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Paper Citation Record · LEDGER

Biomedical knowledge graph-optimized prompt generation for large language models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2311.17330.

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

pith.paper-citation-record.v1
2311.17330 v2

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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:12.719085Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:26:59.000740Z

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 2367fb67-d7f7-40c6-8070-c11d285b9d5b · inbound

SlimRAG: Retrieval without Graphs via Entity-Aware Context Selection cites this paper.

SlimRAG: Retrieval without Graphs via Entity-Aware Context Selection Biomedical knowledge graph-optimized prompt generation for large language models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:12.719085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:42:12.719085Z digest=sha256:eb1a59ed1e970394ef77d84c3dbc85b57dc6369339446959cdecc4d80b1a7740

Observation e7bf5877-1faf-4467-96b1-34f7f8edbd3d · inbound

MultiCNKG: Integrating Cognitive Neuroscience, Gene, and Disease Knowledge Graphs Using Large Language Models cites this paper.

MultiCNKG: Integrating Cognitive Neuroscience, Gene, and Disease Knowledge Graphs Using Large Language Models Biomedical knowledge graph-optimized prompt generation for large language models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-04T11:08:59.930998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:08:59.930998Z digest=sha256:d1ee837b014b53b0440a85cd5bfd21a9da1cc5fce0a4c4c8a1f48db36744206b

Observation 602bd3e0-a925-4041-9ea3-df95ba946d30 · inbound

Format-Constraint Coupling in Knowledge Graph Construction from Statistical Tables cites this paper.

Format-Constraint Coupling in Knowledge Graph Construction from Statistical Tables Biomedical knowledge graph-optimized prompt generation for large language models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-22T06:44:42.014006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-22T06:43:31.886617Z digest=sha256:b8322e60e7bafaf34e458f37c10b36d282bd80a36cc2dd242f0a2319878a2f8e

Observation 8125fe3d-a8c3-4148-9627-047bd2e1f033 · inbound

Beyond Vector Similarity: A Structural Analysis of Graph-Augmented Retrieval for Industrial Knowledge Graphs cites this paper.

Beyond Vector Similarity: A Structural Analysis of Graph-Augmented Retrieval for Industrial Knowledge Graphs Biomedical knowledge graph-optimized prompt generation for large language models

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T13:26:59.002236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T01:19:33.405517Z digest=sha256:f528661d2cb32be0b7c82b40148d6131285f73575c46b95b19ff8743602c7e0d

Observation 55f5a50f-fe70-4ad6-ae70-316667b95fe4 · inbound

Faithful by Design: Evaluating and Improving LLM-Generated Clinical Trial Summaries for Multi-Stakeholder Audiences cites this paper.

Faithful by Design: Evaluating and Improving LLM-Generated Clinical Trial Summaries for Multi-Stakeholder Audiences Biomedical knowledge graph-optimized prompt generation for large language models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-14T14:31:03.141695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T14:31:03.141695Z digest=sha256:43fd8cd2bd033c96e28989012e70442e9c7b68b4af6d9abe176ef64b9e7e6550