Diagnosing our datasets: How does my language model learn clinical information? | Paper Citation Record

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This paper cites Zero-shot clinical acronym expansion via latent meaning cells.

Diagnosing our datasets: How does my language model learn clinical information? Zero-shot clinical acronym expansion via latent meaning cells

Reference 1

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Observation 99a2bec7-6691-45bd-994a-27d5ecfbbace · outbound

This paper cites Large language models are few-shot clinical information extractors.

Diagnosing our datasets: How does my language model learn clinical information? Large language models are few-shot clinical information extractors

Reference 2

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This paper cites Medical large language models are vulnerable to data-poisoning attacks.

Diagnosing our datasets: How does my language model learn clinical information? Medical large language models are vulnerable to data-poisoning attacks

Reference 3

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This paper cites Openbiollms: Advancing open-source large language models for healthcare and life sciences.

Diagnosing our datasets: How does my language model learn clinical information? Openbiollms: Advancing open-source large language models for healthcare and life sciences

Reference 4

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This paper cites Give me Some Hard Questions: Synthetic Data Generation for Clinical QA.

Diagnosing our datasets: How does my language model learn clinical information? Give me Some Hard Questions: Synthetic Data Generation for Clinical QA

Reference 5

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This paper cites Testing and evaluation of health care applications of large language models: a systematic review.

Diagnosing our datasets: How does my language model learn clinical information? Testing and evaluation of health care applications of large language models: a systematic review

Reference 6

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Diagnosing our datasets: How does my language model learn clinical information? Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias

Reference 7

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Observation 7a565fea-87e9-431b-9a14-cf70f44e078d · outbound

This paper cites MEDITRON-70B: Scaling Medical Pretraining for Large Language Models.

Diagnosing our datasets: How does my language model learn clinical information? MEDITRON-70B: Scaling Medical Pretraining for Large Language Models

Reference 8

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This paper cites Med42-v2: A Suite of Clinical LLMs.

Diagnosing our datasets: How does my language model learn clinical information? Med42-v2: A Suite of Clinical LLMs

Reference 9

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Diagnosing our datasets: How does my language model learn clinical information? Scaling instruction-finetuned language models

Reference 10

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Diagnosing our datasets: How does my language model learn clinical information? Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus

Reference 11

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This paper cites The Llama 3 Herd of Models.

Diagnosing our datasets: How does my language model learn clinical information? The Llama 3 Herd of Models

Reference 12

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This paper cites What's In My Big Data?.

Diagnosing our datasets: How does my language model learn clinical information? What's In My Big Data?

Reference 13

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This paper cites Language models are surprisingly fragile to drug names in biomedical benchmarks.

Diagnosing our datasets: How does my language model learn clinical information? Language models are surprisingly fragile to drug names in biomedical benchmarks

Reference 14

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This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Diagnosing our datasets: How does my language model learn clinical information? The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 15

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This paper cites OLMo: Accelerating the Science of Language Models.

Diagnosing our datasets: How does my language model learn clinical information? OLMo: Accelerating the Science of Language Models

Reference 16

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Diagnosing our datasets: How does my language model learn clinical information? Studying Large Language Model Generalization with Influence Functions

Reference 17

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This paper cites MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data.

Diagnosing our datasets: How does my language model learn clinical information? MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data

Reference 18

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This paper cites MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain.

Diagnosing our datasets: How does my language model learn clinical information? MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain

Reference 19

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Observation 8c4f91dd-35ba-4664-946b-e4ecebe47a3c · outbound

This paper cites Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?.

Diagnosing our datasets: How does my language model learn clinical information? Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?

Reference 20

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This paper cites The Limited Impact of Medical Adaptation of Large Language and Vision-Language Models.

Diagnosing our datasets: How does my language model learn clinical information? The Limited Impact of Medical Adaptation of Large Language and Vision-Language Models

Reference 21

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This paper cites What disease does this patient have? a large-scale open domain question answering dataset from medical exams.

Diagnosing our datasets: How does my language model learn clinical information? What disease does this patient have? a large-scale open domain question answering dataset from medical exams

Reference 22

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Diagnosing our datasets: How does my language model learn clinical information? Matching patients to clinical trials with large language models

Reference 23

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Diagnosing our datasets: How does my language model learn clinical information? Mimic-iii

Reference 24

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Diagnosing our datasets: How does my language model learn clinical information? Mimic-iv

Reference 25

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This paper cites Mimic-iii, a freely accessible critical care database.

