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Paper Citation Record · LEDGER

Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.02328.

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

pith.paper-citation-record.v1
2402.02328 v3

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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:39:32.738064Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:19:55.279222Z

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 779eaec1-77ad-4622-abae-85defec9869a · inbound

Approximating the Gomory Mixed-Integer Cut Closure Using Historical Data cites this paper.

Approximating the Gomory Mixed-Integer Cut Closure Using Historical Data Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T14:39:32.738064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:39:32.738064Z digest=sha256:d43b513d66a8dab87dd4192870dce2adef103710b149e771ddd414a5bc037cc7

Observation dc4a4fe9-4463-497d-8ea4-db2f2d2ee976 · inbound

How hard is learning to cut? Trade-offs and sample complexity cites this paper.

How hard is learning to cut? Trade-offs and sample complexity Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:19:55.338608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-07T12:19:53.628634Z digest=sha256:c52718f5676bbc494cbaecbcc57bb71367c8d484860be3dfde49754f737337d7