Measuring Epistemic Resilience of LLMs Under Misleading Medical Context | Paper Citation Record

Observation 0c261a26-5299-4181-9e32-924ec78a814a · outbound

This paper cites The evaluation illusion of large language models in medicine.npj Digital Medicine, 8(1):600, 2025.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context The evaluation illusion of large language models in medicine.npj Digital Medicine, 8(1):600, 2025

Reference 1

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Observation b80a1a4e-76e0-4561-956d-3f49a38a89a9 · outbound

This paper cites Introducing Claude Sonnet 4.6, February 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Introducing Claude Sonnet 4.6, February 2026

Reference 2

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Observation f5a1742e-396c-4ff5-8470-868ed1648851 · outbound

This paper cites Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum.JAMA internal medicine, 183(6):589–596, 2023.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum.JAMA internal medicine, 183(6):589–596, 2023

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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This paper cites Fries, Michael Wornow, Akshay Swami- nathan, Lisa Soleymani Lehmann, Hyo Jung Hong, Mehr Kashyap, Akash R.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Fries, Michael Wornow, Akshay Swami- nathan, Lisa Soleymani Lehmann, Hyo Jung Hong, Mehr Kashyap, Akash R

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-27T09:40:47.713725Z

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Observation be36c7f0-cd1a-4761-99c8-606b73022289 · outbound

This paper cites and Saba, Luca and Hadamitzky, Martin and Kather, Jakob Nikolas and Truhn, Daniel and Cuocolo, Renato and Adams, Lisa C.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context and Saba, Luca and Hadamitzky, Martin and Kather, Jakob Nikolas and Truhn, Daniel and Cuocolo, Renato and Adams, Lisa C

Reference 5

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.715756Z

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Observation 7e605dd6-e4a8-4331-bce0-cb9334308c6b · outbound

This paper cites MedBench: A Large-Scale Chinese Benchmark for Evaluating Medical Large Language Models.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context MedBench: A Large-Scale Chinese Benchmark for Evaluating Medical Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-27T09:40:47.726832Z

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Observation d577bdeb-c2e2-452a-bf3e-cec76a00e335 · outbound

This paper cites Singer, Xuguang Ai, Po-Ting Lai, Zhizheng Wang, et al.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Singer, Xuguang Ai, Po-Ting Lai, Zhizheng Wang, et al

Reference 7

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.729745Z

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Observation 1e241908-2353-4149-87e4-a074900d5322 · outbound

This paper cites M ed R isk E val: Medical Risk Evaluation Benchmark of Language Models, On the Importance of User Perspectives in Healthcare Settings.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context M ed R isk E val: Medical Risk Evaluation Benchmark of Language Models, On the Importance of User Perspectives in Healthcare Settings

Reference 8

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.703992Z

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Observation 719ec87d-f4b3-4372-be84-e1568a1de664 · outbound

This paper cites Nour, Seth Spielman, Samuel F.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Nour, Seth Spielman, Samuel F

Reference 9

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.717626Z

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Observation 5351bece-dab5-4883-a7cc-6ef534825137 · outbound

This paper cites Openseeker: Democratizing frontier search agents by fully open-sourcing training data.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Openseeker: Democratizing frontier search agents by fully open-sourcing training data

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-27T09:40:47.720548Z

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Observation 540d2000-a428-44b9-ab3d-16b6a5dfff03 · outbound

This paper cites Gemini 3.1 Flash-Lite model card, March 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Gemini 3.1 Flash-Lite model card, March 2026

Reference 11

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Observation c5699b5a-6319-465d-be68-7fab4520da9c · outbound

This paper cites Gemini 3.1 Pro model card, February 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Gemini 3.1 Pro model card, February 2026

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 27ac4c67-ad69-4624-9585-ed5d35d10b72 · outbound

This paper cites Gemma 4 model card, April 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Gemma 4 model card, April 2026

Reference 13

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Observation 7a4ed9e4-0b01-4fca-b6dc-362ca410d226 · outbound

This paper cites InProceedings of the 16th ACM Workshop on Artificial Intelligence and Security (AISec @ CCS 2023).

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context InProceedings of the 16th ACM Workshop on Artificial Intelligence and Security (AISec @ CCS 2023)

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T09:40:47.665521Z

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Observation 32c75ced-a565-4b9f-9ea8-459d041a706b · outbound

This paper cites Bressem, Jakob Niko- las Kather, and Daniel Truhn.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Bressem, Jakob Niko- las Kather, and Daniel Truhn

Reference 15

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.671155Z

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Observation 1c4768a3-0fc8-408c-9191-6c9e5ae83fe9 · outbound

This paper cites MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-27T09:40:47.682854Z

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Observation 4a51a8e8-4057-411b-a30a-9ff8d7640f71 · outbound

This paper cites What disease does this patient have? A large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context What disease does this patient have? A large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421

