Pith. sign in

Paper Citation Record · LEDGER

A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.18988.

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

pith.paper-citation-record.v1
2310.18988 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:44:48.961883Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:35:43.106228Z

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 37d494aa-f891-4533-a94e-768fce59f061 · inbound

ESS-ReduNet: Enhancing Subspace Separability of ReduNet via Dynamic Expansion with Bayesian Inference cites this paper.

ESS-ReduNet: Enhancing Subspace Separability of ReduNet via Dynamic Expansion with Bayesian Inference A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-12T11:44:48.961883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:44:48.961883Z digest=sha256:7067103c4736b49f39e4725dd8778a0c349380b0175c69cec2701a542a10bbcd

Observation af3697ee-27bb-45a3-a3a7-20ae3cfe1576 · inbound

How much do language models memorize? cites this paper.

How much do language models memorize? A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:35:43.210795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-07T12:35:37.350051Z digest=sha256:39e2349e32fd1fd2a9092097e75d9953cb0d248b5cee31e75867a1608b8feb6e