Pith. sign in

Paper Citation Record · LEDGER

Stochastic Training is Not Necessary for Generalization

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2109.14119.

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

pith.paper-citation-record.v1
2109.14119 v2

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:58:26.292899Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

6
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b4df2c74-8030-4e9d-8d83-3dfa0771e781 · inbound

Parameter Symmetry Potentially Unifies Deep Learning Theory cites this paper.

Parameter Symmetry Potentially Unifies Deep Learning Theory Stochastic Training is Not Necessary for Generalization

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-08T19:58:26.292899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:58:26.292899Z digest=sha256:c51a620b2c482620426a9dab188ff18103138153ffda59689438c6af211236fd

Observation 27ee764b-8393-4c31-98be-13dc6a5ecc43 · inbound

Knowledge distillation as a pathway toward next-generation intelligent ecohydrological modeling systems cites this paper.

Knowledge distillation as a pathway toward next-generation intelligent ecohydrological modeling systems Stochastic Training is Not Necessary for Generalization

Reference 60

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T12:05:50.000752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T12:05:49.947002Z digest=sha256:ab6d30c508d8bd5fb777a8cf4d3df1c3b1d482871038ee5797c3937bdbb2251a