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Paper Citation Record · LEDGER

LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2501.05464.

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

pith.paper-citation-record.v1
2501.05464 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:26:28.866002Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T04:26:37.983125Z

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 10bb5225-3e6f-45bf-ad53-76867a54c702 · inbound

ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Images cites this paper.

ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Images LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T17:26:28.866002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:26:28.866002Z digest=sha256:d9420aede7854ec511554d0e3fdfa2f8a43717f9ba2dd1374715b5b5ba240426

Observation 9a0cb9bf-ae94-4c1c-9080-b579905d9524 · inbound

PRL: Prompts from Reinforcement Learning cites this paper.

PRL: Prompts from Reinforcement Learning LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T14:26:40.377512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T14:25:22.002977Z digest=sha256:405fc19423d4f93ab537df634eeb8b394fd3a747e1c47a146f5e7feb81fd7f3e

Observation d4c5c0cd-0860-4158-bdfc-d55305e017b4 · inbound

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment cites this paper.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T11:32:34.774825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:32:34.774825Z digest=sha256:536c0580dd1747af7b682291bd413e16ef2eb5bd6b893cf928f1444063f57dd1

Observation 93b52ef7-c7ba-49e6-9e66-bd4ccee1a962 · inbound

TreeReview: A Dynamic Tree of Questions Framework for Deep and Efficient LLM-based Scientific Peer Review cites this paper.

TreeReview: A Dynamic Tree of Questions Framework for Deep and Efficient LLM-based Scientific Peer Review LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T05:33:21.285342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:33:21.285342Z digest=sha256:e691a8abcc2491cb7ec22281927f4904fe075a564dd0e8e047625c49260fb2fe

Observation f75262ea-b5d0-49f1-9959-d7189b39a289 · inbound

A Multi-Layered Framework for Modeling Human Biology: From Basic AI Agents to a Full-Body AI Agent cites this paper.

A Multi-Layered Framework for Modeling Human Biology: From Basic AI Agents to a Full-Body AI Agent LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T15:32:37.359152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:32:37.359152Z digest=sha256:8a53849a7cad2e9b7ab6955bba0704591da67c88417b4f45d1983df5af026ed1

Observation 94532e34-8ff2-4efb-8459-54cf675c3a27 · inbound

CaresAI at BioCreative IX Track 1 -- LLM for Biomedical QA cites this paper.

CaresAI at BioCreative IX Track 1 -- LLM for Biomedical QA LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T13:17:40.190725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:17:40.190725Z digest=sha256:85d5a1ec7803a1339eb746a381246d418ed384f72cc0d95f7558c21488854bf9

Observation 8c6503d6-51d9-4ce1-a451-6f795513dfde · inbound

Latent Collaboration in Multi-Agent Systems cites this paper.

Latent Collaboration in Multi-Agent Systems LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-03T20:17:51.760033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T20:17:51.760033Z digest=sha256:97079d6302816c1a1ebc524d071fe4ff01385dcbf4669975e92e81bc417af3cb

Observation f60eb27b-2835-48c4-a76f-3eff58e7e401 · inbound

Latent Collaboration in Multi-Agent Systems cites this paper.

Latent Collaboration in Multi-Agent Systems LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-04T06:52:33.595754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T06:52:33.595754Z digest=sha256:9ccafadc867adbce32b066375fbe82d48f6b264182cfba6e6eafba70773ccb25

Observation 800ce77b-3e99-4eca-b335-18bb2c50c9e1 · inbound

The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems cites this paper.

The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-02T22:58:12.495580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T22:58:12.495580Z digest=sha256:dd67796db2ab3e6502fcfe1a4567c7b8d3b0a3f2ed38a646698d070cad6f8a6f

Observation 2c6142c3-fec2-4c56-86a8-19b5fe85e400 · inbound

APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation cites this paper.

APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:26:25.211553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T05:22:25.475956Z digest=sha256:c617276f01bea43b2f4435b7eb7567d912baca23c9c4182fddd815de18a2be1c

Observation 6cd65a94-22b4-4c46-9b3c-db45583ce517 · inbound

When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems cites this paper.

When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-25T04:26:37.986685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-25T04:25:26.710488Z digest=sha256:153c4ff2b6d54aa79cd8d974ae1cefed28b2233b93f6d8856656976575b61c6a

Observation 4fed3ac2-21f6-4119-9e58-b9b15bebf9c5 · inbound

MedPRESS: A Multi-turn Benchmark for Patient-Pressure-Induced Medical Sycophancy in LLMs cites this paper.

MedPRESS: A Multi-turn Benchmark for Patient-Pressure-Induced Medical Sycophancy in LLMs LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-04T05:39:51.132018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T05:39:51.132018Z digest=sha256:464923100bcb9a570ef93d29d39afc2637cbc109f4696226080269dcfb4774d7