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Paper Citation Record · LEDGER

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models

As of 20 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 1 inbound Pith citation observation for arXiv:2411.15232.

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

pith.paper-citation-record.v1
2411.15232 v2

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:15:54.783799Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:56:23.202931Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T19:56:23.290936Z

Reference resolution

63 of 63 outbound references displayed

  • verified exact0
  • verified fuzzy43
  • unresolved18
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ed09910c-ca91-4d1b-99e5-0931e84cc3a9 · outbound

This paper cites GPT-4 Technical Report.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

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Observation 9dc0e63d-588d-4f44-a9db-81b51973e4a7 · outbound

This paper cites Dataset of breast ultrasound images.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Dataset of breast ultrasound images

Reference 2

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verified fuzzy
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Source-reported events for the cited work

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Observation fcdb72d8-7b3b-45c4-bd46-f78010dd2f11 · outbound

This paper cites Xcoop: Explainable prompt learning for computer-aided di- agnosis via concept-guided context optimization.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Xcoop: Explainable prompt learning for computer-aided di- agnosis via concept-guided context optimization

Reference 3

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Source-reported events for the cited work

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Observation 44712d8b-a15d-4df0-bd4f-8d0896eff968 · outbound

This paper cites Making the most of text semantics to improve biomedical vision–language processing.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Making the most of text semantics to improve biomedical vision–language processing

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation ef060e51-c2eb-4b74-b004-9866ce47db08 · outbound

This paper cites Borkowski, Marilyn M.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Borkowski, Marilyn M

Reference 5

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Source-reported events for the cited work

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Observation fe56cb3c-208c-4c7a-975f-4242945006f1 · outbound

This paper cites Domain-controlled prompt learning.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Domain-controlled prompt learning

Reference 6

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Source-reported events for the cited work

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Observation 19f4a63b-3d5a-49d2-bdff-2ceede1b1ec2 · outbound

This paper cites Knee osteoarthritis severity grading dataset,.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Knee osteoarthritis severity grading dataset,

Reference 7

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Source-reported events for the cited work

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Observation d2fee4e5-83a2-4efd-ab3d-0434494b15be · outbound

This paper cites gscorecam: What objects is clip looking at? In Proceedings of the Asian Conference on Computer Vision , pages 1959– 1975, 2022.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models gscorecam: What objects is clip looking at? In Proceedings of the Asian Conference on Computer Vision , pages 1959– 1975, 2022

Reference 8

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Source-reported events for the cited work

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Observation ac0717ef-c12b-471f-babb-0361e3947328 · outbound

This paper cites brain tumor dataset, 2017.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models brain tumor dataset, 2017

Reference 9

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Source-reported events for the cited work

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Observation d39db563-e425-4f20-9eb8-1603c179d41f · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 71addbd1-270c-4157-8f6f-667f989c344a · outbound

This paper cites an unresolved cited work.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Unresolved cited work

Reference 11

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Source-reported events for the cited work

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Observation 405856ac-d586-4484-ba50-933c68cddcc5 · outbound

This paper cites BCN20000: Dermoscopic Lesions in the Wild.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models BCN20000: Dermoscopic Lesions in the Wild

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5ae2a1a3-b2c1-4ecf-a679-6ebfd09606b3 · outbound

This paper cites Cleft: Language-image contrastive learning with efficient large language model and prompt fine-tuning.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Cleft: Language-image contrastive learning with efficient large language model and prompt fine-tuning

Reference 13

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Source-reported events for the cited work

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Observation 80e2ac09-fb65-4547-b82e-2ae6dd0ccabc · outbound

This paper cites Does clip benefit visual question answering in the medical domain as much as it does in the general domain?, 2021.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Does clip benefit visual question answering in the medical domain as much as it does in the general domain?, 2021

Reference 14

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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 2026-08-20T06:33:59.587034+00:00.

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Observation b6bfa79a-a107-4eb3-aa86-5ce25ab4255c · outbound

This paper cites Aligning medical images with general knowl- edge from large language models.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Aligning medical images with general knowl- edge from large language models

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation fcffca70-3690-468a-af47-1d44197ff716 · outbound

This paper cites Clip-adapter: Better vision-language models with feature adapters.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Clip-adapter: Better vision-language models with feature adapters

Reference 16

Resolution
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Source-reported events for the cited work

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Observation ceb70338-c4c9-41bd-b0df-3f45f2797d05 · outbound

This paper cites Potential of gpt-4 for de- tecting errors in radiology reports: Implications for reporting accuracy.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Potential of gpt-4 for de- tecting errors in radiology reports: Implications for reporting accuracy

