Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.08469.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:07:35.091789Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T23:21:01.201668Z
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 f42dc2bd-c6f3-4deb-aff4-ca2c585d7073 · inbound
Rapid yet accurate Tile-circuit and device modeling for Analog In-Memory Computing cites this paper.
Rapid yet accurate Tile-circuit and device modeling for Analog In-Memory Computing Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:07:35.091789Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a4c88559-fb41-4ecc-b82d-11dfb5367c12 · inbound
AnalogNAS-Bench: A NAS Benchmark for Analog In-Memory Computing cites this paper.
AnalogNAS-Bench: A NAS Benchmark for Analog In-Memory Computing Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
Reference 18
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T23:21:01.254789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.