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Paper Citation Record · LEDGER

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays

As of 11 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2509.15234.

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

pith.paper-citation-record.v1
2509.15234 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:33:17.808608Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T19:23:46.184189Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T23:00:50.533946Z

Reference resolution

47 of 47 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved47
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d01d3dc1-1179-4df7-b8e3-99032c767350 · outbound

This paper cites Mishkin, J.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Mishkin, J

Reference 1

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source=pdf_text observed=2026-08-04T16:33:13.760156Z digest=sha256:3019289d8e713b9291ef21d6106fdddd25b4853ddbb0929dd67cc929768937b3

Observation 46c1dee9-d73a-4046-99c8-3f58faef5624 · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-04T16:33:13.854601Z digest=sha256:0bcf3abb1b1606dd926004767e346c5ada947670ae300bc4d3230a0ebcce2d99

Observation 86085ab5-c5a5-4a38-82ff-26aadd70a092 · outbound

This paper cites Çallı, E.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Çallı, E

Reference 3

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source=pdf_text observed=2026-08-04T16:33:13.947915Z digest=sha256:c9d3edf72fcfe5f5e24d7b3b9755c83063b3963c6d6bf00c337761a580bf7350

Observation e8642379-ba05-4890-ac54-893538e50fa0 · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-04T16:33:14.031940Z digest=sha256:fd40fd366bb8874e4f5d801e7ad769861cd5a0153ebee667d52af9a284594fec

Observation 5eaf43d6-aacd-4715-b312-689734d9fe3c · outbound

This paper cites Publicly Available Clinical BERT Embeddings.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Publicly Available Clinical BERT Embeddings

Reference 5

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source=pdf_text observed=2026-08-04T16:33:14.110141Z digest=sha256:3efc3a4f79f08e6197d64de22beb1aabc9f72ea81d2ff0410bddf8d21303c786

Observation cc35852c-775a-4271-809f-6046fd411390 · outbound

This paper cites Boecking, N.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Boecking, N

Reference 6

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source=pdf_text observed=2026-08-04T16:33:14.226088Z digest=sha256:2f75c6df8d82c0059d33e2dad7139ea45f32e9c2956725707895d5499ceab97b

Observation 5aeb4cb3-edbe-4847-b00b-c921ea38fe02 · outbound

This paper cites Bannur, S.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Bannur, S

Reference 7

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source=pdf_text observed=2026-08-04T16:33:14.323123Z digest=sha256:3bb873abed0ec68e2364110358f7f43560db1eaa5d2e0579c5ed81ec65f6e1c3

Observation 11c3b678-5cf4-449d-bf78-e34e39acc0aa · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-04T16:33:14.413261Z digest=sha256:829904bf790fa945cbf1a80aad9c7e999cffcc03d239dd88837d0105f0445984

Observation 1370ad1e-a9c6-45b5-9136-8cbc0775c8b9 · outbound

This paper cites Johnson, L.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Johnson, L

Reference 9

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source=pdf_text observed=2026-08-04T16:33:14.491403Z digest=sha256:37fa1d4b5779e9044adf35849c1b6a2db0a359481273526658790de6d1a9a655

Observation a89927f7-59f9-4c1f-a155-25b5a2850c4c · outbound

This paper cites CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image Formats.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image Formats

Reference 10

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source=pdf_text observed=2026-08-04T16:33:14.574804Z digest=sha256:aa22093ca9d612be38af0b600f3dfb95600f2740c50e37d9cb5a489b59d9f38b

Observation 6a548834-b491-4783-ae3d-5689909b030e · outbound

This paper cites Bustos, A.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Bustos, A

Reference 11

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source=pdf_text observed=2026-08-04T16:33:14.697474Z digest=sha256:e79a3cf8e6e0cb9024e09c2299c3ed8d137bb94cb62a68952eecd5ecc92284bb

Observation 9b13ae4c-cf54-4e8e-b547-dbe2946f4d6d · outbound

This paper cites Demner-Fushman, M.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Demner-Fushman, M

Reference 12

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source=pdf_text observed=2026-08-04T16:33:14.776531Z digest=sha256:87af9828e3c7c9ced97eb975c46a33dd75e898f454e90dcf85eb63a56cff6245

