Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Meta Mirror Descent: Optimiser Learning for Fast Convergence
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.02711.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T17:35:46.255291Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T18:35:59.114010Z
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 2e51fcfe-df6d-4316-8917-56b6b481fa62 · inbound
Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning cites this paper.
Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta Mirror Descent: Optimiser Learning for Fast Convergence
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:35:46.255291Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bcb18031-2c65-428c-b8dc-48d3a6e50c6c · inbound
Learnable Loss Geometries with Mirror Descent for Scalable and Convergent Meta-Learning cites this paper.
Learnable Loss Geometries with Mirror Descent for Scalable and Convergent Meta-Learning Meta Mirror Descent: Optimiser Learning for Fast Convergence
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:45:39.016680Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 76c62ca0-37c4-4e3a-b860-a83f36bda7b7 · inbound
Non-Linear Strategic Classification Made Practical cites this paper.
Non-Linear Strategic Classification Made Practical Meta Mirror Descent: Optimiser Learning for Fast Convergence
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T18:35:59.115271Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.