Pith. sign in

Paper Citation Record · LEDGER

Efficient Representations for High-Cardinality Categorical Variables in Machine Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2501.05646.

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

pith.paper-citation-record.v1
2501.05646 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:25:34.793120Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T06:05:34.639907Z

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 9f6cd03b-125b-4c55-bf4e-1294f9916571 · inbound

What's on My Network? Using Large Language Models to Identify Real-World IoT Devices at Scale cites this paper.

What's on My Network? Using Large Language Models to Identify Real-World IoT Devices at Scale Efficient Representations for High-Cardinality Categorical Variables in Machine Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T15:25:34.793120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T15:25:34.793120Z digest=sha256:f61d3e9cfe202f91e10616f5bbd7928ded229ffa4810ea02b7478c9025008529

Observation 854c5ac2-ce29-4768-93b3-b86cf1854560 · inbound

Evaluating Tabular Representation Learning for Network Intrusion Detection cites this paper.

Evaluating Tabular Representation Learning for Network Intrusion Detection Efficient Representations for High-Cardinality Categorical Variables in Machine Learning

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:05:34.641556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T19:02:57.094306Z digest=sha256:0a6ab6687ba16afd5f07ac29e7f15ad97c2f929294e1beb1222a378d2492c0bb