Paper Citation Record · LEDGER

Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2209.11469.

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

pith.paper-citation-record.v1
2209.11469 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:59:32.961771Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:05:15.210614Z

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 8d474f35-8869-462b-8d54-3ccb80ff5025 · inbound

Towards Macro-AUC oriented Imbalanced Multi-Label Continual Learning cites this paper.

Towards Macro-AUC oriented Imbalanced Multi-Label Continual Learning Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T04:59:32.961771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfa0c2c7-0359-473a-9020-7a415ae6a3fd · inbound

Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning cites this paper.

Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T22:56:48.535504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eae55ff-d366-4707-9703-c49ca6480735 · inbound

Online Continual Learning: A Systematic Literature Review of Approaches, Challenges, and Benchmarks cites this paper.

Online Continual Learning: A Systematic Literature Review of Approaches, Challenges, and Benchmarks Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T21:26:04.326787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbd9e397-9f50-4fb6-96e2-fedf69e6d075 · inbound

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning cites this paper.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:43.235747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 149b1247-44ea-4016-871e-7c3fff76a3ec · inbound

L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning cites this paper.

L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:05:15.345953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a3193732-eeda-482e-b8e2-bbc5f5a967c2 · inbound

DeCLIP: Decoupled Prompting for Multi-Label Class-Incremental Learning with CLIP cites this paper.

DeCLIP: Decoupled Prompting for Multi-Label Class-Incremental Learning with CLIP Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:00.613209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.