Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2303.07338.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T15:34:40.707494Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T18:08:18.750202Z
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 670af31b-6005-45f3-98cb-30ecdf0c32d1 · inbound
Sparse Orthogonal Parameters Tuning for Continual Learning cites this paper.
Sparse Orthogonal Parameters Tuning for Continual Learning Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T18:08:18.752885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2cb71b29-f481-48fe-b9d4-b4ffeb6441f8 · inbound
PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning cites this paper.
PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:34:40.707494Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c18ceeb0-4541-4a38-aecd-32feef747dcd · inbound
On the Generalization and Adaptation Ability of Machine-Generated Text Detectors in Academic Writing cites this paper.
On the Generalization and Adaptation Ability of Machine-Generated Text Detectors in Academic Writing Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:44:06.417154Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6bef14b2-15ad-429c-a16e-f4566b5d4073 · inbound
ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think cites this paper.
ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:41:42.424676Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cad88f8-44f8-4119-9131-a821ec45a442 · inbound
MSA at BEA 2025 Shared Task: Disagreement-Aware Instruction Tuning for Multi-Dimensional Evaluation of LLMs as Math Tutors cites this paper.
MSA at BEA 2025 Shared Task: Disagreement-Aware Instruction Tuning for Multi-Dimensional Evaluation of LLMs as Math Tutors Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:32:35.258946Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.