Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Not All Data Matters: An End-to-End Adaptive Dataset Pruning Framework for Enhancing Model Performance and Efficiency
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.05599.
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 2026-08-06T22:46:00.186939Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T16:45:04.753892Z
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 a5d31db3-065d-4aa1-8875-1f47896ec3e3 · inbound
RL-Selector: Reinforcement Learning-Guided Data Selection via Redundancy Assessment cites this paper.
RL-Selector: Reinforcement Learning-Guided Data Selection via Redundancy Assessment Not All Data Matters: An End-to-End Adaptive Dataset Pruning Framework for Enhancing Model Performance and Efficiency
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:46:00.186939Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b12a6b9b-c675-4cd0-8011-8276fc08becb · inbound
Multimodal-Guided Dynamic Dataset Pruning for Robust and Efficient Data-Centric Learning cites this paper.
Multimodal-Guided Dynamic Dataset Pruning for Robust and Efficient Data-Centric Learning Not All Data Matters: An End-to-End Adaptive Dataset Pruning Framework for Enhancing Model Performance and Efficiency
Reference 18
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T16:45:04.891872Z
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.