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Paper Citation Record · LEDGER

Cross Knowledge Distillation between Artificial and Spiking Neural Networks

As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2507.09269.

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

pith.paper-citation-record.v1
2507.09269 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:05:43.531241Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

  • verified exact4
  • verified fuzzy24
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2bbe1a47-a94c-4b95-8585-4ad101744e84 · outbound

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

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Networks of spiking neurons: the third generation of neural network models,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-06T18:05:43.840403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.434268Z digest=sha256:8cb209d33551039054289cf64f3015aaa86e4527f4f26ab8b903556b94d13c88

Observation 76e013a6-104f-40cd-aa1b-04b5ed6e4e42 · outbound

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

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Towards spike-based machine intelligence with neuromorphic computing,

Reference 2

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raw_fallback, observed 2026-08-06T18:05:43.831885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.438781Z digest=sha256:d0cc5902da63e81427023900054f36f94f0c999440101b6f877dde903aef3afd

Observation 33e9f075-e1bc-4e06-a9a4-ad6d6ef3a426 · outbound

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

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip,

Reference 3

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raw_fallback, observed 2026-08-06T18:05:43.823968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.442179Z digest=sha256:76cb6c4bfdead6dd876ead1e994e5b0f36f549d7492e6ed761d23dc655a13eb3

Observation 24ca9ee2-c6ef-4b72-b726-f5a926bb17c6 · outbound

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

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 4

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raw_fallback, observed 2026-08-06T18:05:43.815906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.445363Z digest=sha256:1b7f5317a37af7977480236b479d25e524a7661e8607d6e8e34afd504d624f5b

Observation a61f6e0d-c0bf-4384-865c-c08f05222292 · outbound

This paper cites Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks

Reference 5

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verified exact
local_arxiv, observed 2026-08-06T18:05:43.630507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.448851Z digest=sha256:d65f49f72685199ecb444018ae64239fa6283f39a99303599161820bc20adca3

Observation 90a7246f-cf2d-4cd8-945f-769b569d4671 · outbound

This paper cites UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networks.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networks

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:05:43.618321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.452554Z digest=sha256:d095f4f76e0ddbf6b01b1183fa30e9d980a783b492cf6ad78b6ae6912ef33048

Observation 3c5785d4-8d0b-479f-be45-29fd6c66f8fd · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Distilling the Knowledge in a Neural Network

Reference 7

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no resolver link, observed 2026-08-06T18:05:43.456488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:05:43.456488Z digest=sha256:79e24799a6afa2cd43970fa2219c7908137a0c2fd58a5ad7edaf2f1ab7e4982e

Observation c7bbbbc5-36bd-4728-8455-6d74155f5f9b · outbound

This paper cites LaSNN: Layer-wise ANN-to-SNN Distillation for Effective and Efficient Training in Deep Spiking Neural Networks.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks LaSNN: Layer-wise ANN-to-SNN Distillation for Effective and Efficient Training in Deep Spiking Neural Networks

Reference 8

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verified exact
local_arxiv, observed 2026-08-06T18:05:43.597063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.459824Z digest=sha256:624ce6f77f88136d635834061fac084733630668ba34db84eeb7db46c6f863f9

Observation 9c8dcccb-25a2-4042-bf75-0b072bbf050b · outbound

This paper cites ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action Recognition.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action Recognition

Reference 9

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no resolver link, observed 2026-08-06T18:05:43.463058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:05:43.463058Z digest=sha256:95fac66b25153c0aa75d04cca970906c59e2b9713dcd322880931c29b6c958e5

Observation 0209676d-ea4c-42be-8a42-7cb58317d02a · outbound

This paper cites An efficient knowledge transfer strategy for spiking neural networks from static to event domain,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks An efficient knowledge transfer strategy for spiking neural networks from static to event domain,

Reference 10

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raw_fallback, observed 2026-08-06T18:05:43.807835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.466798Z digest=sha256:11449c8dc726cd8fe653f9d303d02656cad152a89b5da50f37b0f07c73ed1ec4

Observation 16a99629-d8ef-4929-981e-306774a1f4b7 · outbound

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

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Converting static image datasets to spiking neuromorphic datasets using saccades,

