Paper Citation Record · LEDGER

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

As of 14 August 2026, this Paper Citation Record lists 100 of 167 outbound references and 4 inbound Pith citation observations for arXiv:2412.09529.

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

pith.paper-citation-record.v1
2412.09529 v3

Coverage vector

measured 100 of 167 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:03:42.447899Z

measured 104 of 104 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:32:25.247617Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T00:08:21.614363Z

Reference resolution

100 of 167 outbound references displayed

verified exact2
verified fuzzy0
unresolved98
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3b945d5d-3246-475f-9cf0-45ecc0f4584e · outbound

This paper cites Large language models encode clinical knowledge.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Large language models encode clinical knowledge

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:38.946189Z

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Observation 2f7c218e-ffdd-49bc-b241-dc1f6f24a6c6 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? A Comprehensive Overview of Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:38.994928Z

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Observation 47da8795-4d1e-46e9-b7f7-09bbb6c67afd · outbound

This paper cites GPT-4 Technical Report.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? GPT-4 Technical Report

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.067380Z

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Observation fae8177c-1686-429d-8bb2-a7445ebc0c7a · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Gemini: A Family of Highly Capable Multimodal Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.144912Z

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Observation 15c89396-ef19-4253-919a-4ad6529892a4 · outbound

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

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? LLaMA: Open and Efficient Foundation Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.239052Z

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Observation 68819d81-a5cc-4c3a-be35-8642d379538b · outbound

This paper cites Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.342147Z

Source-reported events for the cited work

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Observation 5be6b458-1042-4b1b-859b-df8e228015d6 · outbound

This paper cites Biomedical Visual Instruction Tuning with Clinician Preference Alignment.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Biomedical Visual Instruction Tuning with Clinician Preference Alignment

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.368236Z

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Observation ecf6e4d3-9935-4f2a-b07f-4fbb3a69eb55 · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Visual instruction tuning.Advances in neural information processing systems, 36, 2024

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.417968Z

Source-reported events for the cited work

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Observation 1613d86a-ac79-48da-b970-8657df9d51ce · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.Advances in Neural Information Processing Systems, 36, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Toolformer: Language models can teach themselves to use tools.Advances in Neural Information Processing Systems, 36, 2024

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.445779Z

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Observation 41adc6d3-0611-4faf-8f54-bf2af22fae25 · outbound

This paper cites Medagents: Large language models as collaborators for zero-shot medical reasoning.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Medagents: Large language models as collaborators for zero-shot medical reasoning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.484844Z

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Observation 7457c02c-5ffd-4085-b41d-3f40b8f3c70b · outbound

This paper cites AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.524743Z

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Observation 52ecb94c-1efd-4e1c-a165-4db65db64990 · outbound

This paper cites ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.549996Z

Source-reported events for the cited work

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Observation 0b1b4d1a-3bc3-418f-91a0-46532c47dcba · outbound

This paper cites Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face.Advances in Neural Information Processing Systems, 36, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face.Advances in Neural Information Processing Systems, 36, 2024

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.566775Z

Source-reported events for the cited work

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Observation c1314fb7-938e-491b-abb6-3db7f9d87c85 · outbound

This paper cites LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:03:43.693802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c4b1a77e-aa90-4d17-8e74-3cf2ec7132dd · outbound

This paper cites Evaluating large language models as agents in the clinic.NPJ digital medicine, 7(1):84,.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Evaluating large language models as agents in the clinic.NPJ digital medicine, 7(1):84,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.802934Z

Source-reported events for the cited work

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Observation ee832b2a-8c94-4381-a21f-d495b2ce6a09 · outbound

This paper cites Foundation models for generalist medical artificial intelligence.Nature, 616(7956):259–265, 2023.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Foundation models for generalist medical artificial intelligence.Nature, 616(7956):259–265, 2023

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.870967Z

Source-reported events for the cited work

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Observation 791ceaec-afc6-4e20-a749-abe411f86ff3 · outbound

This paper cites Generalist vision foundation models for medical imaging: A case study of segment anything model on zero-shot medical segmentation.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Generalist vision foundation models for medical imaging: A case study of segment anything model on zero-shot medical segmentation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.890457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b7f546c-358a-406b-9272-25014786b790 · outbound

