Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Online Continual Learning with Maximally Interfered Retrieval
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1908.04742.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:55:28.085440Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-04T22:32:18.086830Z
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 aaf4e3bc-b302-44ce-8ff0-90b97b8340a5 · inbound
GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning cites this paper.
GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Online Continual Learning with Maximally Interfered Retrieval
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:55:28.085440Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05b1222c-39d8-4797-8a07-e6d494513ae5 · inbound
Class Incremental Continual Learning with Self-Organizing Maps and Variational Autoencoders Using Synthetic Replay cites this paper.
Class Incremental Continual Learning with Self-Organizing Maps and Variational Autoencoders Using Synthetic Replay Online Continual Learning with Maximally Interfered Retrieval
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:31:11.752724Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ffcdcdf-1d7f-4608-9657-2e8eccc28713 · inbound
MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models cites this paper.
MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Online Continual Learning with Maximally Interfered Retrieval
Reference 43
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-04T22:32:18.092940Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.