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Paper Citation Record · LEDGER

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

As of 18 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 2026-08-18T06:34:40.430872+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=sha256:9ce7f0179c8bb9e953950754b250f711037f0111af29a8ad498382b840807dee

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=sha256:4c289761f0a3cdf2481dabf9ea95f47646a2212d743d61719a82e1f27df07091

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:e008014e4b676bb1aa49fbc3e04e6da99921fcccf9cb00c838331e7d9d4c8229

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=sha256:74904ebb1c1a01759f3cede5bcb66b556fc436ea5d805e02a3db43cd3d4d8709

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:cf0385db47bfed865b8c2a13e0e3b2f565ddc85a126344bfb39b256c3b3836f1

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=sha256:821b7f4c7c70a1800a0fed8a2352ef1db843d3d855a909717d15f7957d58166a

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:ca32934ec400d976110e82bba83a761accd139bba5a4c59ab889b1f4b0b385c2

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-08T16:49:52.020897Z digest=sha256:1c7dacd0df509a545629211c89922eafa3c497f9bb5d278ff3e9b060c1eb770e