Observation ce10fec5-2717-4232-ad73-6adee0f3c208 · outbound

This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 13

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source=pdf_text observed=2026-08-04T16:33:14.837168Z digest=sha256:c7a8a9a3ca9ad934390356a54612098faa08059487c6c321574eac837f95bc30

Observation dd06970b-bde1-4b9e-bb63-8e253feb48f9 · outbound

This paper cites Huang, A.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Huang, A

Reference 14

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source=pdf_text observed=2026-08-04T16:33:14.895578Z digest=sha256:a8bf651f84a6810f3c89bc43202ee67954d5e5d5360ffb5236cef458e24c23bf

Observation eb3ff32e-61f6-4d81-8ed4-4bd584f370ef · outbound

This paper cites Zhang, H.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Zhang, H

Reference 15

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source=pdf_text observed=2026-08-04T16:33:14.966969Z digest=sha256:996282d970deaeeb973f699eacd9bf2eefd44a09a5431a6e0966780a50b4028f

Observation c8b3db20-3bd1-4e2d-bb15-8cdb871990d1 · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 16

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source=pdf_text observed=2026-08-04T16:33:15.036453Z digest=sha256:d8645d1bb8905c3771dc5e5189e98faf812dd470cf589f6d81125fa51767ab5c

Observation a09ab3f1-71d4-4da4-86a7-7dd712666221 · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 17

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source=pdf_text observed=2026-08-04T16:33:15.113364Z digest=sha256:ed19a17ba8f5f0c7a43a67e36624f1d79510e7eed7d50a2ba8d9142068fe34f9

Observation f36cddcc-627a-4cbd-a5ee-66005804b0ee · outbound

This paper cites BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 18

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source=pdf_text observed=2026-08-04T16:33:15.209923Z digest=sha256:96aace8dd4346ed617aac2f938aa13c0ca686ea836c6e94c80465e9ae32883cf

Observation 45b0f36e-df49-4450-bd44-624cda12b6f3 · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:15.303494Z digest=sha256:6288aa1aef5bd500ca1ef15beea1fa23b858e02cb7147cd3b4ef7bd390b80aca

Observation 16ba3e8b-b482-42c0-b29d-152ec49b0d3a · outbound

This paper cites ReXrank: A Public Leaderboard for AI-Powered Radiology Report Generation.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays ReXrank: A Public Leaderboard for AI-Powered Radiology Report Generation

Reference 20

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source=pdf_text observed=2026-08-04T16:33:15.357777Z digest=sha256:946937d39e651d146b4dcd059432dc65f105e4a6e620f4734846e6369d0edd7b

Observation 9f6de6b6-3ed6-4dea-967f-124c76fc5595 · outbound

This paper cites MAIRA-2: Grounded Radiology Report Generation.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays MAIRA-2: Grounded Radiology Report Generation

Reference 21

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source=pdf_text observed=2026-08-04T16:33:15.413715Z digest=sha256:feb64f8dcc9b11d26b9e639fbe3230426063b751103ae83dd0220624fe297044

Observation c2ae2297-0477-41fb-9c39-d175384f9aca · outbound

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

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation

Reference 22

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source=pdf_text observed=2026-08-04T16:33:15.458286Z digest=sha256:79aff3b970feeb8fa8224d1f8dcdb675c1b8b6ca1e6b29b4b3806e38bf35c9a4

Observation 95c7003b-c78e-42a3-a18a-2d5882a8fdae · outbound

This paper cites CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

Reference 23

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source=pdf_text observed=2026-08-04T16:33:15.515018Z digest=sha256:efd777a44f2c2c6189023b1ca0cc9202a3edd5807bd8be7d463f703081a42dbe

Observation 0e0f1394-c5d9-43b2-a6b7-3221ae2d6b94 · outbound

This paper cites RadGraph: Extracting Clinical Entities and Relations from Radiology Reports.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays RadGraph: Extracting Clinical Entities and Relations from Radiology Reports

