CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values | Paper Citation Record

Observation 533fa2e6-2a97-4732-8b0f-eb7a2e0426e5 · outbound

This paper cites GPT-4 Technical Report.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values GPT-4 Technical Report

Reference 1

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This paper cites Intrinsic dimensionality explains the effective- ness of language model fine-tuning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Intrinsic dimensionality explains the effective- ness of language model fine-tuning

Reference 2

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This paper cites Dataset of breast ultrasound images.Data in brief, 28:104863.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Dataset of breast ultrasound images.Data in brief, 28:104863

Reference 3

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This paper cites Proker: A kernel perspective on few-shot adaptation of large vision-language models.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Proker: A kernel perspective on few-shot adaptation of large vision-language models

Reference 4

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Observation a7c657f1-a313-4395-832b-2c72490e374a · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Xcoop: Explainable prompt learning for computer- aided diagnosis via concept-guided context optimization

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.216208Z

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Making the most of text semantics to improve biomedical vision–language processing

Reference 6

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Observation f264135b-7f71-4abe-a227-2b418334a2d0 · outbound

This paper cites Borkowski, Marilyn M.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Borkowski, Marilyn M

Reference 7

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Observation 89e889f9-4682-4010-8ef0-6915abbec4f6 · outbound

This paper cites Food-101–mining discriminative components with random forests.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Food-101–mining discriminative components with random forests

Reference 8

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Observation 7e686aec-4dc5-49b5-8282-66ce42749e1f · outbound

This paper cites Domain-controlled prompt learning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Domain-controlled prompt learning

Reference 9

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Observation 7e377c8e-3d36-4d0d-ab44-3ed399f3dbfc · outbound

This paper cites Knee osteoarthritis severity grading dataset.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Knee osteoarthritis severity grading dataset

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.218850Z

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Observation ad5324b2-bca9-42d1-956d-113092f67dc9 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values gscorecam: What objects is clip looking at? InProceedings of the Asian Conference on Computer Vision, pages 1959–1975

Reference 11

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This paper cites Adapt- former: Adapting vision transformers for scalable visual recognition.Advances in Neural Information Processing Systems, 35:16664–16678.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Adapt- former: Adapting vision transformers for scalable visual recognition.Advances in Neural Information Processing Systems, 35:16664–16678

Reference 12

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Observation 06b09df2-4f47-4ce4-b2ad-65ac6694efc6 · outbound

This paper cites Describing textures in the wild.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Describing textures in the wild

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.353160Z

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Observation 06c553b8-a234-4820-8fc1-d11b13efda97 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:56:46.005598Z

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Observation 1faa7fc3-e9bc-4eda-a62b-fd20924fc40c · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Imagenet: A large-scale hierarchical image database

Reference 15

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Observation cf7df616-77bc-401a-97b4-8c0e47ead3f2 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Does clip benefit visual question answering in the medical domain as much as it does in the general domain?

Reference 16

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This paper cites Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories

Reference 17

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Observation 3de5c3cf-6734-4c7e-9a89-c8653d1bf5e7 · outbound

This paper cites Interpreting CLIP's Image Representation via Text-Based Decomposition.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Interpreting CLIP's Image Representation via Text-Based Decomposition

Reference 18

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This paper cites Clip-adapter: Better vision-language models with feature adapters.International Journal of Computer Vision, 132(2):581–595.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Clip-adapter: Better vision-language models with feature adapters.International Journal of Computer Vision, 132(2):581–595

Reference 19

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This paper cites Imagenet auto-annotation with segmentation propagation.International Journal of Computer Vision, 110(3):328–348.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Imagenet auto-annotation with segmentation propagation.International Journal of Computer Vision, 110(3):328–348

Reference 20

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This paper cites Parameter-efficient transfer learning with diff pruning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Parameter-efficient transfer learning with diff pruning

Reference 21

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This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.J-STARS, 12(7):2217–2226.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.J-STARS, 12(7):2217–2226

Reference 22

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Observation 2a0abd87-4ade-406f-a9e5-8d9c2a3d2105 · outbound

This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 23

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This paper cites Natural adversarial examples.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Natural adversarial examples

Reference 24

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This paper cites Nxmtransformer: semi-structured sparsification for natural language understanding via admm.Advances in neural information processing systems, 34: 1818–1830.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Nxmtransformer: semi-structured sparsification for natural language understanding via admm.Advances in neural information processing systems, 34: 1818–1830

