Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Rethinking Distribution Shifts: Empirical Analysis and Modeling for Tabular Data
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2307.05284.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T12:33:05.552147Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T12:45:46.787657Z
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 61f1ede8-be20-4cac-886d-fbb3fe535545 · inbound
Distributionally Robust Policy Learning under Concept Drifts cites this paper.
Distributionally Robust Policy Learning under Concept Drifts Rethinking Distribution Shifts: Empirical Analysis and Modeling for Tabular Data
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:33:05.552147Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc8d3394-c9dd-4b5f-a55c-cba5a2196d03 · inbound
Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning cites this paper.
Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning Rethinking Distribution Shifts: Empirical Analysis and Modeling for Tabular Data
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:19:19.554178Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06e5ce70-db75-416f-9802-dc13fcad6ee5 · inbound
DRO: A Python Library for Distributionally Robust Optimization in Machine Learning cites this paper.
DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Rethinking Distribution Shifts: Empirical Analysis and Modeling for Tabular Data
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T12:45:46.871235Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.