Paper Citation Record · LEDGER

SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2407.04752.

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

pith.paper-citation-record.v1
2407.04752 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:15:48.010686Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T15:08:32.797977Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
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 76e59010-5c96-48be-be49-30ba63287a9b · inbound

Reconsidering the Energy Efficiency of Spiking Neural Networks Inference from Analytical Perspectives cites this paper.

Reconsidering the Energy Efficiency of Spiking Neural Networks Inference from Analytical Perspectives SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-23T21:38:27.786528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d7a6f292-14bb-49d7-a2c2-7f81a57002d6 · inbound

Darkit: A User-Friendly Software Toolkit for Spiking Large Language Model cites this paper.

Darkit: A User-Friendly Software Toolkit for Spiking Large Language Model SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T11:15:48.010686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 835ed317-e61d-4c36-ae25-bd28ea26c5c1 · inbound

A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search cites this paper.

A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 158

Resolution: unresolved; no resolver link, observed 2026-08-07T05:07:40.148962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9f4bb16-75b8-4047-a75b-9ca85bfd065f · 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 SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:46:12.434277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e1a414ee-27c9-4207-ada8-1ae23946a7bd · inbound

Matterhorn: Masked Time-to-First-Spike Encoding by Reassigning the Silent State for Sparse and Energy-Efficient Spiking Transformers cites this paper.

Matterhorn: Masked Time-to-First-Spike Encoding by Reassigning the Silent State for Sparse and Energy-Efficient Spiking Transformers SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T06:31:51.756697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa82caaa-6580-4241-9ea7-aa01f80c4fa5 · inbound

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

Winner-Take-All Spiking Transformer for Language Modeling SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:06:03.713203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f5d5cf6a-3ffb-4d5f-8716-54de18e08e5e · inbound

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

Adaptive Spiking Neurons for Vision and Language Modeling SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:30:30.768619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 267b5636-24d7-4fdf-a0a5-6b6c0eab2729 · 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 SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-07-03T13:48:21.527502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0acea7dd-b876-40c5-a35a-47b7b32e2bec · inbound

Otters++: A Time-to-first-spike Based Energy Efficient Optical Spiking Transformer cites this paper.

Otters++: A Time-to-first-spike Based Energy Efficient Optical Spiking Transformer SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-03T15:08:32.799467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 46e37794-08bf-49e2-91b0-a153672fb85e · inbound

SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks cites this paper.

SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:33:54.595161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.