Reference 24

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source=pdf_text observed=2026-08-04T16:33:15.592440Z digest=sha256:547db9bbaeb6c3bbb681a57830a7a7220ce45f36c0133147e52c39886ad9b2dd

Observation 00b36930-3124-417f-8bac-b60aa8d21b55 · outbound

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

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays GREEN: Generative Radiology Report Evaluation and Error Notation

Reference 25

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source=pdf_text observed=2026-08-04T16:33:15.713278Z digest=sha256:a91fa85cf2c2a237fa46e623ac7bc25af8ec2019deb665c8a358b3af47c03422

Observation ee425e2c-9bd7-4ac8-a93e-06facaeccea7 · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 26

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source=pdf_text observed=2026-08-04T16:33:15.820428Z digest=sha256:5755b975e499e873f0b7c21f0830874df1025a1dbac586f0cbad69657b957cb2

Observation 5501e52e-2cf8-42a7-aae0-636f7293b3ba · outbound

This paper cites LLM Embeddings for Deep Learning on Tabular Data.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays LLM Embeddings for Deep Learning on Tabular Data

Reference 27

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source=pdf_text observed=2026-08-04T16:33:15.905501Z digest=sha256:d0e09c6e40e98f681bcb0f8922ce760237b3dc73ebe33a98d506ba6b498ae2de

Observation 86c8d3c2-7555-4cae-bfae-aa6b103bbe9f · outbound

This paper cites NoteLLM-2: Multimodal Large Representation Models for Recommendation.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays NoteLLM-2: Multimodal Large Representation Models for Recommendation

Reference 28

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source=pdf_text observed=2026-08-04T16:33:16.014946Z digest=sha256:820e952fa7590ed7fbad8f7444404f4525a65d21acc76b4f51390eb8ae839548

Observation d5c9709c-47f3-4954-b0fe-718707e715e5 · outbound

This paper cites BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers

Reference 29

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no resolver link, observed 2026-08-04T16:33:16.136080Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T16:33:16.136080Z digest=sha256:f654526eb3b48c87f88b20b0144efeef85ccdc287d8e705e4714b19f305b93c8

Observation 37d74310-373f-480c-878c-7976674ae219 · outbound

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

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Gemini: A Family of Highly Capable Multimodal Models

Reference 30

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source=pdf_text observed=2026-08-04T16:33:16.205021Z digest=sha256:dd7ec2ebe6f73fd20d801058d2a2997f2fd1c1b0d2492d0ef72e8bf56d277141

Observation d61d8552-6371-4882-804e-c5a68aa12952 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 31

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no resolver link, observed 2026-08-04T16:33:16.292573Z

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source=pdf_text observed=2026-08-04T16:33:16.292573Z digest=sha256:32dcb3f7c71c32dc98e642f0b9976bbd94992082e3352abfce506e85de2688e2

Observation 84c7cf7c-66c0-484d-8e7c-85b799b2a2d5 · outbound

This paper cites CheX-GPT: Harnessing Large Language Models for Enhanced Chest X-ray Report Labeling.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays CheX-GPT: Harnessing Large Language Models for Enhanced Chest X-ray Report Labeling

Reference 32

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source=pdf_text observed=2026-08-04T16:33:16.365797Z digest=sha256:aeeb42303460f7494c68d35c1ba005d8b561c3a9a251a1990f3f897be6f424f8

Observation fad01336-9d63-4983-84bd-97b968d8bf31 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 33

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source=pdf_text observed=2026-08-04T16:33:16.431907Z digest=sha256:15f7f7020ed47b0345da98e70d8b56f1653d1f05aef32e8efa38e2e6f8a94e08

Observation 4971dd82-4cd3-4a50-9234-5c81d1f6d36b · outbound

This paper cites The Llama 3 Herd of Models.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays The Llama 3 Herd of Models

Reference 34

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source=pdf_text observed=2026-08-04T16:33:16.516585Z digest=sha256:612b791b955bc0dc48cff634df92a8c60b773423ede1fcc28f793b085bd6116c

Observation 66902a68-7887-4154-af9d-22ffa3caebd5 · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 35

