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Paper Citation Record · LEDGER

Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.09327.

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

pith.paper-citation-record.v1
2402.09327 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:08:57.275663Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T06:15:59.164578Z

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 89d0b8c9-37f5-4fad-afc5-bfc94d30165e · inbound

A Lightweight Method to Disrupt Memorized Sequences in LLM cites this paper.

A Lightweight Method to Disrupt Memorized Sequences in LLM Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T20:08:57.275663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:08:57.275663Z digest=sha256:f3ab432afbf7db4b9a50624c4554d48a8489870710054e27f97095b6d949fc0a

Observation 9757a501-e865-4b83-96d9-6bca12f90fc4 · inbound

Lower Bounds for Public-Private Learning under Distribution Shift cites this paper.

Lower Bounds for Public-Private Learning under Distribution Shift Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T14:56:03.906871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:56:03.906871Z digest=sha256:b069edba5ca2a1677749fffab626a4754a79a69a4dd5dd6a453ebc689ef68816

Observation d5cd5cde-afc1-4784-bc59-a4b2b0b59e78 · inbound

Is your algorithm unlearning or untraining? cites this paper.

Is your algorithm unlearning or untraining? Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:30:59.279716Z

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=2026-05-10T18:06:08.962042Z digest=sha256:ebca13967115daaa82dd84f16f2239f1141eb3c75a058ed600f38a98a67fbcae

Observation ac394751-4551-4077-90bb-27bdf6ff6b42 · inbound

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts cites this paper.

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:15:59.168795Z

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=arxiv_source observed=2026-05-10T17:42:31.465077Z digest=sha256:24ff5aa6db9bf23b489ffb95101a0127c50e409a16aea52a28b6028cb3777ebb

Observation dc1b8b78-18a6-44f6-a55d-f07aa0abdfc0 · inbound

The Fourth Quadrant: A Stylized View of Benign Misfitting cites this paper.

The Fourth Quadrant: A Stylized View of Benign Misfitting Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T00:43:05.484211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:43:05.484211Z digest=sha256:4fead31df22e95197fde3437fe6a7db2906d41ac4552789c70937d06dedd2a18