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Paper Citation Record · LEDGER

Towards Omni-RAG: Comprehensive Retrieval-Augmented Generation for Large Language Models in Medical Applications

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.02460.

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

pith.paper-citation-record.v1
2501.02460 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:41:52.878541Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:42:43.121218Z

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 0c98647c-cbd7-46ca-b150-0a20222fab6c · inbound

POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications cites this paper.

POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications Towards Omni-RAG: Comprehensive Retrieval-Augmented Generation for Large Language Models in Medical Applications

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T11:41:52.878541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:41:52.878541Z digest=sha256:fd71afadad713cfa426bdf9b04f2fd9729b1f53cd9dc28bce403e30d445caa6e

Observation cad576ed-a261-4e72-9545-3c08f6bdcff9 · inbound

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models cites this paper.

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models Towards Omni-RAG: Comprehensive Retrieval-Augmented Generation for Large Language Models in Medical Applications

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:42:43.124696Z

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=2026-08-06T16:42:22.955677Z digest=sha256:9a8a79928e4c640b3834fc0d31486d7cfb7402f6e2a662ea53f41404df11bb6b

Observation f4191ccf-a891-4289-8ebd-a5be5dd8f057 · inbound

RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation cites this paper.

RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation Towards Omni-RAG: Comprehensive Retrieval-Augmented Generation for Large Language Models in Medical Applications

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T17:54:29.137189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:54:29.137189Z digest=sha256:970d0e17ea766dd3685e1698808b6767c541e4bff63dd7c5f96e9ef4296a39de