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Paper Citation Record · LEDGER

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

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 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 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:59:45.336692Z

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:f07e59a14179c58d7fee6eb3e4dfe5fb2f608b416849e9a3fbe41b4ed3437342

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=sha256:6de478b0a715c209d4f7147bcb552298b5efb12c00c79ceceeb794f34a50c3e7

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:ee3f1d84aaa41ecabd55b9fb9dac6bdc4d3d0b66876efd194fda8afcc60b6c7d

Observation 06c8aaa4-a7c8-433f-98af-4c5df5e85230 · inbound

Uncovering Conspiratorial Narratives within Arabic Online Content cites this paper.

Uncovering Conspiratorial Narratives within Arabic Online Content A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T11:59:45.336692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:59:45.336692Z digest=sha256:2ca731e23d129faacde5fbcbd45d1d8c3ec7d71e5d6d229aaae04f30fd4e1223

Observation 35e727f9-53b3-4a6a-affb-e1654dc3028e · inbound

Towards DS-NER: Unveiling and Addressing Latent Noise in Distant Annotations cites this paper.

Towards DS-NER: Unveiling and Addressing Latent Noise in Distant Annotations A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T20:38:33.324761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:33.324761Z digest=sha256:572e9e909290f8c8346625e1a7478d476d3a2f9260568e0b71c9821998efcb36

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=sha256:585cd7a1c1df1b43cdc8b19b8e1234a3058c59ed3562334c657e8ac76c2187d0

Observation 51d1d131-7522-4a53-9796-f6a41f418394 · inbound

A Survey on Retrieval And Structuring Augmented Generation with Large Language Models cites this paper.

A Survey on Retrieval And Structuring Augmented Generation with Large Language Models A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

Reference 270

Resolution
unresolved
no resolver link, observed 2026-08-15T15:56:22.285141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:56:22.285141Z digest=sha256:4ec8eecfd99f4a06211baa36da5d379f56eab1bda728438c1b1b93f2d7c2c00b

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-08T16:49:52.020897Z digest=sha256:a16440511319c687a61493ffbf608de1df1efca03a8619691b2b9e0a8ebea78b