Reference 17

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.679630Z

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Observation 58b18d2e-4f74-41c8-aaf5-84660a3342ab · outbound

This paper cites H., et al.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context H., et al

Reference 18

Resolution: metadata mismatch; doi, observed 2026-06-27T09:40:47.657248Z

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Observation 89a3a225-a350-4a6e-a4bc-33a2f0d0ab4e · outbound

This paper cites Evaluating clinical competencies of large language models with a general practice benchmark.Nature Communications, 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Evaluating clinical competencies of large language models with a general practice benchmark.Nature Communications, 2026

Reference 19

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.668222Z

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Observation 1a051535-a6c0-4d00-84d3-dc346cc526ad · outbound

This paper cites an unresolved cited work.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Unresolved cited work

Reference 20

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.659138Z

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Observation 9e798e51-8f1c-4fb7-9a37-9cf94bc46b4f · outbound

This paper cites Chen, Yining Hua, Peilin Zhou, Junling Liu, Chengfeng Mao, Chenyu You, Xian Wu, Yefeng Zheng, Lei Clifton, Zheng Li, Jiebo Luo, and David A.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Chen, Yining Hua, Peilin Zhou, Junling Liu, Chengfeng Mao, Chenyu You, Xian Wu, Yefeng Zheng, Lei Clifton, Zheng Li, Jiebo Luo, and David A

Reference 21

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.661074Z

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Observation 3b68e594-aaad-45d0-851a-2c5d26fc447e · outbound

This paper cites Benchmarking large language models on CMExam - A comprehensive chinese medical exam dataset.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Benchmarking large language models on CMExam - A comprehensive chinese medical exam dataset

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 38bcec30-d012-4b2e-a991-839b04c20f97 · outbound

This paper cites Carrero, Xiaofeng Jiang, Dyke Ferber, Georg Wölflein, Li Zhang, Sanddhya Jayabalan, Tim Lenz, Zhouguang Hui, et al.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Carrero, Xiaofeng Jiang, Dyke Ferber, Georg Wölflein, Li Zhang, Sanddhya Jayabalan, Tim Lenz, Zhouguang Hui, et al

Reference 23

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.653523Z

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Observation b64375e8-78c7-4159-b8ff-7db14240cf13 · outbound

This paper cites Beyond the Leaderboard: Rethinking Medical Benchmarks for Large Language Models.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Beyond the Leaderboard: Rethinking Medical Benchmarks for Large Language Models

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-06-27T09:40:47.697055Z

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Observation 66d22251-a305-46e8-86ef-e56236d08886 · outbound

This paper cites Persuasion with Large Language Models: A Survey of Empirical Evidence, Study Methodologies, and Ethical Implications.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Persuasion with Large Language Models: A Survey of Empirical Evidence, Study Methodologies, and Ethical Implications

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-06-27T09:40:47.674649Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1d8fef7f-8bf1-4cd9-8e4e-b071d2fb5167 · outbound

This paper cites Capabilities of GPT-4 on Medical Challenge Problems.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Capabilities of GPT-4 on Medical Challenge Problems

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-06-27T09:40:47.694621Z

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Observation d88b5189-5ad4-4e53-9185-0cd2cf898024 · outbound

This paper cites Wieler, Alexander W.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Wieler, Alexander W

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-06-27T09:40:47.688112Z

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Observation 5148f2fd-5fa3-4acf-8a4f-09af51f4093f · outbound

This paper cites Introducing HealthBench, May 2025.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Introducing HealthBench, May 2025

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation a7a54846-05e7-43af-ab70-764dbaacd8e6 · outbound

This paper cites Introducing ChatGPT health, January 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Introducing ChatGPT health, January 2026

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 941e6f5f-006e-42ee-abf5-c930b369fb1a · outbound

This paper cites Introducing GPT-5.4, March 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Introducing GPT-5.4, March 2026

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 49d70b12-958a-434a-ab60-021c82fb2059 · outbound

This paper cites Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation c8402bc5-06b9-45e1-b2f0-a77ca98e549d · outbound

This paper cites Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, and Jared Kaplan.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, and Jared Kaplan

Reference 32

Resolution: metadata mismatch; doi, observed 2026-06-27T09:40:47.692104Z

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Observation 0ab6ef48-f502-416c-9af1-027bd2548c5f · outbound

This paper cites A benchmark of expert-level academic questions to assess ai capabilities.Nature, 649(8099):1139–1146, 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context A benchmark of expert-level academic questions to assess ai capabilities.Nature, 649(8099):1139–1146, 2026

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 544ca31a-b033-459b-9e6a-345ab9c37178 · outbound

This paper cites Qwen3.6-35B-A3B: Agentic coding power, now open to all, April 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Qwen3.6-35B-A3B: Agentic coding power, now open to all, April 2026