This paper cites Large-scale long-tailed disease diagnosis on radiology images.Nature Communications, 15(1):10147, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Large-scale long-tailed disease diagnosis on radiology images.Nature Communications, 15(1):10147, 2024

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.935754Z

Source-reported events for the cited work

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Observation 16680c70-f2ba-4d76-9d14-2bb763fb170b · outbound

This paper cites Large-Vocabulary Segmentation for Medical Images with Text Prompts.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Large-Vocabulary Segmentation for Medical Images with Text Prompts

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.954743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fea79f1e-0091-4589-b7f2-ef69114ffac2 · outbound

This paper cites Knowledge-enhanced visual-language pretraining for computational pathology.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Knowledge-enhanced visual-language pretraining for computational pathology

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.964737Z

Source-reported events for the cited work

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Observation 00c5692e-8691-410b-ae17-a80fca2445af · outbound

This paper cites AutoRG-Brain: Grounded Report Generation for Brain MRI.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.994745Z

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Observation 4ccd57ef-4f1c-4e26-844c-5de794f778bc · outbound

This paper cites Towards generalist biomedical ai.NEJM AI, 1(3):AIoa2300138, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Towards generalist biomedical ai.NEJM AI, 1(3):AIoa2300138, 2024

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.015932Z

Source-reported events for the cited work

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Observation 169007b2-59ef-493c-951a-9edbdf056172 · outbound

This paper cites LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.035789Z

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Observation 6058dfb6-5288-4556-adee-e168d8ff503f · outbound

This paper cites Radiology-llama2: Best-in-class large language model for radiology.arXiv e-prints, pages arXiv–2309, 2023.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Radiology-llama2: Best-in-class large language model for radiology.arXiv e-prints, pages arXiv–2309, 2023

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.105090Z

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Observation 707e9fd4-f98c-47f9-b8f1-cd2ebb5cf410 · outbound

This paper cites A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.190210Z

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Observation 1b4686ce-db13-42de-a7f8-4ffd3b23c57d · outbound

This paper cites A generalist vision–language foundation model for diverse biomedical tasks.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? A generalist vision–language foundation model for diverse biomedical tasks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.209727Z

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Observation d6d31113-6bd9-4166-a879-855d5776d6ee · outbound

This paper cites PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.228374Z

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Observation d75dd2f5-fee1-4b15-82ad-b0819343afad · outbound

This paper cites an unresolved cited work.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.234739Z

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Observation 659e8a7b-67a4-418a-ac88-20a8362b5b17 · outbound

This paper cites an unresolved cited work.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.242606Z

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Observation 71a9844e-2d70-4bd2-9e0e-8a1375b78e9e · outbound

This paper cites Mixtral of Experts.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Mixtral of Experts

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.257906Z

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Observation 21ac6fd3-312a-40d0-8dcb-840ef0914301 · outbound

This paper cites Qwen Technical Report.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Qwen Technical Report

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.284866Z

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Observation c10ecaab-5f02-41b6-bacb-ad725e39a4bb · outbound

This paper cites M^3Builder: A Multi-Agent System for Automated Machine Learning in Medical Imaging.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? M^3Builder: A Multi-Agent System for Automated Machine Learning in Medical Imaging

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.434743Z

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Observation af36366c-f847-4270-971d-90af0699bfa2 · outbound

This paper cites LLM Agents Making Agent Tools.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? LLM Agents Making Agent Tools

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.522427Z

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Observation cebde7ec-9707-4ade-af3e-76a1b3e9cbb2 · outbound

This paper cites Large Language Models as Tool Makers.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Large Language Models as Tool Makers

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.541168Z

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Observation 8e546e1f-ea79-4bba-b6e1-b79ea1d25218 · outbound

This paper cites Taskmatrix.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Taskmatrix

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.566484Z

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Observation 83634795-df9d-40aa-95ac-f3f129508372 · outbound

This paper cites MLLM-Tool: A Multimodal Large Language Model For Tool Agent Learning.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? MLLM-Tool: A Multimodal Large Language Model For Tool Agent Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.694852Z

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Observation f244f5c6-1665-4208-bcc0-e334a9761ce3 · outbound

This paper cites Voxelprompt: A vision-language agent for grounded medical image analysis.arXiv preprint arXiv:2410.08397, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Voxelprompt: A vision-language agent for grounded medical image analysis.arXiv preprint arXiv:2410.08397, 2024

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.739597Z

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Unavailable: canonical work link unavailable.

