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Paper Citation Record · LEDGER

Neural Collapse Inspired Federated Learning with Non-iid Data

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2303.16066.

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

pith.paper-citation-record.v1
2303.16066 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:22:23.447747Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T10:22:23.798413Z

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 ee42a6b9-310e-4078-8fef-73b8e3baeb6d · inbound

Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse cites this paper.

Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse Neural Collapse Inspired Federated Learning with Non-iid Data

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-16T10:22:23.801988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T10:22:23.447747Z digest=sha256:0cdb49284ae738c55f0e49e6a8304d30fe31e0380fb3f4e9e1f39298d01389f5