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Paper Citation Record · LEDGER

Cross Knowledge Distillation between Artificial and Spiking Neural Networks

As of 8 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.438781Z digest=sha256:a922facf71fc54f0d9d0dc7d9ab44384df06ab13cd40d190e5747021768d9743

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.442179Z digest=sha256:b60209d73e13f1bf07a4235e0bd707c03ebfee28a671a14b00e81e78bbffea16

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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verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.445363Z digest=sha256:60bde073c438e5c571de629d30451b278049cd75fe4bb544dfde891efc672850

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.448851Z digest=sha256:99476a3bdfa45b39e1e8887da882473f7790286a2c976378b5e75e671fcd81e5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.452554Z digest=sha256:7ffb1e76def301d8e89d4166791b79964658f658cae23c4511f676192a032a99

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.459824Z digest=sha256:ea6a23cf7fe776cc781d106984d41dfbd8fe3586e3804736108bfc7fbcebf913

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.466798Z digest=sha256:ac9538f38dbed3d0ce1315e1e56fdd5571e3e39adea56b1c8acc588a4d412f06

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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verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.469823Z digest=sha256:6d3928608f76f3814e2f42ef8c62a6f00d24e341e35e483ed8b7f51adb8b2b6e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.472947Z digest=sha256:e7e3bd8fd45bd602b010f859ff6189c0b3a38991d765510cc28022a5fc2e0978

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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raw_fallback, observed 2026-08-06T18:05:43.782692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.478932Z digest=sha256:0576d9871683fe0939afa21b6c19aa068f15296140a2648216ab4c162a073bad

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.482173Z digest=sha256:730dff485ecaa67e325fc48c8a09cef908980a9d0ac981e65d5c666da93e2736

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.485087Z digest=sha256:d4f15c6d3f2d09d0a5e2fce0359c6336b8896696bf2c85feba4ef5da3f048696

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.488269Z digest=sha256:1112cf96cc77ee7404c1229d3cdf362dc4e4e20c7520d1a2f2ac58ade692ef4d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.491120Z digest=sha256:c5d4deed3eada8cee6f750d49b47d082c15d2dda3ec361a183febe7bfca3a5e2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.494120Z digest=sha256:b34b914cc00ee3c7b8531134ad9e2d7d5dee048588b1a86fe237ff0651637922

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.496897Z digest=sha256:48da6ab098fec85de4e27dc4a18729c3a1f210c41c7105c350778d58db3176a5

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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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.499679Z digest=sha256:eef8f16570003470b5d4c724073df0ec95e350291235cbd039b31ff0f6cbc81c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.502648Z digest=sha256:8b991cf378387dfc0926ae65221907a21941ec80197bb15269fa0453d85c18b6

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.505602Z digest=sha256:615d7f8b60b517fb41db9199a2faf4a437999f9e8c8c808732e0a83d79c728a1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.508606Z digest=sha256:a1c9301224f361886291cd690b6d3cffd420d9ef678ebbd7d7b76e63e0c4beee

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.511355Z digest=sha256:73a3eb75434394b6a57c73ceeb37d762710c70096b4f7697a7599cb043ca4bae

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.514257Z digest=sha256:939f22c47032fb5a956a58c63fe2abafdb65bf6053f55ad3ab068b0006cbdcf8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.516908Z digest=sha256:ab5d5b316444fa01f83d491a5ab15d42ffbd3912d909caddfd1e86fcbb30f3c0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.519959Z digest=sha256:60fc8e443c5661998e37ad033cd45a1729ae29719252381719babcee7bff14f9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.522616Z digest=sha256:455ae18b1379a597f44ef20b2e8733ec949cfa529e13b8110231ef66b97bad62

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

Resolution
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.525576Z digest=sha256:6506ff8eed03805618cd693d99a5c8b0a1fd209ac59be8a1e9aa64450a8b980a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T18:05:43.528257Z digest=sha256:75e553900645424ff425648816e6bc454ce6e02edb5bfbfb2c754c6eebdfd35b

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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unresolved
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.