Observation b3c51a32-3b39-4717-9237-313acb5ae5f5 · outbound

This paper cites Llm-based agentic systems in medicine and healthcare.Nature Machine Intelligence, 12 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Llm-based agentic systems in medicine and healthcare.Nature Machine Intelligence, 12 2024

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.746603Z

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Observation bb04ddfb-d350-4e92-a55d-4c63c2662141 · outbound

This paper cites Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.856825Z

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Unavailable: canonical work link unavailable.

Observation a8b3ac0a-99ba-4f14-8b2b-13a83f57749d · outbound

This paper cites Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.912687Z

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Observation a4077bab-c6e2-424c-917e-ce9404b4d876 · outbound

This paper cites Assessing gpt-4 multimodal performance in radiological image analysis.European Radiology, pages 1–7, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Assessing gpt-4 multimodal performance in radiological image analysis.European Radiology, pages 1–7, 2024

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.921559Z

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Observation 506ad7d5-25fa-4ddb-96c5-f3d69bc8de71 · outbound

This paper cites an unresolved cited work.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.927025Z

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Unavailable: canonical work link unavailable.

Observation 79d73416-2972-4015-880e-0638f8f72a39 · outbound

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

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:40.932346Z

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Observation 54464eaa-3686-4752-a0cb-e6ad3df56344 · outbound

This paper cites Langchain.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Langchain

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.030779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a5fbdb0-2314-41fd-9ca4-1fec89765cbf · outbound

This paper cites Pmc-llama: toward building open-source language models for medicine.Journal of the American Medical Informatics Association, page ocae045, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Pmc-llama: toward building open-source language models for medicine.Journal of the American Medical Informatics Association, page ocae045, 2024

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.037338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0d396c5-91c7-40b2-b3fe-b5e932a7d91a · outbound

This paper cites Towards building multilingual language model for medicine.Nature Communications, 15(1):8384, 2024.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Towards building multilingual language model for medicine.Nature Communications, 15(1):8384, 2024

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.045771Z

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Observation b8eeddc6-e588-4ce9-8b6f-6a12dab6b498 · outbound

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

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? MEDITRON-70B: Scaling Medical Pretraining for Large Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.179131Z

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Observation 90273562-04f2-499a-a777-95345a3f6cd7 · outbound

This paper cites Towards Evaluating and Building Versatile Large Language Models for Medicine.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Towards Evaluating and Building Versatile Large Language Models for Medicine

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:03:43.102167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 374529ea-05ca-4fd9-bb27-fd355cfb2934 · outbound

This paper cites Large language models in medicine.Nature medicine, 29(8):1930–1940,.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Large language models in medicine.Nature medicine, 29(8):1930–1940,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.264741Z

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Observation d32b6a8a-f763-44cb-8cfe-80228985eace · outbound

This paper cites Can Large Language Models Replace Data Scientists in Biomedical Research?.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Can Large Language Models Replace Data Scientists in Biomedical Research?

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.271056Z

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Observation 2e654b03-1055-4c8e-81a8-94424a24131e · outbound

This paper cites MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.279896Z

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Observation bc0c5cd0-bde0-4b11-820d-da2b45951adc · outbound

This paper cites Why Do Multi-Agent LLM Systems Fail?.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Why Do Multi-Agent LLM Systems Fail?

