Paper Citation Record · LEDGER

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models

As of 18 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 3 inbound Pith citation observations for arXiv:2504.19061.

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

pith.paper-citation-record.v1
2504.19061 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:05:59.731328Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:47:57.706717Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:26:06.760140Z

Reference resolution

37 of 37 outbound references displayed

verified exact0
verified fuzzy25
unresolved12
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ab86aeab-e472-40ce-ae8b-f7283b25f558 · outbound

This paper cites Better late than never: Model-agnostic hallucination post-processing framework towards clinical text summarization,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Better late than never: Model-agnostic hallucination post-processing framework towards clinical text summarization,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.232181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c1a311cb-1ab0-445f-8eb0-1f2135abcd0f · outbound

This paper cites Automated generation of hospital discharge summaries using clinical guidelines and large language models,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Automated generation of hospital discharge summaries using clinical guidelines and large language models,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.219200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3595d34d-b4d0-4f02-bd03-53b4f52401f4 · outbound

This paper cites Adapted large language models can outperform medical experts in clinical text summarization,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Adapted large language models can outperform medical experts in clinical text summarization,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.206758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fe60cdaf-92e0-42e0-b0a1-a36a864b531e · outbound

This paper cites A systematic review of large language models and their implications in medical education,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models A systematic review of large language models and their implications in medical education,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.194593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 603c9fbe-1389-490d-9f75-16cd96d6e611 · outbound

This paper cites A gold standard methodology for evaluating accuracy in data-to-text systems,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models A gold standard methodology for evaluating accuracy in data-to-text systems,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.181317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 76ae0dd0-a441-457c-ae9b-18d7613ff3ae · outbound

This paper cites Can large language models challenge CNNs in medical image analysis?.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Can large language models challenge CNNs in medical image analysis?

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.168688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7ee7c2ed-70d5-4a65-a786-58a20668d778 · outbound

This paper cites Evaluating large language models on medical evidence summarization,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Evaluating large language models on medical evidence summarization,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.154728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0d2e2384-5cfc-4f99-8ba5-9d4aaa3ecae6 · outbound

This paper cites CLINICSUM: Utilizing language models for gen- erating clinical summaries from patient-doctor conversations,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models CLINICSUM: Utilizing language models for gen- erating clinical summaries from patient-doctor conversations,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.141030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 40f167c9-9fba-4ee3-8f70-77b1fdd25891 · outbound

This paper cites An iterative optimizing framework for radiology report summarization with ChatGPT,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models An iterative optimizing framework for radiology report summarization with ChatGPT,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.128515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e3a61206-35af-4135-9f4f-85c8eaeef8f4 · outbound

This paper cites Survey of hallucination in natural language generation,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Survey of hallucination in natural language generation,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.619486Z

Source-reported events for the cited work

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Observation 9882cedc-ec28-4339-98fe-b1949da0f553 · outbound

This paper cites Battling misinformation: An empirical study on adversarial factuality in open-source large language models,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Battling misinformation: An empirical study on adversarial factuality in open-source large language models,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.106624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d3c2ed89-2f8d-40fd-8202-ba32551bcdfa · outbound

This paper cites Trustworthy medical imaging with large language models: A study of hallucinations across modalities,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Trustworthy medical imaging with large language models: A study of hallucinations across modalities,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.094630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation aaf17dc6-97b2-4cc5-a79f-662665c22dac · outbound

This paper cites Med-HALT: Medical Domain Hallucination Test for Large Language Models.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Med-HALT: Medical Domain Hallucination Test for Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.630607Z

Source-reported events for the cited work

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Observation c5403695-06de-41ba-a55f-9ad6dc575bf8 · outbound

This paper cites CoMT: Chain-of-medical-thought reduces hallucination in medical report generation,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models CoMT: Chain-of-medical-thought reduces hallucination in medical report generation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.079746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 17dc87a3-849e-421c-95e0-5cd493377dae · outbound

This paper cites MIMIC-IV, a freely accessible electronic health record dataset,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models MIMIC-IV, a freely accessible electronic health record dataset,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.067093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ad463901-92d5-44d9-95d8-646e1bddf486 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.642393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdb1c544-98dc-49b6-a44e-543aae92bed5 · outbound

This paper cites Enhancing healthcare through large language models: A study on medical question answering,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Enhancing healthcare through large language models: A study on medical question answering,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.054438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2956f8b6-4e64-463c-b1e4-ab1a8d87c5b0 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Gemma: Open Models Based on Gemini Research and Technology

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.650257Z

Source-reported events for the cited work

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Observation eeac0c9c-1a99-45ee-8aca-18d6e55ef229 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.654591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 080380d1-c938-448c-aac4-6c3edf2767ba · outbound

This paper cites Falcon2-11B Technical Report.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Falcon2-11B Technical Report

