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Paper Citation Record · LEDGER

Replay to Remember (R2R): An Efficient Uncertainty-driven Unsupervised Continual Learning Framework Using Generative Replay

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2505.04787.

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

pith.paper-citation-record.v1
2505.04787 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T23:12:11.283075Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T23:14:01.243262Z

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 ff639f10-ff7b-4449-bcfc-f4e295399ec9 · inbound

AIFIND: Artifact-Aware Interpreting Fine-Grained Alignment for Incremental Face Forgery Detection cites this paper.

AIFIND: Artifact-Aware Interpreting Fine-Grained Alignment for Incremental Face Forgery Detection Replay to Remember (R2R): An Efficient Uncertainty-driven Unsupervised Continual Learning Framework Using Generative Replay

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-10T08:58:12.957873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T08:53:13.455361Z digest=sha256:6e3fae6fb3d69d9e4953fa3d0a0ae090505552d5500a0d00a3b14663b65a67e0

Observation 52d706d3-4c3e-4a4f-86ac-5ff8457770bf · inbound

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning cites this paper.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Replay to Remember (R2R): An Efficient Uncertainty-driven Unsupervised Continual Learning Framework Using Generative Replay

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:14:01.244995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T23:12:11.283075Z digest=sha256:1a7d3ac43b35af23f66eee1bcb7d3578cf61fa29b0e4b218e3bb0ceb42d25499