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Paper Citation Record · LEDGER

A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2106.06984.

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

pith.paper-citation-record.v1
2106.06984 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:24:58.274648Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T03:45:58.498240Z

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 1294a23d-a892-4452-aeba-a967c95110a8 · inbound

QKFormer: Hierarchical Spiking Transformer using Q-K Attention cites this paper.

QKFormer: Hierarchical Spiking Transformer using Q-K Attention A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:45:58.501209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T03:45:18.189832Z digest=sha256:0e2941eb061b3b16d438aef22066f913d0c8af96cf522f3012e8b370be29a007

Observation fa52cab0-9215-4332-ba17-dab1aade9c11 · inbound

FAS: Fast ANN-SNN Conversion for Spiking Large Language Models cites this paper.

FAS: Fast ANN-SNN Conversion for Spiking Large Language Models A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-09T00:24:58.274648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:24:58.274648Z digest=sha256:f94053d26775c0132047849b7b288eee1991c2a715363a11044ca152a0740ef1