Reference 25

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Observation ff141ef5-a5b6-4053-82d2-c7e61a7fe838 · outbound

This paper cites Parameter-efficient transfer learning for nlp.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Parameter-efficient transfer learning for nlp

Reference 26

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Observation 0e94d59a-5196-450f-b1c0-b81017d33df0 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Lora: Low-rank adaptation of large language models

Reference 27

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Observation 5db304b2-26a3-4684-b42a-a4b648a4d4e3 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Lp++: A surprisingly strong linear probe for few-shot clip

Reference 28

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Observation d19ffe23-ef9d-4776-b362-0dfad662f787 · outbound

This paper cites Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from ct-radiography.Scientific Reports, 12(1):1–14.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from ct-radiography.Scientific Reports, 12(1):1–14

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.307575Z

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Observation 9f248b4f-9ca5-480e-8979-d96c9d015bac · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Scaling up visual and vision-language representation learning with noisy text supervision

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.402750Z

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Observation fc2f5acf-8726-447c-9c49-67fe7ab6a40e · outbound

This paper cites Visual prompt tuning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Visual prompt tuning

Reference 31

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Observation 2c9eb32a-2a68-46e4-a067-916104d3b9e8 · outbound

This paper cites Compacter: Efficient low-rank hypercomplex adapter layers.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Compacter: Efficient low-rank hypercomplex adapter layers

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.374775Z

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Observation 3857d8ed-b090-4a9e-aeff-a1b4d4081332 · outbound

This paper cites Multi-class texture analysis in colorectal cancer histology.Scientific reports, 6(1):1–11.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Multi-class texture analysis in colorectal cancer histology.Scientific reports, 6(1):1–11

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.406018Z

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Observation 848acc46-63f5-455d-b75c-038a2aa792f6 · outbound

This paper cites Kermany, Michael Goldbaum, et al.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Kermany, Michael Goldbaum, et al

Reference 34

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Observation a3fb7660-8c44-4ab4-b78a-07d91a053063 · outbound

This paper cites Maple: Multi-modal prompt learning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Maple: Multi-modal prompt learning

Reference 35

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Observation e339d494-6064-40bc-8a42-8aa9288e9ece · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Self-regulating prompts: Foundational model adaptation without forgetting

Reference 36

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Observation 07a9159c-0162-459f-af3d-b3032a8304ab · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Medclip-sam: Bridging text and image towards universal medical image segmentation

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.281463Z

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Observation 88b295f4-746b-4068-8972-e2af30dfa4ab · outbound

This paper cites Medclip-samv2: Towards universal text-driven medical image segmentation.Medical Image Analysis, page 103749.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Medclip-samv2: Towards universal text-driven medical image segmentation.Medical Image Analysis, page 103749

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.378519Z

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Observation 6eaddcca-d63a-4f28-90af-e405d2d32914 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Biomedcoop: Learning to prompt for biomedical vision-language models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.272112Z

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Observation f92e7d54-d7a0-48c5-b7ea-f62b4824189a · outbound

This paper cites 3d object representations for fine-grained categorization.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values 3d object representations for fine-grained categorization

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.274957Z

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Observation 804ac4b9-b880-45a3-95c7-c728914c3814 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Automatic no-reference quality assessment for retinal fundus images using vessel segmentation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.371205Z

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Observation 1f86f39d-fc62-47f8-be3f-d44616a2fe8f · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:56:45.944281Z

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Observation e9cbea95-8d88-4b83-bfa9-7f072393afc0 · outbound

This paper cites Measuring the intrinsic dimension of objective landscapes.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Measuring the intrinsic dimension of objective landscapes

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.382172Z

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Observation 7c3c92b4-c35e-4d7f-9856-dc309bed2e3c · outbound

This paper cites Prefix-tuning: Optimizing continuous prompts for generation.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Prefix-tuning: Optimizing continuous prompts for generation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.359999Z

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Observation 33523daa-722b-4eb3-862f-fc3862b74efc · outbound

This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:56:45.955971Z

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Observation 54b8b752-c796-4766-b965-cb93a83d2494 · outbound

