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Paper Citation Record · LEDGER

Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2309.02233.

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

pith.paper-citation-record.v1
2309.02233 v4

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 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:22:11.958325Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T11:52:16.125231Z

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 4504b4b3-4587-4b45-9c15-31685214653f · inbound

COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation cites this paper.

COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-11T05:22:11.958325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:22:11.958325Z digest=sha256:a8952069df898291bc887748e5f317a22d21852f4da4aebfec8107484d72b4d3

Observation 814adf65-71dd-4d0a-b1c4-b592457988cd · inbound

GANQ: GPU-Adaptive Non-Uniform Quantization for Large Language Models cites this paper.

GANQ: GPU-Adaptive Non-Uniform Quantization for Large Language Models Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T16:39:33.103957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:39:33.103957Z digest=sha256:bb0f264c8767e9f9e8d3b080b8454c5b1fdea6175c58a6c3e32cc4ce640234f9

Observation 13b0ab83-0d73-4a07-9a24-2f0e5b7d8065 · inbound

K-COMP: Retrieval-Augmented Medical Domain Question Answering With Knowledge-Injected Compressor cites this paper.

K-COMP: Retrieval-Augmented Medical Domain Question Answering With Knowledge-Injected Compressor Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T15:54:42.727002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:54:42.727002Z digest=sha256:3272fcb829a5fd12f39046d2faa6a7242470616faba9f6260f0df827a984ce07

Observation 9a176afc-2f8f-42d0-85d7-089391535398 · inbound

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems cites this paper.

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering

Reference 187

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:52:16.127437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-19T11:49:36.574471Z digest=sha256:404234cb1862e8dee858935897663f6a9969ff09a64feb9c9b14c15ae519ec87

Observation 5e38a408-890c-4312-97c0-1818f3530a5b · inbound

Domain Fine-Tuning vs. Retrieval-Augmented Generation for Medical Multiple-Choice Question Answering: A Controlled Comparison at the 4B-Parameter Scale cites this paper.

Domain Fine-Tuning vs. Retrieval-Augmented Generation for Medical Multiple-Choice Question Answering: A Controlled Comparison at the 4B-Parameter Scale Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:16:12.799134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-08T06:14:04.532308Z digest=sha256:595d4f64c5587d04b2e5ac6288103edfee62e895b3f1a153756cdea1a0e43f47