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.659600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4b60a70-5689-4123-acc4-8f5767dda10d · outbound

This paper cites LLaV A-Med: Training a large language-and-vision assistant for biomedicine in one day,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models LLaV A-Med: Training a large language-and-vision assistant for biomedicine in one day,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.042283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 12f4a191-3e7a-4493-9649-6eac48a134e8 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.668767Z

Source-reported events for the cited work

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Observation 762c7039-695f-4335-8497-2c0b89cf60b5 · outbound

This paper cites Qwen Technical Report.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Qwen Technical Report

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.673629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a68510f-f28d-4062-a02d-5cbef21a9e22 · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models BERT: Pre-training of deep bidirectional transformers for language understanding,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.028870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eb115563-7ccc-4af1-bb6c-0add970c3c33 · outbound

This paper cites Discharge summary hospital course summarisation of in patient electronic health record text with clinical concept guided deep pre-trained transformer models,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Discharge summary hospital course summarisation of in patient electronic health record text with clinical concept guided deep pre-trained transformer models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.014560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9aec0db5-88a0-4cc0-a395-3f5400da1f27 · outbound

This paper cites BioBERT: a pre-trained biomedical language representation model for biomedical text mining,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models BioBERT: a pre-trained biomedical language representation model for biomedical text mining,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:06:00.002064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e591cf65-8d64-4bcf-ba8d-d303085f9bcb · outbound

This paper cites ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.690031Z

Source-reported events for the cited work

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Observation 39d6a518-4aaa-4c99-8e80-fac7e004ffbd · outbound

This paper cites GPT-4 Technical Report.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models GPT-4 Technical Report

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.695486Z

Source-reported events for the cited work

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Observation e8410cbc-5467-45ef-b8d5-9ee1833ef1dc · outbound

This paper cites Towards generalist biomedical AI,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Towards generalist biomedical AI,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:05:59.988266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 95df659f-3073-44bf-ab90-1d105479ea1c · outbound

This paper cites Use of the systematized nomenclature of medicine clinical terms (SNOMED CT) for processing free text in health care: systematic scoping review,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Use of the systematized nomenclature of medicine clinical terms (SNOMED CT) for processing free text in health care: systematic scoping review,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:05:59.975676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2199ac77-71c1-4c50-9bd9-ad4b14e035da · outbound

This paper cites Position: TrustLLM: Trustworthiness in large language models,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Position: TrustLLM: Trustworthiness in large language models,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:05:59.961824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0433e4f2-df38-4410-89b7-74312dac5f9d · outbound

This paper cites A data-centric approach to generate faithful and high quality patient summaries with large language models,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models A data-centric approach to generate faithful and high quality patient summaries with large language models,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:05:59.945441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f947897-cae7-473a-bce1-afbbee5d805f · outbound

This paper cites Faithfulness hallucination detection in healthcare AI,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Faithfulness hallucination detection in healthcare AI,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:05:59.931766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ee1957f1-a906-44c4-9fb9-8d96059d54ea · outbound

This paper cites Controlled hallucinations: Learning to generate faithfully from noisy data,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Controlled hallucinations: Learning to generate faithfully from noisy data,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:05:59.917508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eaff9085-6060-41d1-bcdd-9b134fa918d6 · outbound

This paper cites Large Language Models are Inconsistent and Biased Evaluators.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models Large Language Models are Inconsistent and Biased Evaluators

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.723006Z

Source-reported events for the cited work

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Observation 96351fd7-3f12-4348-b32f-31c9d6ef1385 · outbound

This paper cites LLM hallucinations results on MIMIC IV clinical texts,.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models LLM hallucinations results on MIMIC IV clinical texts,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:05:59.903125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 73532168-0e56-42a5-92f2-29268c655503 · outbound

This paper cites MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models.

Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T10:05:59.731328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation c351cda3-c118-4070-8de3-d99f95a4038a · inbound

Can Large Language Models Challenge CNNs in Medical Image Analysis? cites this paper.

Can Large Language Models Challenge CNNs in Medical Image Analysis? Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:47:57.706717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc5692b7-7986-471c-af9f-2d399a6117df · inbound

TerraMAE: Learning Spatial-Spectral Representations from Hyperspectral Earth Observation Data via Adaptive Masked Autoencoders cites this paper.

TerraMAE: Learning Spatial-Spectral Representations from Hyperspectral Earth Observation Data via Adaptive Masked Autoencoders Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T22:26:40.759713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5b4f2af-03a5-4059-9b43-016f347b1f5e · inbound

Trustworthy Medical Imaging with Large Language Models: A Study of Hallucinations Across Modalities cites this paper.

Trustworthy Medical Imaging with Large Language Models: A Study of Hallucinations Across Modalities Hallucinations and Key Information Extraction in Medical Texts: A Comprehensive Assessment of Open-Source Large Language Models

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-05T22:26:06.764545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.