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6fad88db-0186-4512-ac5a-74c4a95f834c · outbound

This paper cites Parameter-efficient transfer learning for nlp.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Parameter-efficient transfer learning for nlp

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 34dc4096-2c12-4ebe-b10c-fd066a418b1b · outbound

This paper cites Lp++: A surprisingly strong linear probe for few-shot clip.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Lp++: A surprisingly strong linear probe for few-shot clip

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 2ca8546b-d8ce-4c6e-80af-48f91d4f0ea6 · outbound

This paper cites Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from ct- radiography.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from ct- radiography

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 5120db6a-f001-49ff-8d70-721bd80b3151 · outbound

This paper cites Scaling up visual and vision-language representa- tion learning with noisy text supervision.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 16344d51-c40b-42fb-bdc2-a0475ab3fb42 · outbound

This paper cites Multi-class texture anal- ysis in colorectal cancer histology.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Multi-class texture anal- ysis in colorectal cancer histology

Reference 22

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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 2026-08-20T06:33:59.587034+00:00.

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Observation f45083a9-389e-43d6-af3a-18e20c06ba5b · outbound

This paper cites Kermany, Michael Goldbaum, et al.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Kermany, Michael Goldbaum, et al

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 10640332-e041-4874-b479-cce30d583892 · outbound

This paper cites Maple: 9 Multi-modal prompt learning.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Maple: 9 Multi-modal prompt learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.585308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f15c24ae-e2e4-468a-b0bd-b8d700785a94 · outbound

This paper cites Maple: Multi-modal prompt learning.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Maple: Multi-modal prompt learning

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.568466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a6479503-1a7b-4000-9a62-95f031de8e12 · outbound

This paper cites Self-regulating prompts: Foundational model adaptation without forgetting.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Self-regulating prompts: Foundational model adaptation without forgetting

Reference 26

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c367b3aa-d66b-425f-91f5-46a4b2ac7e46 · outbound

This paper cites Learning to Prompt with Text Only Supervision for Vision-Language Models.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Learning to Prompt with Text Only Supervision for Vision-Language Models

Reference 27

Resolution
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no resolver link, observed 2026-08-12T15:15:54.588588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0c1b4529-6ef1-454f-b467-0415431f599f · outbound

This paper cites Medclip-sam: Bridging text and image towards universal medical image segmentation.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Medclip-sam: Bridging text and image towards universal medical image segmentation

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.541341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0d08898b-3a99-4006-946e-f28599c6393e · outbound

This paper cites MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 29c8f5ce-8f1c-462d-b755-b2efffc86516 · outbound

This paper cites Evaluation of reliability, repeatability, ro- bustness, and confidence of gpt-3.5 and gpt-4 on a radiology board–style examination.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Evaluation of reliability, repeatability, ro- bustness, and confidence of gpt-3.5 and gpt-4 on a radiology board–style examination

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 291f8513-29b4-492c-a3f2-5d296ef61648 · outbound

This paper cites Automatic no- reference quality assessment for retinal fundus images using vessel segmentation, 2013.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Automatic no- reference quality assessment for retinal fundus images using vessel segmentation, 2013

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9a5224e3-18bd-48f9-89be-fe16fd31aaf1 · outbound

This paper cites A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 805655a7-594a-4462-be6d-0d4e5a18b24e · outbound

This paper cites Segment anything in medical images.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Segment anything in medical images

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 269c855d-6c64-4d3a-ac01-10e92a6a5429 · outbound

This paper cites Brain tumor mri dataset, 2021.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Brain tumor mri dataset, 2021

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.479318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 2827826d-6c71-42fa-98ec-22a5c3a9b0b4 · outbound

This paper cites Kvasir: A multi-class image dataset for com- puter aided gastrointestinal disease detection.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Kvasir: A multi-class image dataset for com- puter aided gastrointestinal disease detection

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 659feeea-9154-4c1d-a96a-9a8061d50443 · outbound

This paper cites Indian diabetic retinopathy image dataset (idrid), 2018.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Indian diabetic retinopathy image dataset (idrid), 2018

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 7185b9a8-1bcc-4d93-b980-f9661c82988f · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Learning transferable visual models from natural language supervi- sion

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3c21c7b0-1fe8-4ed9-b310-2278ae13b47e · outbound

This paper cites A closer look at the few-shot adaptation of large vision-language models.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models A closer look at the few-shot adaptation of large vision-language models

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 66dd93ba-b8df-4a7a-9e80-cf2bf25ab143 · outbound

This paper cites Tahir, Muhammad E.H.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Tahir, Muhammad E.H

Reference 39

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 192fb5d2-f023-4d4a-bdcb-05531c928b97 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source der- matoscopic images of common pigmented skin lesions.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models The ham10000 dataset, a large collection of multi-source der- matoscopic images of common pigmented skin lesions

Reference 40

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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 2026-08-20T06:33:59.587034+00:00.

