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Paper Citation Record · LEDGER

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts

As of 16 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:1908.02286.

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

pith.paper-citation-record.v1
1908.02286 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:58:29.823657Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 482264c1-dc6f-4eb7-9e6e-d55a304cb36a · outbound

This paper cites Recent automatic text summarization techniques: a survey,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Recent automatic text summarization techniques: a survey,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.815348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation d26a6523-2743-4ed4-aea7-845f65084205 · outbound

This paper cites CIBS: A biomedical text summarizer using topic -based sentence clustering,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts CIBS: A biomedical text summarizer using topic -based sentence clustering,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.799312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 424103b5-5524-4318-8278-8d687546eb76 · outbound

This paper cites Different approaches for identifying important concepts in probabilistic biomedical text summarization,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Different approaches for identifying important concepts in probabilistic biomedical text summarization,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.785955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 98e102ae-2b3f-4eea-8a50-6702e464bd9a · outbound

This paper cites Text summarization in the biomedical domain: a systematic review of recent research,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Text summarization in the biomedical domain: a systematic review of recent research,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.657820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:58:29.333285Z digest=sha256:eed569a70e31ad73a8c3b4e76e3ddca082cb68545629ec2a3d4935d58bb4a32e

Observation 868fd9d8-f340-432f-af49-1d12a54a01c3 · outbound

This paper cites A semantic graph-based approach to bi omedical summarisation,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts A semantic graph-based approach to bi omedical summarisation,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.544831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:58:29.338399Z digest=sha256:017628622cacff07bb4c518820a5faa5b5c148cd8e414f1b558bbe7b5f4a7d5e

Observation 1ecc2348-2f73-4e25-a181-5b106554b8f2 · outbound

This paper cites Quantifying the informativeness for biomedical literature summarization: An itemset mining method,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Quantifying the informativeness for biomedical literature summarization: An itemset mining method,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.529419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:58:29.429976Z digest=sha256:9328357e9323998223f2bb633ef9bdae98ee248e82ce3d4673158e8965ad23be

Observation 2a863071-692f-4782-95b8-fbc19e1f9764 · outbound

This paper cites Frequent Itemsets as Meaningful Events in Graphs for Summarizing Biomedical Texts,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Frequent Itemsets as Meaningful Events in Graphs for Summarizing Biomedical Texts,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.514738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:58:29.519386Z digest=sha256:484f7561a7a9447ba7d9536aadcee7698f56b4a95c949d8ed239a0e3b1a14b7e

Observation 313403a4-e303-45a5-bf44-d4cf1bcb3353 · outbound

This paper cites Co ncept-based single - and multi-document biomedical text summarization,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Co ncept-based single - and multi-document biomedical text summarization,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.498504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:58:29.555701Z digest=sha256:0402d4516f5767b9a28f7fd62d0864f04263e6de1b876d2d8ee3080f00fedbbe

Observation 5f3d1879-e33e-47ec-8992-12c967dda524 · outbound

This paper cites Application of text mining in the biomedical domain,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Application of text mining in the biomedical domain,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.282473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 84866d9f-270b-4209-9aba-d972024c85ed · outbound

This paper cites Word representations: a simple and general method for semi -supervised learning,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Word representations: a simple and general method for semi -supervised learning,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.261332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7511c9cc-3c9e-49b4-9aed-c9aec7b09f43 · outbound

This paper cites Semi-supervised sequence tagging with bidirectional language models.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Semi-supervised sequence tagging with bidirectional language models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-14T14:58:29.567847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b949b317-8aa7-4077-80b2-4930bd6de9e6 · outbound

This paper cites Improving language understanding by generative pre-training,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Improving language understanding by generative pre-training,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.196490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 2bf2002e-79ff-4884-9593-aecd82a73278 · outbound

This paper cites Deep contextualized word representations.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Deep contextualized word representations

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T14:58:29.576939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:58:29.576939Z digest=sha256:cbd51c4b6f249cf8dceecd5ac2394bef1ce01e0b5549d6e79c1daee00d0cf41a

Observation 75edf69f-e269-4265-8fed-137495ff47d8 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-14T14:58:29.621581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:58:29.621581Z digest=sha256:0eaddbcce97ef0a8552d75054df447f7b789e0ca41d894fa546c2ff11ba8746e

Observation f4f39ca4-2346-4061-b40c-e77d4bf3544c · outbound

This paper cites Looking for a few good metrics: Automatic summarization evaluation -how many samples are enough?,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts Looking for a few good metrics: Automatic summarization evaluation -how many samples are enough?,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:30.067189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:58:29.740695Z digest=sha256:64955b331839b59d7505ca84db5d536621d4976e2d8300c60e8751d5c0b50391

Observation 946d6f3e-7ea9-48b3-a3bf-e2ae722799fa · outbound

This paper cites SUMMA: A robust and adaptable summarization tool,.

Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts SUMMA: A robust and adaptable summarization tool,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:58:29.995197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Pith citing papers

No inbound Pith citation observations are available.