This paper cites Scaling & shifting your features: A new baseline for efficient model tuning.Advances in Neural Information Processing Systems, 35:109–123.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Scaling & shifting your features: A new baseline for efficient model tuning.Advances in Neural Information Processing Systems, 35:109–123

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.367429Z

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Observation a102ab94-6038-4da3-8024-47decc624aca · outbound

This paper cites Decoupled Weight Decay Regularization.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Decoupled Weight Decay Regularization

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:56:45.966402Z

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Observation 559ef509-3203-4482-8681-104cec7aa161 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Fine-Grained Visual Classification of Aircraft

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:56:45.933854Z

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Observation 9d8a16cc-e3e4-44bb-870d-1edd4cadbf2c · outbound

This paper cites Pissa: Principal singular values and singular vectors adaptation of large language models.Advances in Neural Information Processing Systems, 37:121038– 121072.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Pissa: Principal singular values and singular vectors adaptation of large language models.Advances in Neural Information Processing Systems, 37:121038– 121072

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.431612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0d89dcde-e896-4c8e-a3b3-6c1bd6e7ee2e · outbound

This paper cites Brain tumor mri dataset.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Brain tumor mri dataset

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.392730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 099d17cc-ff7f-418e-9568-957d33f24a30 · outbound

This paper cites Automated flower classification over a large number of classes.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Automated flower classification over a large number of classes

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.363462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e5a3e79e-60c6-470c-b931-458d8bb16c04 · outbound

This paper cites Cats and dogs.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Cats and dogs

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.343904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 57344476-a5b9-4655-8890-990c062fb486 · outbound

This paper cites Sam-parser: Fine-tuning sam efficiently by parameter space reconstruction.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Sam-parser: Fine-tuning sam efficiently by parameter space reconstruction

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.428096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2f8b8c00-1516-4a18-8b5a-c4a8856af946 · outbound

This paper cites Adapterfusion: Non-destructive task composition for transfer learning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Adapterfusion: Non-destructive task composition for transfer learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.409357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9bacc35b-6a1c-4d7e-9ad8-13494526dbdb · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Kvasir: A multi-class image dataset for computer aided gastrointestinal disease detection

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.335223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f06d3db4-87b9-46b0-aaf4-2e091ccf1c4b · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Indian diabetic retinopathy image dataset (idrid)

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.332151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 20b7b154-83be-4e12-9c7e-099de07a6b0f · outbound

This paper cites Learning transferable visual models from natural language supervision.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Learning transferable visual models from natural language supervision

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.315131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8ff708a2-cfa4-4723-8a60-f63f337c2806 · outbound

This paper cites an unresolved cited work.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Unresolved cited work

Reference 58

Resolution: parse uncertain; raw_fallback, observed 2026-05-18T18:56:47.421054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 29388302-d5d5-42ac-aeaf-d3d24ff0706d · outbound

This paper cites Grounding DINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Models.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Grounding DINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:56:45.939464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 96520538-42d3-4598-a398-2305c7cd0a57 · outbound

This paper cites Learning multiple visual domains with residual adapters.Advances in neural information processing systems, 30.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Learning multiple visual domains with residual adapters.Advances in neural information processing systems, 30

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.328652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 494ba83a-a8fe-44af-b5a8-3b56be0ac8bb · outbound

This paper cites Do imagenet classifiers generalize to imagenet? InICML, pages 5389–5400.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Do imagenet classifiers generalize to imagenet? InICML, pages 5389–5400

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.412437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8906ab95-3df8-4330-bb77-388259b533ec · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 62

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:56:45.995918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b31418e6-5658-4dfb-b608-ea00b4d1a65c · outbound

This paper cites TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:56:45.976425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 355a03de-17ab-438b-91ea-a62309c57547 · outbound

This paper cites Singular value fine-tuning: Few-shot segmentation requires few-parameters fine-tuning.Advances in neural information processing systems, 35:37484–37496.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Singular value fine-tuning: Few-shot segmentation requires few-parameters fine-tuning.Advances in neural information processing systems, 35:37484–37496

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.297840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation df5a1dae-dbd3-42bc-9b12-de1d5d8a7b0f · outbound

This paper cites Tahir, Muhammad E.H.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Tahir, Muhammad E.H

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.311173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 42838e99-fa3f-4039-afa0-b9a5367f1c94 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific data, page 180161.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific data, page 180161

