

Reference 20

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.701726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.713807Z digest=sha256:6a989d740719643bb02b689791d1379c0e3deee561ad2ae154cc61cae48375ef

Observation 604b84a9-b77b-4243-a653-072d67c9bbb2 · outbound

This paper cites Reliability analysis of a spiking neural network hardware accelerator,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Reliability analysis of a spiking neural network hardware accelerator,

Reference 21

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raw_fallback, observed 2026-08-12T14:49:28.685205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.725002Z digest=sha256:f6ffb4aab9f9f9aa8cdcc2f0015a22795b3c69d94a626ddc1985f8c2047ee6b2

Observation a040173c-d262-419c-9d27-0a271df03848 · outbound

This paper cites Special session: Reliability of hardware-implemented spiking neural networks (SNN),.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Special session: Reliability of hardware-implemented spiking neural networks (SNN),

Reference 22

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.670216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.732226Z digest=sha256:fb2f11510f438d1a9795522377d8aa0f48a1a31eb90e00edb90740e8e918bb7d

Observation 0c7082de-5fd7-4767-a952-af3a56d6985d · outbound

This paper cites SpikingJET: Enhancing fault injection for fully and convolutional spiking neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SpikingJET: Enhancing fault injection for fully and convolutional spiking neural networks,

Reference 23

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.651899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.737509Z digest=sha256:7079dd89bc1cd8cea3686a6d46ba9003411f5346a52318a226573bf1a0c4b58d

Observation 2a00860c-3b72-42a4-8db6-18e08d9c35a5 · outbound

This paper cites Training spiking neural networks using lessons from deep learning,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Training spiking neural networks using lessons from deep learning,

Reference 24

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raw_fallback, observed 2026-08-12T14:49:28.636954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.745481Z digest=sha256:d3a2f4136aa944ff3a28c396e08a5123ad2f3fbcbbbc7b2af46453f7be5f83ba

Observation 5a578f3e-afa7-4f2e-80f1-25f91b4e6282 · outbound

This paper cites SLAYER: Spike layer error reassign- ment in time,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SLAYER: Spike layer error reassign- ment in time,

Reference 25

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raw_fallback, observed 2026-08-12T14:49:28.621024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.751867Z digest=sha256:ced7b2a106874abae547953bd42ec6bd1308154b55efab7f44c80db9e9190f15

Observation ee163186-87ec-49b3-9dfb-3a9f521a99bd · outbound

This paper cites Understanding error propagation in deep learning neural network (DNN) accelerators and applications,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Understanding error propagation in deep learning neural network (DNN) accelerators and applications,

Reference 26

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raw_fallback, observed 2026-08-12T14:49:28.607376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.758197Z digest=sha256:838205f5673aafa577ce040ed3d1ee6f0b013653df05ce2c9f1987744e780f80

Observation 86bec341-2e83-4f24-a657-13e06014ccce · outbound

This paper cites Ares: A framework for quantifying the resilience of deep neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Ares: A framework for quantifying the resilience of deep neural networks,

Reference 27

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.592360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.772474Z digest=sha256:e6560cf13f0afe15da4358b826e0658912ea276a83b7718ab8b98ac8a235d3d0

Observation 0258d5b7-2614-414c-93cd-0ed9afd72c19 · outbound

This paper cites PyTorchFI: A runtime perturbation tool for DNNs,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks PyTorchFI: A runtime perturbation tool for DNNs,

Reference 28

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raw_fallback, observed 2026-08-12T14:49:28.579339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.777614Z digest=sha256:4607bb12a0fe0c6891f31eb1589b6a9a426cae4d07f245bd6276e6ac6ea26277

Observation 746ae228-1cdf-4358-82b9-6ada1cf1802b · outbound

This paper cites TensorFI: A flexible fault injection framework for tensor- flow applications,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks TensorFI: A flexible fault injection framework for tensor- flow applications,

Reference 29

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.566568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.784900Z digest=sha256:24e708f1b90ab04f6e83f736c30eacce1769ceb090b8566204542534e7b0bed5

Observation 7b5e287c-a568-4da4-be5d-91804f49e6aa · outbound

This paper cites Fault injection for TensorFlow applications,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Fault injection for TensorFlow applications,