Reference 11

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raw_fallback, observed 2026-08-06T18:05:43.799895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.469823Z digest=sha256:541faec660adf6cc72662d17367e9c066ce8dabcf17c7566fb3c0e8a70726939

Observation 54fc58c4-6541-4281-8128-aaa0b64d96b6 · outbound

This paper cites Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories,

Reference 12

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raw_fallback, observed 2026-08-06T18:05:43.790908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.472947Z digest=sha256:d797b2d602692989d5816a795c75635305d58aee943200eeffcf7ba3be1ef59d

Observation 4f045aa2-99a2-4f16-b3e3-2b6cfe93f444 · outbound

This paper cites Reduction of class activation uncertainty with background information,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Reduction of class activation uncertainty with background information,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a6d7afb2-2e07-4ef7-bb27-7988b73c6fff · outbound

This paper cites an unresolved cited work.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Unresolved cited work

Reference 14

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unresolved
raw_fallback, observed 2026-08-06T18:05:43.774644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9eebbaea-1f10-4f8e-8458-9bb146de1dde · outbound

This paper cites Unsupervised event-based learning of optical flow, depth, and egomotion,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Unsupervised event-based learning of optical flow, depth, and egomotion,

Reference 15

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raw_fallback, observed 2026-08-06T18:05:43.766713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3539d141-25b1-4d37-b1d8-5b82eac0fda0 · outbound

This paper cites Hots: a hierarchy of event-based time-surfaces for pattern recognition,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Hots: a hierarchy of event-based time-surfaces for pattern recognition,

Reference 16

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raw_fallback, observed 2026-08-06T18:05:43.758467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.485087Z digest=sha256:c0b09b9a0c23139d2ccbd2d13e19878582a77e66c703242d0d3c9c38d8c6d118

Observation 776f12ad-dd53-4781-a85a-e3a520d99017 · outbound

This paper cites Hats: Histograms of averaged time surfaces for robust event-based object classification,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Hats: Histograms of averaged time surfaces for robust event-based object classification,

Reference 17

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raw_fallback, observed 2026-08-06T18:05:43.750333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.488269Z digest=sha256:81200934c8ba64dbfd0c6a4264c8b3349a31caa81d41fe05a00b88e24335974c

Observation b502288e-477d-4dea-9131-3dfdc4763623 · outbound

This paper cites Restructuring the teacher and student in self-distillation,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Restructuring the teacher and student in self-distillation,

Reference 18

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raw_fallback, observed 2026-08-06T18:05:43.741824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.491120Z digest=sha256:8c5dae11c050a7e4d929f5457de5f482b98c1434ce2ffcfcbcc96d225ddd36bd

Observation f22f392a-29e8-4e8c-aae9-a42b1d3509c7 · outbound

This paper cites Decoupled knowledge distillation,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Decoupled knowledge distillation,

Reference 19

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raw_fallback, observed 2026-08-06T18:05:43.734004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.494120Z digest=sha256:4a88fded2098d15d0d309ec4cd62366711f2c2893cbb8d819b6d00c31a4242e8

Observation 28b41aa3-0723-4a1f-9597-4cadeb903ef2 · outbound

This paper cites Distill vision transformers to cnns via teacher collaboration,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Distill vision transformers to cnns via teacher collaboration,

Reference 20

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raw_fallback, observed 2026-08-06T18:05:43.725687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.496897Z digest=sha256:1849d2f32872414f716e29cbfa9e140efaa448c7738563f0285370e50be7def7

Observation e9668ead-799a-4fc9-8186-259c98d902d5 · outbound

This paper cites Distilling spikes: Knowledge distillation in spiking neural networks,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Distilling spikes: Knowledge distillation in spiking neural networks,

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-06T18:05:43.717307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.499679Z digest=sha256:c18de5cf916239f7322925e8692b3133c75dd1c56b526d3ae1410ae19fd4f010

Observation 0cdcfefd-40da-40e9-a911-f1521d6cedca · outbound

This paper cites Similarity of neural network representations revisited,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Similarity of neural network representations revisited,

Reference 22

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raw_fallback, observed 2026-08-06T18:05:43.709438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.502648Z digest=sha256:f429f36583c60f310bcfa14e6fe753251e6269b6896bce83e7ac8c1f720eed76

