Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2307.06084.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
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 2026-07-14T16:02:08.139778Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-08T05:24:31.814995Z
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 40045d0e-7e36-4b13-a735-ea42be4b803a · inbound
A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology cites this paper.
A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T03:20:56.104071Z
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.
Observation 3a7a9a36-e452-46f0-a89a-478fe9abc85a · inbound
A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology cites this paper.
A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:49:10.404230Z
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.
Observation 6bae84f2-80db-4b79-a719-595af900be81 · inbound
A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks cites this paper.
A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-07-08T05:24:31.816783Z
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.
Observation be00893e-f213-4e06-882f-654db0bc5e46 · inbound
A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks cites this paper.
A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T16:02:08.139778Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.