Reference 30

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raw_fallback, observed 2026-08-12T14:49:28.553379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.791644Z digest=sha256:e26423a0dbc27851112ff5870347c5a96d3393ff87e915508f4a41b3636c6959

Observation b6a95bf9-c676-43c3-abe9-0ab99ffeec6c · outbound

This paper cites FIdelity: Efficient resilience analysis framework for deep learning accelerators,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks FIdelity: Efficient resilience analysis framework for deep learning accelerators,

Reference 31

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raw_fallback, observed 2026-08-12T14:49:28.540720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.801296Z digest=sha256:f5e6f4a212b09472b8e848ec81734f0739c08062168ac8f2c6ce7ffb14fd69d1

Observation 41888f1a-5db6-4287-a534-de9615d8739a · outbound

This paper cites Fast and accurate error simulation for CNNs against soft errors,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Fast and accurate error simulation for CNNs against soft errors,

Reference 32

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.522093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.808939Z digest=sha256:0e99be62d9e8201f1c37705f2e0aec47667b32d17105f2429d683affa2afe5f1

Observation 5012b43a-08a4-4e51-89aa-a80c3f627c20 · outbound

This paper cites Emulating the effects of radiation-induced soft-errors for the reliability assessment of neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Emulating the effects of radiation-induced soft-errors for the reliability assessment of neural networks,

Reference 33

Resolution
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raw_fallback, observed 2026-08-12T14:49:28.507889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.815840Z digest=sha256:a2ced6cbc13fdb3001211befef2c749e1e625e774b0808145323fd2e9fbb7418

Observation 031d3457-bbea-4af2-9673-0f22f159dead · outbound

This paper cites BinFI: An efficient fault injector for safety-critical machine learning systems,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks BinFI: An efficient fault injector for safety-critical machine learning systems,

Reference 34

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raw_fallback, observed 2026-08-12T14:49:28.489317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.821354Z digest=sha256:f4e01d0039c41cc3a24da9825429a3afe7c4bf1ee074cc3010f8368d5dcb7c43

Observation 7deab69a-70d4-4b27-8bfa-44c4ded0ef2e · outbound

This paper cites Functional criticality analysis of structural faults in AI accelerators,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Functional criticality analysis of structural faults in AI accelerators,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.462454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.828678Z digest=sha256:ebeeb8a8737bd327cf50d63b144eaacd2651b32013e98e054353a43e078b4d71

Observation 06219cac-eed9-4e6e-9001-313f0583af60 · outbound

This paper cites SCI-FI: a smart, accurate and unintrusive fault-injector for deep neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SCI-FI: a smart, accurate and unintrusive fault-injector for deep neural networks,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.439848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.836187Z digest=sha256:2333d9ad73cb9710c04af550f22966f9564512ea5af575145e0276e9c17a2af7

Observation 005ce207-0359-41ca-af6a-2999c613be2c · outbound

This paper cites Assessing convolutional neural networks reliability through statistical fault injections,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Assessing convolutional neural networks reliability through statistical fault injections,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.421118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.849566Z digest=sha256:97d642258d8c828dd579026684780eb4ffda8070824a4676f175cf79f5a1845a

Observation dff318f5-de31-4e2a-8309-25ba7826a8dc · outbound

This paper cites SASSIFI: An architecture-level fault injection tool for GPU application resilience evaluation,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks SASSIFI: An architecture-level fault injection tool for GPU application resilience evaluation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.404191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.854586Z digest=sha256:c1aedc1b57d4a76c4234dd4f5b0d4c2d366ea5102dd215e4333b5bb7c0531863

Observation b5319b82-4938-4bfa-a872-ee9a1ec9abd7 · outbound

This paper cites NVBitFI: Dynamic fault injection for GPUs,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks NVBitFI: Dynamic fault injection for GPUs,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.390053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.859210Z digest=sha256:90a14c01c5fcb14c397d359dff696b5fec8a82719e178b90acd16cefca492f22

Observation c5003e22-3f21-4304-86a9-b9cdf52363ca · outbound

This paper cites Testability and dependability of AI hardware: Survey, trends, challenges, and perspectives,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Testability and dependability of AI hardware: Survey, trends, challenges, and perspectives,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.367326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.868107Z digest=sha256:ff5db82cdc4138e9a6e2ed24f71992accdb1b302d94622bd9a2717451e19a7e5