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Observation e565f561-5b25-484d-81e0-991d12af4ee4 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source der- matoscopic images of common pigmented skin lesions.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models The ham10000 dataset, a large collection of multi-source der- matoscopic images of common pigmented skin lesions

Reference 41

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d7a543a5-5220-4cd6-bb2c-a51df76b91b1 · outbound

This paper cites Advances in medical image seg- mentation: A comprehensive review of traditional, deep learning and hybrid approaches.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Advances in medical image seg- mentation: A comprehensive review of traditional, deep learning and hybrid approaches

Reference 42

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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 2026-08-20T06:33:59.587034+00:00.

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Observation b7288f3c-4115-4701-bbc8-46b5dbfba629 · outbound

This paper cites Visual- language prompt tuning with knowledge-guided context op- timization, 2023.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Visual- language prompt tuning with knowledge-guided context op- timization, 2023

Reference 43

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T15:15:54.673272Z digest=sha256:dd002d8922439a5a5f2d6a01abe56681910af9af14d7c3a3807a87cd3381aca7

Observation acbe8bd8-8ac0-4ed5-ab92-8000bd5b5ec4 · outbound

This paper cites Visual- language prompt tuning with knowledge-guided context op- timization.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Visual- language prompt tuning with knowledge-guided context op- timization

Reference 44

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:15:54.678830Z digest=sha256:e2658c3a2d1912ead0b42ec9ce7b6cccea31bef604e197a24d80842e23d2f183

Observation 5daa96e6-79eb-40a8-9dfe-97ed952b6aaa · outbound

This paper cites Prompt engineering paradigms for medical applications: scoping review and recommendations for better practices.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Prompt engineering paradigms for medical applications: scoping review and recommendations for better practices

Reference 45

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no resolver link, observed 2026-08-12T15:15:54.684063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c59f0099-0b36-41ff-9dc1-f2c2f049d789 · outbound

This paper cites Prefer: Prompt ensemble learning via feedback-reflect-refine.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Prefer: Prompt ensemble learning via feedback-reflect-refine

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.279378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 71b9972d-50e2-4925-9c50-005651153976 · outbound

This paper cites Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Reference 47

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no resolver link, observed 2026-08-12T15:15:54.694818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7297d3cf-9060-4da7-bc89-4c12b6144821 · outbound

This paper cites Lungren, Tristan Naumann, Sheng Wang, and Hoifung Poon.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Lungren, Tristan Naumann, Sheng Wang, and Hoifung Poon

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.259877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T15:15:54.700023Z digest=sha256:83e43702e0528f944b384c8bd75ecc8bfa1aed8d0f1a08f091691f7f867f00a8

Observation 8c8d619a-9af2-42e9-ba3b-9bb4f8d31dd2 · outbound

This paper cites CLIP in Medical Imaging: A Survey.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models CLIP in Medical Imaging: A Survey

Reference 49

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no resolver link, observed 2026-08-12T15:15:54.705085Z

Source-reported events for the cited work

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Observation 004d6e10-9b51-448e-81ab-dc8132f452a3 · outbound

This paper cites Conditional prompt learning for vision-language models.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Conditional prompt learning for vision-language models

Reference 50

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 12a29ed9-5952-496a-8c6e-74d8374c24e2 · outbound

This paper cites Learning to prompt for vision-language models.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Learning to prompt for vision-language models

Reference 51

Resolution
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no resolver link, observed 2026-08-12T15:15:54.715591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:15:54.715591Z digest=sha256:942d6996a66e5f7d062ed3e10a5a4d4ec13ec1ffb2efa3cc51140a6e0cf0fe27

Observation 7cd2f9c1-228b-43e5-ba6a-7ec8422b804b · outbound

This paper cites Prompt-aligned gradient for prompt tuning.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Prompt-aligned gradient for prompt tuning

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.211590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 3c904205-fe18-4728-9897-3284d7e6c94e · outbound

This paper cites Prompt-aligned gradient for prompt tuning, 2024.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Prompt-aligned gradient for prompt tuning, 2024

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.194005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d9123879-8771-468f-b8e9-118416f124b8 · outbound

This paper cites Each dataset is described in terms of its imaging modality, target organ(s), number of classes, and dataset splits (train/validation/test).