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source=pdf_text observed=2026-08-04T16:33:16.637354Z digest=sha256:4f7eb7280e1e0584aa6c5a9497591ba12f8e6cd908c7987be71361521f7ad186

Observation b009a6ea-7f87-4c37-9851-8c50da7343e6 · outbound

This paper cites RaTEScore: A Metric for Radiology Report Generation.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays RaTEScore: A Metric for Radiology Report Generation

Reference 36

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source=pdf_text observed=2026-08-04T16:33:16.744838Z digest=sha256:67aef2c13d66077a47f13e4b837480770a59d3caa26c96303d4b39941f5ea426

Observation 79ee6baf-0da5-4b4e-a451-0e7f9b70a8f1 · outbound

This paper cites LLM-RadJudge: Achieving Radiologist-Level Evaluation for X-Ray Report Generation.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays LLM-RadJudge: Achieving Radiologist-Level Evaluation for X-Ray Report Generation

Reference 37

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no resolver link, observed 2026-08-04T16:33:16.871286Z

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Observation d8e16df2-dc1e-4a99-ad20-079c1bf65fb6 · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 38

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no resolver link, observed 2026-08-04T16:33:16.971431Z

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Observation f110e60d-a0da-42cd-8325-366ddfb8ef95 · outbound

This paper cites Ko, C.-M.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Ko, C.-M

Reference 39

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no resolver link, observed 2026-08-04T16:33:17.068218Z

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Observation 552f5260-574c-4067-82f7-84a2c165d737 · outbound

This paper cites Huang, L.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Huang, L

Reference 40

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no resolver link, observed 2026-08-04T16:33:17.153491Z

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Observation 2be127b3-4903-4de9-b588-f1771235a348 · outbound

This paper cites year old woman with spontaneous PTX // Assess for PTX or interval change s/p CT placed to WS.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays year old woman with spontaneous PTX // Assess for PTX or interval change s/p CT placed to WS

Reference 41

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unresolved
no resolver link, observed 2026-08-04T16:33:17.213180Z

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Observation 3332d9b2-4890-41dd-8fe0-b1ba1965b081 · outbound

This paper cites mild”→“moderate.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays mild”→“moderate

Reference 42

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unresolved
no resolver link, observed 2026-08-04T16:33:17.324669Z

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Observation 304a9ffe-a742-4093-b3c4-126900f3c041 · outbound

This paper cites an unresolved cited work.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Unresolved cited work

Reference 43

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no resolver link, observed 2026-08-04T16:33:17.373407Z

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Observation e21688db-6dbc-47b6-897a-e69718c83edb · outbound

This paper cites Reticulonodular pattern.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Reticulonodular pattern

Reference 44

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unresolved
no resolver link, observed 2026-08-04T16:33:17.481988Z

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source=pdf_text observed=2026-08-04T16:33:17.481988Z digest=sha256:1cca8ab8c1c65c54b4c99b618c777ad79f6490d929206b7a331697db0403e03a

Observation c636bce7-074f-4714-a646-0a38765fcce9 · outbound

This paper cites left), distribution (upper lobes, lower lobes, basilar, etc.), severity (mild, moderate, severe), and comparisons to prior images.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays left), distribution (upper lobes, lower lobes, basilar, etc.), severity (mild, moderate, severe), and comparisons to prior images

Reference 45

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unresolved
no resolver link, observed 2026-08-04T16:33:17.595014Z

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Observation 72daf0ef-1934-4cd6-92c8-49a482dafc8a · outbound

This paper cites Reticular opacity in BLLF.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays Reticular opacity in BLLF

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:17.722740Z

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Observation 8764632c-c74c-4083-b822-c1867ce3d31f · outbound

This paper cites ‘json "gt.

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays ‘json "gt

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:17.808608Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T16:33:17.808608Z digest=sha256:be39abcceb2847a734f50c0728c0dc51ada0fe0ce0290e5a418d1704c0c21a21

Pith citing papers

Observation 106b0a6f-4bbc-455c-a41c-2adab416592d · inbound

Temporal Inversion for Learning Interval Change in Chest X-Rays cites this paper.

Temporal Inversion for Learning Interval Change in Chest X-Rays Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-06-02T03:04:34.366844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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