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation d825c699-3e00-43b2-b048-d8e047d718f7 · outbound

This paper cites Rao, Kaiz P.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Rao, Kaiz P

Reference 35

Resolution: malformed identifier; doi_truncated, observed 2026-06-27T09:40:47.689981Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b4f2261e-e04c-4420-869d-b162aede1ea0 · outbound

This paper cites AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-06-27T09:40:47.651478Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 75acb012-7971-4e53-ac1e-1ca640badf4b · outbound

This paper cites MedGemma Technical Report.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context MedGemma Technical Report

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-07-03T11:28:04.906945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 88941836-0bfd-4bf4-97ac-daacae0e5e87 · outbound

This paper cites MedGemma Technical Report.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context MedGemma Technical Report

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-06-27T09:40:47.701506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6bad8ac1-4d39-4408-94d6-2d1db9c1f87d · outbound

This paper cites Bowman, Esin Durmus, Zac Hatfield-Dodds, Scott R.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Bowman, Esin Durmus, Zac Hatfield-Dodds, Scott R

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation e86c6f93-bb8b-420f-adee-b5903f9810c6 · outbound

This paper cites Large Language Models Encode Clinical Knowledge.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Large Language Models Encode Clinical Knowledge

Reference 40

Resolution: metadata mismatch; doi, observed 2026-06-27T09:40:47.685587Z

Source-reported events for the cited work

correction dated 2023-07-27. Source: crossref record 10.1038/s41586-023-06455-0->10.1038/s41586-023-06291-2:correction, observed 2026-07-11T03:08:19.417011+00:00. This notice travels one citation hop only.

Observation 1f9089c2-00cb-4e96-81e9-ee9bd8b32776 · outbound

This paper cites Toward expert-level medical question answering with large language models.Nature medicine, 31(3):943–950, 2025.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Toward expert-level medical question answering with large language models.Nature medicine, 31(3):943–950, 2025

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 06564744-66fb-43d8-9e4a-068065fa7b05 · outbound

This paper cites J., Ting, D.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context J., Ting, D

Reference 42

Resolution: metadata mismatch; doi, observed 2026-06-27T09:40:47.677277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2b451404-2d67-4e8f-8c24-2c9344267af2 · outbound

This paper cites Scientists invented a fake disease.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Scientists invented a fake disease

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 56da7f00-9808-4575-ae31-8c6dedc8d968 · outbound

This paper cites Sara Mahdavi, Christoph er Semturs, Juraj Gottweis, Joelle Barral, Katherine Chou, Greg S.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Sara Mahdavi, Christoph er Semturs, Juraj Gottweis, Joelle Barral, Katherine Chou, Greg S

Reference 44

Resolution: verified exact; doi, observed 2026-06-27T09:40:47.665957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 246cfae3-a8c3-4950-b0f6-6006f339bc29 · outbound

This paper cites A novel evaluation benchmark for medical llms illuminating safety and effectiveness in clinical domains.npj Digital Medicine, 2025.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context A novel evaluation benchmark for medical llms illuminating safety and effectiveness in clinical domains.npj Digital Medicine, 2025

Reference 45

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Unavailable: canonical work link unavailable.

Observation 6c145b93-6c3a-40ee-81fb-08fbd133268c · outbound

This paper cites Understanding the infodemic and misinformation in the fight against COVID-19, 2026.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Understanding the infodemic and misinformation in the fight against COVID-19, 2026

Reference 46

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation b3f29295-7fea-479c-ab2e-e5a41d1454a2 · outbound

This paper cites Medjourney: Benchmark and evaluation of large language models over patient clinical journey.Advances in Neural Information Processing Systems, 37:87621–87646, 2024.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context Medjourney: Benchmark and evaluation of large language models over patient clinical journey.Advances in Neural Information Processing Systems, 37:87621–87646, 2024

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 02ea82fb-5be2-413e-813c-a31f49c1b078 · outbound

This paper cites npj Health Systems 2025 2:1 2:2-.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context npj Health Systems 2025 2:1 2:2-

Reference 48

Resolution: metadata mismatch; doi, observed 2026-06-27T09:40:47.655715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 375f9888-66cb-4d10-8354-53ba2a5d62de · outbound

This paper cites React: Synergizing reasoning and acting in language models.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context React: Synergizing reasoning and acting in language models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 1476ca49-19fc-46c6-930f-65b89229fa44 · outbound

This paper cites PoisonedRAG: Knowledge corruption attacks to Retrieval-Augmented generation of large language models.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context PoisonedRAG: Knowledge corruption attacks to Retrieval-Augmented generation of large language models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-06-27T09:30:47.726480Z

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Observation 85ae5e85-f44d-490e-8969-4645295422f7 · outbound

This paper cites MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding.

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding

Reference 51

Resolution: malformed identifier; local_arxiv, observed 2026-07-03T11:28:04.910150Z

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