Paper Citation Record · LEDGER

Attention Guided Graph Convolutional Networks for Relation Extraction

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1906.07510.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1906.07510 v8

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:04:31.516220Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-10T05:56:11.424693Z

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 63493317-bee6-4ec6-8b40-a872626502e7 · inbound

NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction cites this paper.

NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction Attention Guided Graph Convolutional Networks for Relation Extraction

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T05:04:31.516220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb17cfa6-ff74-4229-a1b6-c7e343b20873 · inbound

Scaling Large-scale GNN Training to Thousands of Processors on CPU-based Supercomputers cites this paper.

Scaling Large-scale GNN Training to Thousands of Processors on CPU-based Supercomputers Attention Guided Graph Convolutional Networks for Relation Extraction

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T13:45:10.464061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efcff6d3-7aaa-4313-802c-8ffbf7074bd7 · inbound

A Pluggable Multi-Task Learning Framework for Sentiment-Aware Financial Relation Extraction cites this paper.

A Pluggable Multi-Task Learning Framework for Sentiment-Aware Financial Relation Extraction Attention Guided Graph Convolutional Networks for Relation Extraction

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T00:55:30.563418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97e67648-fe60-42d4-a6eb-ae3f3411c490 · inbound

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval cites this paper.

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval Attention Guided Graph Convolutional Networks for Relation Extraction

Reference 277

Resolution: verified exact; arxiv_id, observed 2026-05-10T05:56:11.425935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.