Observation ae07fac8-368c-49f8-82ad-c56920fb0551 · outbound

This paper cites Temporal efficient training of spiking neural network via gradient re-weighting,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Temporal efficient training of spiking neural network via gradient re-weighting,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:05:43.700737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.505602Z digest=sha256:f1fb48b4c2e9bf11a83b553d55d6e18971a691ce30fb28745e168d85105146cd

Observation 8a7ec086-4136-4ca0-9e72-2ce3d937f266 · outbound

This paper cites Learning from images: A distillation learning framework for event cameras,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Learning from images: A distillation learning framework for event cameras,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:05:43.692496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.508606Z digest=sha256:c786849c2e4a540e1904b6276c706b4173b62a50d5e92751c08fe866c98116ee

Observation b9fe6819-4308-4f4e-9ec3-948f28b26102 · outbound

This paper cites Neuromorphic data augmentation for training spiking neural networks,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Neuromorphic data augmentation for training spiking neural networks,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-06T18:05:43.684175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.511355Z digest=sha256:3b64d0c8982e1c59acfcab4c1252e7187ab84651b7fd46a4c3c2036b05837834

Observation 96510f45-de9a-4446-8c37-a58215fe5af3 · outbound

This paper cites Eventmix: An efficient data augmentation strategy for event-based learning,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Eventmix: An efficient data augmentation strategy for event-based learning,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:05:43.675336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.514257Z digest=sha256:380043333624e82f5465a943a1a03f2c225f113c3af09c4611c045f42289a57f

Observation e25f8b80-fc5f-47c7-9a59-8e5b7c2dff98 · outbound

This paper cites An unsupervised stdp-based spiking neural network inspired by biologically plausible learning rules and connections,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks An unsupervised stdp-based spiking neural network inspired by biologically plausible learning rules and connections,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-06T18:05:43.666570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.516908Z digest=sha256:c17d9957e32219a2eef91336b9a2b0e2a39801b30cfafb44829bb74894021826

Observation 99120ac8-a0b7-4107-b43a-6fa5a140c425 · outbound

This paper cites Improving stability and performance of spiking neural networks through enhancing temporal consistency,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Improving stability and performance of spiking neural networks through enhancing temporal consistency,

Reference 28

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raw_fallback, observed 2026-08-06T18:05:43.657361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.519959Z digest=sha256:47064f05baea0ee88adbbca3f748ae63120fd65d8c6ad4940751a548bb6de382

Observation 27a3cd9a-231d-48d8-ab8a-1c854b7a319e · outbound

This paper cites Spinalnet: Deep neural network with gradual input,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Spinalnet: Deep neural network with gradual input,

Reference 29

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raw_fallback, observed 2026-08-06T18:05:43.648539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.522616Z digest=sha256:fa49ca788dea57a64d351a4647e7b5c8cbfe1f734821a1ecc2a7aefaf4ed3ff3

Observation 1067eefe-e5d8-4484-9201-12a75940e462 · outbound

This paper cites Braincog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired ai and brain simulation,.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Braincog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired ai and brain simulation,

Reference 30

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raw_fallback, observed 2026-08-06T18:05:43.639859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.525576Z digest=sha256:308b3567e9a2b62ae4ecbbe55dbc05fcef13b5fc4a221cc6974a0727faab82d4

Observation 1740ff76-410a-42b4-a1b4-0fcf386ed045 · outbound

This paper cites LumiNet: Perception-Driven Knowledge Distillation via Statistical Logit Calibration.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks LumiNet: Perception-Driven Knowledge Distillation via Statistical Logit Calibration

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:05:43.575021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:05:43.528257Z digest=sha256:375f9b048a6ea70362a3e5b6c1bc96f17fbd3971343e8266d9e11edfd37a7a45

Observation 6e1d6174-a273-47f9-9cf8-3e8378625d52 · outbound

This paper cites Knowledge Distillation from A Stronger Teacher.

Cross Knowledge Distillation between Artificial and Spiking Neural Networks Knowledge Distillation from A Stronger Teacher

Reference 32

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no resolver link, observed 2026-08-06T18:05:43.531241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:05:43.531241Z digest=sha256:40f554753dd2f7324f42dde0ab5c7637b2e5dda135f37927e9380fb73ad05387

Pith citing papers

No inbound Pith citation observations are available.