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Paper Citation Record · LEDGER

SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2302.13939.

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

pith.paper-citation-record.v1
2302.13939 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 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 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:24:58.392035Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:48:21.577931Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6f68d463-ace0-4752-81e4-1117f8d7bee7 · inbound

FAS: Fast ANN-SNN Conversion for Spiking Large Language Models cites this paper.

FAS: Fast ANN-SNN Conversion for Spiking Large Language Models SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-09T00:24:58.392035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:24:58.392035Z digest=sha256:5c9286348cb311b49cd5847b40624bcd2e4eea34412ec21e193eefa3e38eb8a4

Observation ded996f7-07c9-43d5-ac14-f9251b64c4b4 · inbound

Neuromorphic Principles for Efficient Large Language Models on Intel Loihi 2 cites this paper.

Neuromorphic Principles for Efficient Large Language Models on Intel Loihi 2 SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-08T10:59:50.661408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T10:59:50.661408Z digest=sha256:f8768223bc59b547579b351b49ca7a3e015a4b489f574be6f34fbe82a35666aa

Observation ba8e540d-817e-45a9-93c4-15f659919a7c · inbound

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation cites this paper.

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:33.263307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:33.263307Z digest=sha256:eecf5529451125d5e2c4dc561c9c5041eb127b0330a0f4f065ee81f8223cfcd8

Observation b2bc0e36-fd13-4eec-9e24-cdfa824b4aae · inbound

Word2Spike: Poisson Rate Coding for Associative Memories and Neuromorphic Algorithms cites this paper.

Word2Spike: Poisson Rate Coding for Associative Memories and Neuromorphic Algorithms SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T22:24:23.044237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:24:23.044237Z digest=sha256:a52af7ae47aaaa3d2130a61c6c7d4c95c362e7ad36ae29e68ba7bf1dd03e9d80

Observation 81e43a94-5f93-4484-8b0a-169e587bec58 · inbound

SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba cites this paper.

SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T09:46:12.463285Z

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=2026-05-18T09:44:53.290259Z digest=sha256:542d8f690b5fd01532f02cb0590e9017163d0dd6c9b176f8b97a5107f64d7daa

Observation 984b183a-6452-4523-bd23-c5744f381b0b · inbound

Winner-Take-All Spiking Transformer for Language Modeling cites this paper.

Winner-Take-All Spiking Transformer for Language Modeling SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:06:03.702191Z

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=2026-05-10T15:09:41.160765Z digest=sha256:5cdb201be073bc944da0f91c2a54073ed959b3ecf4a441590d93c4de84c608e5

Observation 26df6ca0-6974-403a-a61b-8d58cd46a793 · inbound

Adaptive Spiking Neurons for Vision and Language Modeling cites this paper.

Adaptive Spiking Neurons for Vision and Language Modeling SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:30:30.715312Z

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=2026-05-10T14:28:41.685107Z digest=sha256:23280183dac3fe710092b36a0ac4cefd8f1fdf3696b0edc6d4ed0a52c0d80766

Observation 15164af8-e913-4236-b4b1-e03778ffd681 · inbound

Affinity Is Not Enough: Recovering the Free Energy Principle in Mixture-of-Experts cites this paper.

Affinity Is Not Enough: Recovering the Free Energy Principle in Mixture-of-Experts SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 47

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T15:51:41.002906Z

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=2026-05-09T19:10:18.888463Z digest=sha256:f25c8d282c7336dd2fe51858fe813fe727c0a3aa9db850dd16c8b7fe4139e90f

Observation 75c53908-17c3-42e1-b08e-e6692975d933 · inbound

BiSpikCLM: A Spiking Language Model integrating Softmax-Free Spiking Attention and Spike-Aware Alignment Distillation cites this paper.

BiSpikCLM: A Spiking Language Model integrating Softmax-Free Spiking Attention and Spike-Aware Alignment Distillation SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:15:11.750639Z

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=2026-05-15T07:11:46.177353Z digest=sha256:c879e21299d998a9ca0a7d661edcf207b32d4ae71d5eed504efbdf26c653cea8

Observation 146aab85-9521-4a4e-a5c1-6def4758c708 · inbound

Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers cites this paper.

Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-21T08:19:52.497765Z

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=2026-05-21T08:17:45.899981Z digest=sha256:6d2c146bde99ea90abb250c2854ec2a56794d3f4e5b872654d618bc17dee3411

Observation 07bbd5d6-67d3-4010-850c-c9ee2e2ae468 · inbound

Spike-Aware C++ INT8 Inference for Sparse Spiking Language Models on Commodity CPUs cites this paper.

Spike-Aware C++ INT8 Inference for Sparse Spiking Language Models on Commodity CPUs SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-02T05:56:40.458777Z

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=2026-06-28T07:58:02.163383Z digest=sha256:06ef991d92e466341979eaf818454566ec7ca2f6a1b849887a8c7f5fed493f4f

Observation 2e8a80ab-f6f2-44f1-8265-23d1a22d1779 · inbound

Attention by Synchronization in Coupled Oscillator Networks cites this paper.

Attention by Synchronization in Coupled Oscillator Networks SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-03T08:17:45.803213Z

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=2026-06-27T10:48:02.028017Z digest=sha256:2c7ae9a84923b1ec711b4402274d834e17ace9d5a3ed6a626ccfb13676f988a7

Observation 297614d0-8f1f-44db-bb79-c02113070bf3 · inbound

LongSpike: Fractional Order Spiking State Space Models for Efficient Long Sequence Learning cites this paper.

LongSpike: Fractional Order Spiking State Space Models for Efficient Long Sequence Learning SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 33

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T13:48:21.579370Z

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=2026-06-27T07:26:58.608421Z digest=sha256:b41815a03446330c58af9c47d7a09120bcacced77f9f839888e3e4d4a9d2994d

Observation 67ec51e6-329e-4de0-b66b-92d0170fe2e6 · inbound

SpikeLogBERT: Energy-Efficient Log Parsing Using Spiking Transformer Networks cites this paper.

SpikeLogBERT: Energy-Efficient Log Parsing Using Spiking Transformer Networks SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T09:45:39.803200Z

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=2026-07-01T06:18:36.409752Z digest=sha256:1f05551773efb2ea83eacf92b5dc6c239b9f93c21d39c539af0b716614319465

Observation e73bcdaf-5de8-4968-a156-f7a8ac65956c · inbound

The Sparsity Ceiling: Where Spiking Networks Can and Cannot Trade Activity for Energy cites this paper.

The Sparsity Ceiling: Where Spiking Networks Can and Cannot Trade Activity for Energy SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-01T11:38:15.065442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:38:15.065442Z digest=sha256:c9258159082862322be487d0ff9981cbc640813e8c749f7f699cd3fc68546a13