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.285114Z

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Observation ba19ff39-4a86-45e7-97d1-848c03b6c815 · outbound

This paper cites an unresolved cited work.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.349187Z

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Observation fa088da1-9013-41b4-95cf-d2288e82f579 · outbound

This paper cites PaLM 2 Technical Report.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? PaLM 2 Technical Report

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.355145Z

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Observation e3b25931-17ee-498e-a47c-90e8e5722a98 · outbound

This paper cites Mixture of experts: a literature survey.Artificial Intelligence Review, 42:275–293, 2014.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Mixture of experts: a literature survey.Artificial Intelligence Review, 42:275–293, 2014

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Observation c1e258bc-010b-4efa-8cab-e5ff3d145de7 · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? A normalized levenshtein distance metric.IEEE transactions on pattern analysis and machine intelligence, 29(6):1091–1095, 2007

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Observation 1d713838-efbc-49e4-bfbb-399f0e422b2a · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? False discovery rate.International encyclopedia of statistical science, 1:504–508, 2011

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Observation 68b07881-3464-4ccc-8d03-c6b30f6369b5 · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? A survey of text matching techniques

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Observation bc620d1f-3f4b-4f82-b327-50dc5e5c2c06 · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? A comprehensive survey of evaluation techniques for recommendation systems

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Bleu: a method for automatic evaluation of machine translation

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Observation 09a662c8-a076-4324-8785-74d285760c7b · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Rouge: A package for automatic evaluation of summaries

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.522592Z

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Observation ca352e18-a14e-4f06-842b-6baad68727ac · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Baseline

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Observation 1eb6b74c-b91c-43d1-8df2-862da0e5de62 · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Input: [Image] Output: [Modality]

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Observation 34280db0-43ec-4247-a67e-30267c237b4a · outbound

This paper cites Input: [Image] Output: [Anatomy].

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Input: [Image] Output: [Anatomy]

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.553430Z

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Input: [Image] & [Modality] & [Anatomy] Output: [Organ Mask] & [Organ Label]

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.559285Z

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Input: [Image] & [Modality] & [Anatomy] Output: [Anomaly Mask] & [Anomaly Label]

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.622281Z

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Observation 698976fb-67b6-446d-a7b8-8ef7044e9440 · outbound

This paper cites Input: [Image] & [Modality] & [Anatomy] Output: [Diseases].

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Input: [Image] & [Modality] & [Anatomy] Output: [Diseases]

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.649658Z

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Observation 47cf6f99-f3d5-4627-bd91-1dcbdf942a4f · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Input: [Image] & [Organ Mask] & [Organ Label] & [Anomaly Mask] & [Anomaly Label] Output: [Diseases]

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.656101Z

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? The biomarker can be either organ or anomaly

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.663392Z

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Input: [Priors] & [Indicator] & [Biomarkers] & [Quants] Output: [Value]

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.670755Z

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:41.710647Z

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Observation d5d9a18e-da3a-4312-8b85-c5d1167d5717 · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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Observation 809949f1-61c1-4747-b076-c75fe7afa4c0 · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? The questions should be phrased in a way that necessitates the use of these basic identification tools

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Your task involves three sequential parts:

Reference 78

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? 45-year-old male

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? When provided, analyze it following the format shown in the examples above

Reference 87

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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Observation 98c6079a-03e1-409c-a791-9f797c91f1d5 · outbound

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 90

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 93

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 95

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 96

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 97

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 98

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 99

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 100

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 101

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 102

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

Reference 103

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? Unresolved cited work

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Pith citing papers

Observation 0eb7b7a9-1deb-4963-88a5-b3782964b992 · inbound

Explainable Cross-Disease Reasoning for Cardiovascular Risk Assessment from Low-Dose Computed Tomography cites this paper.

Explainable Cross-Disease Reasoning for Cardiovascular Risk Assessment from Low-Dose Computed Tomography How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

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MedOpenClaw and MedFlowBench: Auditing Medical Agents in Full-Study Workflows cites this paper.

MedOpenClaw and MedFlowBench: Auditing Medical Agents in Full-Study Workflows How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

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Observation 9aef4bb8-3cd9-4261-bdc4-2789667b45d0 · inbound

ABRA: Agent Benchmark for Radiology Applications cites this paper.

ABRA: Agent Benchmark for Radiology Applications How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

Reference 35

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Observation c481c642-6460-43d0-9b02-567dba06ed3a · inbound

CT-PrepAgent: Bounded Policy and Controlled Execution for Adaptive CT Data Preparation cites this paper.

CT-PrepAgent: Bounded Policy and Controlled Execution for Adaptive CT Data Preparation How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

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