Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Strongly Incremental Constituency Parsing with Graph Neural Networks
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2010.14568.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T05:40:20.059398Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-12T05:40:20.196978Z
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 0ab06f00-2f58-44ab-b08f-a4466940aced · inbound
Train Once for All: A Transitional Approach for Efficient Aspect Sentiment Triplet Extraction cites this paper.
Train Once for All: A Transitional Approach for Efficient Aspect Sentiment Triplet Extraction Strongly Incremental Constituency Parsing with Graph Neural Networks
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T05:40:20.202291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.