Observation cdd145b9-6d8d-4198-ba1f-5cf1a644cf65 · outbound

This paper cites A survey on deep learning resilience assessment methodologies,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A survey on deep learning resilience assessment methodologies,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.344050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.878409Z digest=sha256:6ba8878cf7c57d53433f412d26096fca2dd325ffa38ba00ce8b582a19ed09beb

Observation 9a4d4b67-3592-49d3-92f3-1c25099f61ec · outbound

This paper cites Testing and reliability of spiking neural networks: A review of the state-of-the-art,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Testing and reliability of spiking neural networks: A review of the state-of-the-art,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.314396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.885575Z digest=sha256:68a52eed8744e9efd66009e871e036f3a02f22015953dd25a4d505409850e251

Observation 647a80fc-e5c5-4184-8ca7-b499b8602985 · outbound

This paper cites A systematic literature review on hardware reliability assessment methods for deep neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A systematic literature review on hardware reliability assessment methods for deep neural networks,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.295134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.894823Z digest=sha256:59c42dc4ecabaacf00f02fe1cd1e134256d3fd8300b84f8ed8a57cd54aa75e71

Observation f883664a-5bc8-4d71-8187-a6bdb8375826 · outbound

This paper cites Artificial neural networks for space and safety-critical applications: Reliability issues and potential solutions,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Artificial neural networks for space and safety-critical applications: Reliability issues and potential solutions,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.273717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.906359Z digest=sha256:20da7ec7a19a430270187be71e0c720357df4db6bccc61cb045988eb408b1d8e

Observation 9cff2907-6f8d-45e3-a8ce-78345e7714bd · outbound

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

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Networks of spiking neurons: The third generation of neural network models,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.243913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.916561Z digest=sha256:82297ca79e3150370c7c4263c0afba11f5a3fe9162e60edc95bda52db0d4ec52

Observation f03c0914-8763-4995-9f90-cd5f9a2b6c86 · outbound

This paper cites Gerstner, W.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Gerstner, W

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.227743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.923654Z digest=sha256:13537270e295b0e11473f2b3de4dec7b92f929101751643b2def63d2761a1f60

Observation 607d67b6-7765-4291-a922-890b9e5faaeb · outbound

This paper cites Deep learning in spiking neural networks,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Deep learning in spiking neural networks,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.199668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.933391Z digest=sha256:b3c4b6bc303894a4f7799fee3a0bd72bad8306f212040edff4aa2cde29c0341a

Observation e31baef6-7424-4190-aaae-81da375bf9d6 · outbound

This paper cites Spiking neuron hardware-level fault modeling,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Spiking neuron hardware-level fault modeling,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.156168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.938111Z digest=sha256:0c9fe18dfa8ba540563d077791a22f7ddce99de10b22a74702892aca3ecd6a3b

Observation a915a472-9e33-40c6-8374-14942611972e · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks PyTorch: An imperative style, high-performance deep learning library,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.130481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.946435Z digest=sha256:28c4023f51dd0acd8bebb9f288ad7bcdb41632cd4809bd389642c517f40a4ad9

Observation 67983f75-8743-4c68-8134-b5bfc0cf47b8 · outbound

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

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Converting static image datasets to spiking neuromorphic datasets using saccades,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.096137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.951767Z digest=sha256:d95278ce21228cac91d0bf5784ae4785fe0ca7f57c184bb399ed7e2558464609

Observation bda1c393-856a-4959-9575-6e4cbb7a279d · outbound

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

SpikeFI: A Fault Injection Framework for Spiking Neural Networks A low power, fully event-based gesture recognition system,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.071351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.959793Z digest=sha256:ee4129427169788cfa28f75826bb40b013a948a4e82c6a1ff0d3cf98014c6b9a

Observation 7a28efcc-16ad-4a42-8afd-dc9488df162d · outbound

This paper cites Gradient-based learning applied to document recognition,.

SpikeFI: A Fault Injection Framework for Spiking Neural Networks Gradient-based learning applied to document recognition,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:49:28.029789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:49:27.965402Z digest=sha256:7b460f04aee5da95c833c8c3626e69fb7ad9a5441f4b95837bab6fe9ee056109

Pith citing papers

No inbound Pith citation observations are available.