Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2006.08796.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:21:48.168027Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T10:49:56.898855Z
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 2f451310-e881-453f-8d2f-0501d3f1000c · inbound
SGS-GNN: A Supervised Graph Sparsification method for Graph Neural Networks cites this paper.
SGS-GNN: A Supervised Graph Sparsification method for Graph Neural Networks Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T19:05:45.927784Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fd322528-0ec1-4afe-ae06-375d46c4f27b · inbound
Towards Understanding Deep Learning Model in Image Recognition via Coverage Test cites this paper.
Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:21:48.168027Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19c21e2e-1203-4cd4-8cfe-d616f256c5ac · inbound
NFTDELTA: Detecting Permission Control Vulnerabilities in NFT Contracts through Multi-View Learning cites this paper.
NFTDELTA: Detecting Permission Control Vulnerabilities in NFT Contracts through Multi-View Learning Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T10:49:56.900996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.