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Paper Citation Record · LEDGER

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation

As of 9 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2506.01118.

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

pith.paper-citation-record.v1
2506.01118 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:54:56.886214Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

26 of 26 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f76d73e3-9310-43d7-9728-fe431dd51a15 · outbound

This paper cites arXiv preprint arXiv:2503.23512 (2025).

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation arXiv preprint arXiv:2503.23512 (2025)

Reference 1

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Unavailable: canonical work link unavailable.

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Observation a00997de-d357-4dc1-bb14-ee0bcccf1353 · outbound

This paper cites Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models

Reference 2

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Unavailable: canonical work link unavailable.

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Observation 3e7b7e51-594d-4561-8f13-6b6a7bceb95e · outbound

This paper cites In: Findings of the Association for Computational Linguistics, ACL 2024, Bangkok, Thailand and virtual meeting, August 11-16, 2024.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation In: Findings of the Association for Computational Linguistics, ACL 2024, Bangkok, Thailand and virtual meeting, August 11-16, 2024

Reference 3

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Unavailable: canonical work link unavailable.

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Observation fd184b4f-4aea-4b26-8cb7-dfc5ca28637c · outbound

This paper cites In: Findings of the Association for Computational Linguistics: EACL 2023.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation In: Findings of the Association for Computational Linguistics: EACL 2023

Reference 4

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source=pdf_text observed=2026-08-07T11:54:55.854265Z digest=sha256:dc4dc04b8ec14f7d55375c5ffad872e280d0105cd11f5f8ccb16de0eb69d1039

Observation 07e3ec92-8d30-4ef1-95f9-94d4983a3a45 · outbound

This paper cites Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback

Reference 5

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Observation 11c74da8-437d-40c2-a8b0-376f1b55708d · outbound

This paper cites Thread of Thought Unraveling Chaotic Contexts.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Thread of Thought Unraveling Chaotic Contexts

Reference 6

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Observation 8a298d4d-9f02-4226-a149-96a06ed0aaef · outbound

This paper cites In: The Thirteenth International Confer- ence on Learning Representations (2025),https://openreview.net/forum?id= N1vYivuSKq.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation In: The Thirteenth International Confer- ence on Learning Representations (2025),https://openreview.net/forum?id= N1vYivuSKq

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e56c289b-79fa-496f-b88a-3f7abec512fb · outbound

This paper cites Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey

Reference 8

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Observation c40f9778-7036-45a3-9529-5c49891d3d2e · outbound

This paper cites an unresolved cited work.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 74bc855e-6490-4f55-83b5-6f65fc340323 · outbound

This paper cites In: 58th ACM/IEEE Design Au- tomation Conference, DAC 2021, San Francisco, CA, USA, December 5-9, 2021.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation In: 58th ACM/IEEE Design Au- tomation Conference, DAC 2021, San Francisco, CA, USA, December 5-9, 2021

Reference 10

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Observation 90c4119c-8d3a-41f0-9d71-e20f0e85f587 · outbound

This paper cites In: Proceedings of the ACM Web Conference 2022.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation In: Proceedings of the ACM Web Conference 2022

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8670fa6e-5102-476b-9d56-33c57b7a6a25 · outbound

This paper cites The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs

Reference 12

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Observation f26c5734-9fe0-493c-a6a1-33e814523200 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation A Comprehensive Overview of Large Language Models

Reference 13

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Observation 1a530e53-737b-42a5-ab31-8b314add7cad · outbound

This paper cites Authorea Preprints1, 1–26 (2023).

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Authorea Preprints1, 1–26 (2023)

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-07T11:54:58.104626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 5e4df372-0e5f-48c6-9594-9d2ddfa14836 · outbound

This paper cites The Debate Over Understanding in AI's Large Language Models.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation The Debate Over Understanding in AI's Large Language Models

Reference 15

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Unavailable: canonical work link unavailable.

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Observation 61e71fe4-85d5-41e7-ab53-4938074841fc · outbound

This paper cites Frontiers Artif.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Frontiers Artif

Reference 16

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metadata mismatch
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3197c1eb-85d9-4193-97a8-3afe0b82c134 · outbound

This paper cites Journal of Medical Internet Research27, e59069 (2025).

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Journal of Medical Internet Research27, e59069 (2025)

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d58acdba-55f5-4880-a7c7-b2f93f6cd8ed · outbound

This paper cites Communications Medicine5(1), 26 (2025).

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Communications Medicine5(1), 26 (2025)

Reference 18

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raw_fallback, observed 2026-08-07T11:54:57.934192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 483b19ab-4748-4491-880f-0be286436f7d · outbound

This paper cites an unresolved cited work.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Unresolved cited work

Reference 19

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Observation 890bba10-dbab-42a0-bb05-5cb3d876e3c3 · outbound

This paper cites Me LLaMA: Foundation Large Language Models for Medical Applications.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Me LLaMA: Foundation Large Language Models for Medical Applications

Reference 20

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Observation f3065245-652b-437f-96b3-b5799961ec07 · outbound

This paper cites an unresolved cited work.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Unresolved cited work

Reference 21

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metadata mismatch
raw_fallback, observed 2026-08-07T11:54:57.157344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f57c4d82-d7a4-4992-92ea-777e9b2ad620 · outbound

This paper cites Journal of Medical Internet Research 26, e52399 (2024).

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Journal of Medical Internet Research 26, e52399 (2024)

Reference 22

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verified fuzzy
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 84382d35-64ca-41bf-8e97-b5572aa90833 · outbound

This paper cites Journal of Medical Internet Research27, e64486 (2025).

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Journal of Medical Internet Research27, e64486 (2025)

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-07T11:54:57.764216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ade995d4-998b-48cd-a391-69ec6068964b · outbound

This paper cites PLOS Digital Health3(11), e0000662 (2024).

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation PLOS Digital Health3(11), e0000662 (2024)

Reference 24

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f518a756-ed34-4669-816b-9d32e017210e · outbound

This paper cites an unresolved cited work.

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1e0aab9b-d157-4942-acaf-231b55fbfc9f · outbound

This paper cites ACM transactions on intelligent systems and technology15(3), 1–45 (2024).

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation ACM transactions on intelligent systems and technology15(3), 1–45 (2024)

Reference 26

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Pith citing papers

No inbound Pith citation observations are available.