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Paper Citation Record · LEDGER

How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domain

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2307.00186.

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

pith.paper-citation-record.v1
2307.00186 v2

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 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:19:56.180590Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:59:58.852277Z

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 f724ab19-b616-41c4-8a42-3bf0c1ce5e2a · inbound

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition cites this paper.

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domain

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:43:25.525895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-23T20:40:09.530799Z digest=sha256:427f38574751319745856dbe1077433989fac72313f57b7ba835a4c2deea4a6e

Observation 4f640390-1286-4e48-b31e-4bf0f7cf070e · inbound

Token and Span Classification for Entity Recognition in French Historical Encyclopedias cites this paper.

Token and Span Classification for Entity Recognition in French Historical Encyclopedias How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domain

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T11:19:56.180590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:19:56.180590Z digest=sha256:e989c7b580fa56afe3f8794e874a561c948066a6b7d6bb458a12b3f816b6b576

Observation b2b69d52-bfe2-4496-9952-7f9318b3f0a8 · inbound

Extracting OPQRST in Electronic Health Records using Large Language Models with Reasoning cites this paper.

Extracting OPQRST in Electronic Health Records using Large Language Models with Reasoning How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domain

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T12:11:03.937755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T12:11:03.937755Z digest=sha256:21e66b9e4784e6d2c8c6945e176acc97c758a5a2bf30d62d18e6294ee6c630a9

Observation a3422938-c6a6-4ca4-aae0-5ebaa0b9fea2 · inbound

Task Decomposition for Efficient Annotation cites this paper.

Task Decomposition for Efficient Annotation How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domain

Reference 166

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:59:58.854081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T00:00:16.588823Z digest=sha256:3c64731cf0e170341fbba8293ede02169c8964e5986c1212c6940dfff461d91d