Paper Citation Record · LEDGER

Weighted Ensemble Models Are Strong Continual Learners

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2312.08977.

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

pith.paper-citation-record.v1
2312.08977 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:20:41.243663Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T00:20:51.989347Z

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 65afe5a5-ea5e-41f1-bed0-b66e88bfffbb · inbound

Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations cites this paper.

Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations Weighted Ensemble Models Are Strong Continual Learners

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:41.243663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de520aba-25b8-44ca-a22f-885d4716141d · inbound

CKAA: Cross-subspace Knowledge Alignment and Aggregation for Robust Continual Learning cites this paper.

CKAA: Cross-subspace Knowledge Alignment and Aggregation for Robust Continual Learning Weighted Ensemble Models Are Strong Continual Learners

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T18:00:20.660701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6d013e9-92e1-4a65-9c04-bba5e3432a6c · inbound

Continual Learning via Ensemble-Based Depth-Wise Masked Autoencoders for Data Quality Monitoring in High-Energy Physics cites this paper.

Continual Learning via Ensemble-Based Depth-Wise Masked Autoencoders for Data Quality Monitoring in High-Energy Physics Weighted Ensemble Models Are Strong Continual Learners

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T19:26:49.984515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f162a1db-a164-4a11-b63e-7059f201adfa · inbound

Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogies cites this paper.

Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogies Weighted Ensemble Models Are Strong Continual Learners

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:20:51.992717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.