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Paper Citation Record · LEDGER

A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1910.11470.

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

pith.paper-citation-record.v1
1910.11470 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:56:49.478988Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

468
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c51f0c95-5861-46bc-8ba0-4b8866f24792 · inbound

A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala cites this paper.

A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-11T23:56:49.478988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:56:49.478988Z digest=sha256:a89c2277c0be6b29045b01d22a066e2bfc787da8bdd47e17ee26726c450666c4

Observation 989a7b9e-c66f-4527-bc89-7bf2ed3d981d · inbound

GerPS-Compare: Comparing NER methods for legal norm analysis cites this paper.

GerPS-Compare: Comparing NER methods for legal norm analysis A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T23:31:15.914860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:31:15.914860Z digest=sha256:7a411616be6807ea50cb46bc12de4513dfc229ba386f258c51e8c0230550a85f

Observation 3f64d412-f078-45ed-b0b0-8b11d9f5348d · inbound

The Use of Artificial Intelligence in Military Intelligence: An Experimental Investigation of Added Value in the Analysis Process cites this paper.

The Use of Artificial Intelligence in Military Intelligence: An Experimental Investigation of Added Value in the Analysis Process A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T22:33:53.120938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:33:53.120938Z digest=sha256:14eff41c0c72ac23c436a8202dd4bcb5ae1fbb4e50ec03759f33fc920fbe0792

Observation 8aae71c5-fcb8-4182-bdda-a19651598686 · inbound

BYOKG-RAG: Multi-Strategy Graph Retrieval for Knowledge Graph Question Answering cites this paper.

BYOKG-RAG: Multi-Strategy Graph Retrieval for Knowledge Graph Question Answering A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T19:59:58.064288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:59:58.064288Z digest=sha256:2961f35aa89fdac7d3fa4c1dbe4b322d0b06bcdaebd53ef64f5c651211a96510

Observation 225a76d4-597b-422d-97dd-1676d895bbe9 · inbound

A Hybrid Method for Low-Resource Named Entity Recognition cites this paper.

A Hybrid Method for Low-Resource Named Entity Recognition A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-08T16:50:03.292592Z

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.

source=pdf_text observed=2026-05-08T16:49:52.020897Z digest=sha256:dbe6f6641308f6bd2235df7d0f3ec985613ab3284216692e91ba07bbeb908b8d