Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Pruning Foundation Models for High Accuracy without Retraining
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.15567.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T18:53:06.660997Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T13:10:06.560526Z
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 98afd9ea-93dc-4699-aa52-80f8dbe7376f · inbound
F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics cites this paper.
F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics Pruning Foundation Models for High Accuracy without Retraining
Reference 93
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:53:06.660997Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation de9973e7-f742-483a-81ab-dc2e73cc6ed6 · inbound
Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation cites this paper.
Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation Pruning Foundation Models for High Accuracy without Retraining
Reference 65
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T13:10:06.691603Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.