Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2012.11701.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:32:29.413824Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T10:32:30.464924Z
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 bbfbcca7-e0f3-48fa-9807-1a3e0f9bdb7e · inbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair cites this paper.
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data
Reference 14
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T10:32:30.468168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a01ea820-1fa3-4dec-a9d8-76853123c350 · inbound
Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus cites this paper.
Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T20:30:10.166113Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.