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.399269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 03f9afa4-48c9-4f1d-8146-041e45b14650 · outbound

This paper cites Visualizing data using t-sne.Journal of Machine Learning Research, 9(86):2579–2605.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Visualizing data using t-sne.Journal of Machine Learning Research, 9(86):2579–2605

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.347057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation af41b729-3a1f-4d52-a684-c727f05b3b30 · outbound

This paper cites Learning robust global representations by penalizing local predictive power.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Learning robust global representations by penalizing local predictive power

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.389438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3510163b-0c1e-4881-af56-20a4047bb684 · outbound

This paper cites A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:56:45.991085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 47e6cc0f-0091-4217-bda3-6c3a2360a648 · outbound

This paper cites Sun database: Large- scale scene recognition from abbey to zoo.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Sun database: Large- scale scene recognition from abbey to zoo

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.396029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f5ab602a-0f48-4b9d-9200-e3ad7e12a684 · outbound

This paper cites Advances in med- ical image segmentation: A comprehensive review of traditional, deep learning and hybrid approaches.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Advances in med- ical image segmentation: A comprehensive review of traditional, deep learning and hybrid approaches

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.284669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 10250800-a55d-4352-a870-2c3a762d6421 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Visual-language prompt tuning with knowledge-guided context optimization

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.424576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ccc4f19b-234e-4dd4-aefd-60517db83e46 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Visual-language prompt tuning with knowledge-guided context optimization

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.259551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b484a3ea-ecfb-4502-aa04-990bb8029f37 · outbound

This paper cites Tcp: Textual-based class-aware prompt tuning for visual- language model.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Tcp: Textual-based class-aware prompt tuning for visual- language model

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.338267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0dfb92f4-efb6-4d72-b6cf-8cfa9ed3b615 · outbound

This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.415789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation aadc4da3-3bcf-4e96-8d0b-22be2be15e5d · outbound

This paper cites Low-rank few-shot adaptation of vision-language models.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Low-rank few-shot adaptation of vision-language models

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.278196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 52ab96e8-5928-43c6-a84d-6a19a4021378 · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 77

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:56:45.960924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a849a1f4-8681-46ac-8484-ba68e78fe3b8 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Reference 78

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T18:56:45.928999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 40a5174e-b514-49f2-aa00-8c6b4542e7f7 · outbound

This paper cites LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

Reference 79

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:56:45.981251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ca41c26c-dc8c-40e7-9617-b73f38d2ae1d · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Lungren, Tristan Naumann, Sheng Wang, and Hoifung Poon

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.256698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 806eeee6-c2aa-4d2f-b038-901fa6512f73 · outbound

This paper cites CLIP in Medical Imaging: A Survey.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values CLIP in Medical Imaging: A Survey

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:56:45.950305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4e9ca3b1-a490-4053-8039-86b405908467 · outbound

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

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Conditional prompt learning for vision-language models

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.239075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c2cc51d0-6579-4e96-88a4-364789f79080 · outbound

This paper cites Learning to prompt for vision-language models.IJCV, 130(9):2337–2348.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Learning to prompt for vision-language models.IJCV, 130(9):2337–2348

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.385678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3f436a21-1d8f-405b-b6a6-050776f648fe · outbound

This paper cites Prompt-aligned gradient for prompt tuning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Prompt-aligned gradient for prompt tuning

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.235685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8340cb08-a5da-4d24-afa8-15818451c3d6 · outbound

This paper cites Prompt-aligned gradient for prompt tuning.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Prompt-aligned gradient for prompt tuning

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.253761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 67a79dec-01b7-4218-a42c-1fd1f76fbb1c · outbound

This paper cites Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models

Reference 86

Resolution: malformed identifier; arxiv_id, observed 2026-05-18T18:56:45.971143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 64d032c1-3714-4f25-bf8c-d60eab6850b5 · outbound

This paper cites L" denotes layer while “H.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values L" denotes layer while “H

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T18:56:47.262907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a87230f2-2d21-4041-ac90-83530fe0aa92 · outbound

This paper cites an unresolved cited work.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Unresolved cited work

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:56:46.000619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cb6afaba-a9dc-477b-8248-38c532fc32df · outbound

This paper cites an unresolved cited work.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values Unresolved cited work

Reference 89

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:56:45.922830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers