Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1804.06987.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T00:35:28.309660Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-04T09:19:42.861792Z
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 0af48f9f-9463-405e-a665-2e149d1eb158 · inbound
Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis cites this paper.
Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T00:35:28.309660Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a4710026-c0f4-4296-843e-797fa374f7e6 · inbound
Sub-Billion, Super-Frontier: Small Language Models Rival Zero-Shot Frontier LLMs on General and Literary Relation Extraction cites this paper.
Sub-Billion, Super-Frontier: Small Language Models Rival Zero-Shot Frontier LLMs on General and Literary Relation Extraction Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention
Reference 239
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T09:19:42.862963Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.