Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2402.04663.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:59:34.758558Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-09T05:55:31.967857Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 712923c8-45dd-497e-a931-70d4c580ea5e · inbound
Enhanced Temporal Processing in Spiking Neural Networks for Static Object Detection Using 3D Convolutions CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 21833f08-4a1d-4d9c-b6e2-cf760b0324fa · inbound
ASRC-SNN: Adaptive Skip Recurrent Connection Spiking Neural Network CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 17
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 092a7009-801d-4152-bc23-43b8423ffcf9 · inbound
TDFormer: A Top-Down Attention-Controlled Spiking Transformer CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 583824b1-dd4b-4f5a-a253-eba525d3a1fc · inbound
Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 51
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 80e0fa7d-85a8-41d2-9479-f5d1bf6c3115 · inbound
Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 28
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 72a36404-4718-401c-901a-3e412d2674ca · inbound
SPEAR: Structured Pruning for Spiking Neural Networks via Synaptic Operation Estimation and Reinforcement Learning CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d8afc88-22ab-4e42-a585-aecaa6002497 · inbound
Optimization of Low-Latency Spiking Neural Networks Utilizing Historical Dynamics of Refractory Periods CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6a739e5-fb06-4e36-9dcc-806353b50461 · inbound
SDSNN: A Single-Timestep Spiking Neural Network with Self-Dropping Neuron and Bayesian Optimization CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 159c1563-c5dd-41e4-a53f-71c707d01e31 · inbound
ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.