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Paper Citation Record · LEDGER

An Online-Learning Approach to Inverse Optimization

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1810.12997.

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

pith.paper-citation-record.v1
1810.12997 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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:55:50.960830Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T08:57:38.634225Z

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 b0adb9fc-4e51-4551-8d3e-8d66a7a79efb · inbound

Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis cites this paper.

Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis An Online-Learning Approach to Inverse Optimization

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:50.960830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:55:50.960830Z digest=sha256:956db7fba8e98b7048331360303a7026eb35a426d96e7de869d3bcc692dd9dd9

Observation 36d833de-2567-4dfe-8b0f-54c154564085 · inbound

Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets cites this paper.

Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets An Online-Learning Approach to Inverse Optimization

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:57:38.635975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T08:56:27.405530Z digest=sha256:20684d5036e9faf2eb11f02c45cc165134b7fd1a0125bc187dd4837f5e8dc78e