Diagnosing our datasets: How does my language model learn clinical information? Mimic-iii, a freely accessible critical care database

Reference 26

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This paper cites Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports.

Diagnosing our datasets: How does my language model learn clinical information? Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports

Reference 27

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Diagnosing our datasets: How does my language model learn clinical information? Mimic-iv, a freely accessible electronic health record dataset

Reference 28

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Diagnosing our datasets: How does my language model learn clinical information? Large language models struggle to learn long-tail knowledge

Reference 29

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This paper cites Debunking health fake news with domain specific pre-trained model.

Diagnosing our datasets: How does my language model learn clinical information? Debunking health fake news with domain specific pre-trained model

Reference 30

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This paper cites Can Large Language Models abstract Medical Coded Language?.

Diagnosing our datasets: How does my language model learn clinical information? Can Large Language Models abstract Medical Coded Language?

Reference 31

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Diagnosing our datasets: How does my language model learn clinical information? A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs)

Reference 32

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Diagnosing our datasets: How does my language model learn clinical information? Are Clinical T5 Models Better for Clinical Text?

Reference 33

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Diagnosing our datasets: How does my language model learn clinical information? Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 34

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Diagnosing our datasets: How does my language model learn clinical information? S2ORC: The Semantic Scholar Open Research Corpus

Reference 35

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Diagnosing our datasets: How does my language model learn clinical information? Fake or real news about covid-19? pretrained transformer model to detect potential misleading news

Reference 36

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This paper cites Evaluating base and retrieval augmented llms with document or online support for evidence based neurology.

Diagnosing our datasets: How does my language model learn clinical information? Evaluating base and retrieval augmented llms with document or online support for evidence based neurology

Reference 37

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This paper cites A sense inventory for clinical abbreviations and acronyms created using clinical notes and medical dictionary resources.

Diagnosing our datasets: How does my language model learn clinical information? A sense inventory for clinical abbreviations and acronyms created using clinical notes and medical dictionary resources

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:29:13.713212Z

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Diagnosing our datasets: How does my language model learn clinical information? Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 39

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Diagnosing our datasets: How does my language model learn clinical information? It’s time to bench the medical exam benchmark, 2025

Reference 40

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This paper cites Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.

Diagnosing our datasets: How does my language model learn clinical information? Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

Reference 41

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Diagnosing our datasets: How does my language model learn clinical information? Large language models are poor medical coders—benchmarking of medical code querying

Reference 42

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This paper cites Prevalence of health misinformation on social media: systematic review.

Diagnosing our datasets: How does my language model learn clinical information? Prevalence of health misinformation on social media: systematic review

Reference 43

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Diagnosing our datasets: How does my language model learn clinical information? Hashimoto

Reference 44

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Diagnosing our datasets: How does my language model learn clinical information? RedPajama: An Open Source Recipe to Reproduce LLaMA training dataset , April 2023

Reference 45

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Observation 89ef4626-a47c-4e1d-9043-a7fe80bfdc97 · outbound

This paper cites Clinical camel: An open-source expert-level medical language model with dialogue-based knowledge encoding.

Diagnosing our datasets: How does my language model learn clinical information? Clinical camel: An open-source expert-level medical language model with dialogue-based knowledge encoding

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:29:12.321384Z

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Diagnosing our datasets: How does my language model learn clinical information? LLaMA: Open and Efficient Foundation Language Models

Reference 47

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

Diagnosing our datasets: How does my language model learn clinical information? Adapted large language models can outperform medical experts in clinical text summarization

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:29:12.050114Z

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Observation 4824c5f2-d689-44d9-b29b-4d9ac1db0003 · outbound

This paper cites RedPajama: an Open Dataset for Training Large Language Models.

Diagnosing our datasets: How does my language model learn clinical information? RedPajama: an Open Dataset for Training Large Language Models

Reference 49

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Diagnosing our datasets: How does my language model learn clinical information? Me-llama: Foundation large language models for medical applications

Reference 50

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Observation 206aacf5-94cc-47cd-84a1-69a23639e6fb · outbound

This paper cites Almanac—retrieval-augmented language models for clinical medicine.

Diagnosing our datasets: How does my language model learn clinical information? Almanac—retrieval-augmented language models for clinical medicine

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:29:11.516515Z

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This paper cites A dataset for evaluating clinical research claims in large language models.

Diagnosing our datasets: How does my language model learn clinical information? A dataset for evaluating clinical research claims in large language models

Reference 52

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This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

Diagnosing our datasets: How does my language model learn clinical information? Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 53

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