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Each dataset is described in terms of its imaging modality, target organ(s), number of classes, and dataset splits (train/validation/test)

Reference 54

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d139fd1a-cdeb-4e23-9a9b-d592a80c03f0 · outbound

This paper cites It underscores BiomedCoOp’s robustness in adapting to limited data.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models It underscores BiomedCoOp’s robustness in adapting to limited data

Reference 55

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0e4711f6-2bea-4b23-bb0c-c246e4d05d9a · outbound

This paper cites A photo of [CLASS].

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models A photo of [CLASS]

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.137573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 1409ff9f-6daa-40e9-bd59-3d3c8e5c20dc · outbound

This paper cites A shorter context length, such as 4, achieves a better balance between base and novel accuracy, resulting in a higher har- monic mean (HM) score.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models A shorter context length, such as 4, achieves a better balance between base and novel accuracy, resulting in a higher har- monic mean (HM) score

Reference 57

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c7abd5b4-bc26-4854-8508-ac63f757af8f · outbound

This paper cites Figure S2 illus- trates the impact of increasing the selection threshold ( ζs) for the absolute value of the modified z-score to allow more prompts generated by the LLM to be used.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Figure S2 illus- trates the impact of increasing the selection threshold ( ζs) for the absolute value of the modified z-score to allow more prompts generated by the LLM to be used

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.098981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T15:15:54.755369Z digest=sha256:623a7414ef76e7b2f051f635ce3b351c63b5fa4750ee66c25d4fbc1115143ff2

Observation 2c095f47-2174-4319-a187-0d10ada21465 · outbound

This paper cites To verify the effect of prompt selection for SCCM, we compare the model per- formance with and without prompt selection.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models To verify the effect of prompt selection for SCCM, we compare the model per- formance with and without prompt selection

Reference 59

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verified fuzzy
raw_fallback, observed 2026-08-12T15:15:55.077191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T15:15:54.760634Z digest=sha256:4ab41df73ae7d1a4583b4fd5175d8ccd50394f184192fe09f4ec9c9c8b9e3c5b

Observation baf3c2bd-3840-4fd7-bdfd-d0bfcb5ab8f5 · outbound

This paper cites We also compare with zero- shot methods (in blue).

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models We also compare with zero- shot methods (in blue)

Reference 60

Resolution
malformed identifier
raw_fallback, observed 2026-08-12T15:15:55.058334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T15:15:54.766356Z digest=sha256:ac4673ccf7ed720ba2818150f70d9377405b3cf612fad83e9ffd35a044a0baf8

Observation aed8a65f-8f27-46dc-87c3-30e90a5ae40f · outbound

This paper cites an unresolved cited work.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Unresolved cited work

Reference 61

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unresolved
raw_fallback, observed 2026-08-12T15:15:55.040371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T15:15:54.771739Z digest=sha256:e62928051b920ffe58aa695e6af6f7ba1483e69e5519dbe65d23927379a1ce01

Observation 8c415c8a-fb2b-4ba0-97cf-4cc6eb6dfa92 · outbound

This paper cites an unresolved cited work.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models Unresolved cited work

Reference 62

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unresolved
raw_fallback, observed 2026-08-12T15:15:55.021807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T15:15:54.777585Z digest=sha256:1d69c95e4e84948256a940b2c68df87db6a3330109ec2ebc58bcaee2129b8420

Observation d3f83676-664a-4677-9770-a9014c985ded · outbound

This paper cites The image of a normal brain on MRI shows a clear differentiation between different brain regions with no disruptions.

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models The image of a normal brain on MRI shows a clear differentiation between different brain regions with no disruptions

Reference 63

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malformed identifier
raw_fallback, observed 2026-08-12T15:15:55.002755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T15:15:54.783799Z digest=sha256:520e4bc5c4705368c07bd1b15f7e3e72caf192b2c38cc7f233cc28feb7d3d6b5

Pith citing papers

Observation df1cf5b4-669b-405d-9ecf-db0404f80320 · inbound

Interpreting Biomedical VLMs on High-Imbalance Out-of-Distributions: An Insight into BiomedCLIP on Radiology cites this paper.

Interpreting Biomedical VLMs on High-Imbalance Out-of-Distributions: An Insight into BiomedCLIP on Radiology BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-15T19:56:23.296718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:56:23.202931Z digest=sha256:6fbfbc336ad4a3e2bfdd3b2cf204152fc04ae59341cf5e3c871cecd4555b193a