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Paper Citation Record · LEDGER

Structuring Radiology Reports: Challenging LLMs with Lightweight Models

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2506.00200.

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

pith.paper-citation-record.v1
2506.00200 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:16:57.463178Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 43974f0a-9981-4730-837d-5ed32a5eea44 · outbound

This paper cites Provide the relevant information as specified for each section.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Provide the relevant information as specified for each section

Reference 1

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verified fuzzy
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Source-reported events for the cited work

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

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Observation 218db902-3217-4857-8c21-337f085349d6 · outbound

This paper cites Improving Large Models with Small models: Lower Costs and Better Performance.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Improving Large Models with Small models: Lower Costs and Better Performance

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 53d66010-aec7-4f1e-ab6a-09cd3a7a2ecb · outbound

This paper cites Improving the Factual Correctness of Radiology Report Generation with Semantic Rewards.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Improving the Factual Correctness of Radiology Report Generation with Semantic Rewards

Reference 3

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Observation d05692d8-a7b4-4184-9fed-b79fb946c6c4 · outbound

This paper cites Do not add or extrapolate information beyond what is found in the original report.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Do not add or extrapolate information beyond what is found in the original report

Reference 4

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verified fuzzy
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Source-reported events for the cited work

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

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Observation 12a1fd73-b363-45ef-8736-494d61532102 · outbound

This paper cites Don't Stop Pretraining: Adapt Language Models to Domains and Tasks.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Don't Stop Pretraining: Adapt Language Models to Domains and Tasks

Reference 5

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Unavailable: canonical work link unavailable.

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Observation ce7041c6-6867-4590-a72f-cdb73b483b37 · outbound

This paper cites Ensure all findings are numbered.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Ensure all findings are numbered

Reference 6

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Source-reported events for the cited work

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Observation 3a910c0e-b868-499e-9fe5-e65e675cd30f · outbound

This paper cites GREEN: Generative Radiology Report Evaluation and Error Notation.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models GREEN: Generative Radiology Report Evaluation and Error Notation

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c11851c0-648c-4050-96c7-615eaf7e6704 · outbound

This paper cites Automated Annotation with Generative AI Requires Validation.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Automated Annotation with Generative AI Requires Validation

Reference 9

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Unavailable: canonical work link unavailable.

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Observation cbfc6336-d388-4074-96e6-3aecd62c1dd8 · outbound

This paper cites Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise?.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise?

Reference 10

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Source-reported events for the cited work

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Observation f69913cd-6d99-4444-bf0f-8bde3431009e · outbound

This paper cites RadAdapt: Radiology Report Summarization via Lightweight Domain Adaptation of Large Language Models.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models RadAdapt: Radiology Report Summarization via Lightweight Domain Adaptation of Large Language Models

Reference 11

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Unavailable: canonical work link unavailable.

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Observation d0fa83a5-af72-47d5-af52-3aedaa099b61 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models BERTScore: Evaluating Text Generation with BERT

Reference 12

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Observation 5f11263d-ed96-44e0-9c4c-b23c493a93fd · outbound

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Structuring Radiology Reports: Challenging LLMs with Lightweight Models Unresolved cited work

Reference 14

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Observation b2ec002d-232f-4ed7-80c5-9bcda06d2a0c · outbound

This paper cites Do not reference previous studies or historical data.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Do not reference previous studies or historical data

Reference 15

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

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Structuring Radiology Reports: Challenging LLMs with Lightweight Models Unresolved cited work

Reference 17

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Observation af549c86-69e1-41e2-b384-24ac73f5c778 · outbound

This paper cites an unresolved cited work.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Unresolved cited work

Reference 18

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

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Observation 45c35db9-84c9-4cfd-bd92-db08d51ba1bd · outbound

This paper cites an unresolved cited work.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Unresolved cited work

Reference 19

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

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Observation d53d8a7c-ed9b-4a5a-8192-4fca9bf8e414 · outbound

This paper cites an unresolved cited work.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Unresolved cited work

Reference 20

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Source-reported events for the cited work

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This paper cites Start with the organ system name followed by a colon, then list observations.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Start with the organ system name followed by a colon, then list observations

Reference 21

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Source-reported events for the cited work

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

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Observation f5b45fbf-8eed-479f-bc61-3cf7cbd44ae9 · outbound

This paper cites Quantifying the Carbon Emissions of Machine Learning.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Quantifying the Carbon Emissions of Machine Learning

Reference 2019

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Observation 5edaf3cd-0676-4388-901d-c7465277cb86 · outbound

This paper cites PhysioNet.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models PhysioNet

Reference 2020

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Source-reported events for the cited work

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

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Observation 8392a5d0-2972-41da-bf96-a6198fb61835 · outbound

This paper cites In Proceedings of the 2nd Workshop on Pattern-based Approaches to NLP in the Age of Deep Learning, pages 103–113.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models In Proceedings of the 2nd Workshop on Pattern-based Approaches to NLP in the Age of Deep Learning, pages 103–113

Reference 2023

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Source-reported events for the cited work

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

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Observation 3c050a36-a27e-4874-8964-08e8f8a2dbc0 · outbound

This paper cites Artificial Intelligence in Medicine , 154:102924.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Artificial Intelligence in Medicine , 154:102924

Reference 2024

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Pith citing papers

No inbound Pith citation observations are available.