Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2102.02887.
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 2026-08-07T14:44:18.767822Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T06:34:01.144081Z
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 482c5d6b-2cb0-49da-bb04-d671f422c8ac · inbound
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs cites this paper.
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T06:34:01.146379Z
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.
Observation 82285b37-8be4-4244-a883-9675835242b6 · inbound
NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling cites this paper.
NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:44:18.767822Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.