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Paper Citation Record · LEDGER

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning

As of 15 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2501.16720.

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

pith.paper-citation-record.v1
2501.16720 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T11:16:55.871753Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9523706f-8b3e-485b-ad61-3cc36bd0a659 · outbound

This paper cites Foundational Models Defining a New Era in Vision: A Survey and Outlook.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Foundational Models Defining a New Era in Vision: A Survey and Outlook

Reference 1

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Observation 62d5552b-eee4-4db6-affd-2b1b3ccc65f4 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning On the Opportunities and Risks of Foundation Models

Reference 2

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Observation 8c0331f0-67c2-4349-98d3-7ffebe31e317 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Food-101--mining discriminative components with random forests

Reference 3

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Observation 9136fc42-ee78-4a23-9498-b69e404f46eb · outbound

This paper cites Describing textures in the wild.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Describing textures in the wild

Reference 4

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Observation f332c9e0-09bf-4f11-b384-edd775385f98 · outbound

This paper cites Parameter-efficient fine-tuning of large-scale pre-trained language models.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Parameter-efficient fine-tuning of large-scale pre-trained language models

Reference 5

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Observation eed8ee98-451c-4d0a-93d0-2e58d7056806 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 6

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Observation afdf7af8-af52-44f8-aaa0-1bd6e4dd9f8e · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories

Reference 7

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Observation cbfaba35-7cf2-4336-a7a9-6451d4f40962 · outbound

This paper cites One-shot learning of object categories.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning One-shot learning of object categories

Reference 8

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Observation 47a52404-791b-4516-9694-168548db09f1 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Model-agnostic meta-learning for fast adaptation of deep networks

Reference 9

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Observation fa95dbc5-b0dc-4b91-874b-86f65b3efc9b · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Clip-adapter: Better vision-language models with feature adapters

Reference 10

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Observation 5afca768-451c-4b1e-aa94-7147c809a353 · outbound

This paper cites Domain aligned clip for few-shot classification.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Domain aligned clip for few-shot classification

Reference 11

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Observation 25da61a2-2cd4-4644-b654-fbae490bd101 · outbound

This paper cites A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

Reference 12

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Observation 1eab689b-af0b-45e8-a93a-5f06254bfe4a · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 13

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Observation 9e1bd683-827d-464e-a90c-8f183340f8bf · outbound

This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 14

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Observation c6797df0-c414-4b3c-8b09-2f7a5f36d415 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 15

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Observation 65e495a2-047c-435f-9897-d2382e32fc42 · outbound

This paper cites Natural adversarial examples.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Natural adversarial examples

Reference 16

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Observation cd56ec59-ec0b-4526-bbf9-bcc14f539f6a · outbound

This paper cites Parameter-efficient transfer learning for nlp.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Parameter-efficient transfer learning for nlp

Reference 17

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Observation d88fdf1c-754e-4175-b88b-a758618d64f3 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Lo RA : Low-rank adaptation of large language models

Reference 18

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Observation e7a3f1e7-442d-40ca-9c80-03f5afa00adc · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Scaling up visual and vision-language representation learning with noisy text supervision

Reference 19

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Observation 53e55b0f-27d3-4de7-9a82-c5f3c5fa61ea · outbound

This paper cites Maple: Multi-modal prompt learning.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Maple: Multi-modal prompt learning

Reference 20

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Observation 2b0f838c-deb3-4859-a2d9-68a4a54ff6e3 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Self-regulating prompts: Foundational model adaptation without forgetting

Reference 21

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Observation 693a81f2-5af4-4e67-967b-10d9fc82d8cd · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning 3d object representations for fine-grained categorization

Reference 22

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This paper cites Human-like systematic generalization through a meta-learning neural network.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Human-like systematic generalization through a meta-learning neural network

Reference 23

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One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Human-level concept learning through probabilistic program induction

Reference 24

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Observation 4c9e5814-d918-48a3-bf37-de5b0f3ffd4b · outbound

This paper cites Graphadapter: Tuning vision-language models with dual knowledge graph.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Graphadapter: Tuning vision-language models with dual knowledge graph

Reference 25

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Observation 8c4f7569-b980-453c-9d25-8627d8e79670 · outbound

This paper cites Patch-prompt aligned bayesian prompt tuning for vision-language models.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Patch-prompt aligned bayesian prompt tuning for vision-language models

Reference 26

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This paper cites Vision-and-Language Pretrained Models: A Survey.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Vision-and-Language Pretrained Models: A Survey

Reference 27

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One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Fine-Grained Visual Classification of Aircraft

Reference 28

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One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Foundation models for generalist medical artificial intelligence

Reference 29

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One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Automated flower classification over a large number of classes

Reference 30

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One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Cats and dogs

Reference 31

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Learning transferable visual models from natural language supervision

Reference 32

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This paper cites Do imagenet classifiers generalize to imagenet? In International conference on machine learning , pages 5389--5400.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Do imagenet classifiers generalize to imagenet? In International conference on machine learning , pages 5389--5400

Reference 33

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One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Imagenet large scale visual recognition challenge

Reference 34

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One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Unresolved cited work

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.822052Z digest=sha256:5e78da336a257142d88167d5365fc87f1988669de6fb95ba95dbf8237cfca3f8

Observation 4efb9d70-1b85-4157-8b72-22efc8664b11 · outbound

This paper cites Meta-adapter: An online few-shot learner for vision-language model.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Meta-adapter: An online few-shot learner for vision-language model

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:56.055832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.824585Z digest=sha256:7f1fe763af80b25c07f27b456b78182f6462e4820bc2a29f589c30354dbe014e

Observation f61a35a5-5348-4a2b-a8ae-71379ef11288 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-10T11:16:55.827000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T11:16:55.827000Z digest=sha256:65cc2e7e2372b5c2e11ea3566a8626c7ce93f4b22167a3394d13cb2ea77db5dc

Observation 3ef9b23e-3095-4c9e-82c9-da34c7478a3a · outbound

This paper cites Meta-adam: An meta-learned adaptive optimizer with momentum for few-shot learning.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Meta-adam: An meta-learned adaptive optimizer with momentum for few-shot learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:56.048150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.829477Z digest=sha256:d9f1bc5518d3473fe7798fc985f1accbcafbf69b2b97e79d998ae414da23436f

Observation 9dde82ee-8d7f-40a9-b55a-ceaea3958e6d · outbound

This paper cites Matching networks for one shot learning.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Matching networks for one shot learning

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:56.040192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.831820Z digest=sha256:4f8cb975f517a628ba61375a293130623daa43f183a00138f5932efc79992201

Observation a79b1e3f-1ea7-4252-b080-56c61f6d5e93 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Learning robust global representations by penalizing local predictive power

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:56.031424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.834105Z digest=sha256:568158a9734b3da29b025128ce9fab13fa2aefa6e9e7b18877117aca20dd14e7

Observation 2181057a-fb40-45cb-9ecf-68e4738a289e · outbound

This paper cites Generalizing from a few examples: A survey on few-shot learning.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Generalizing from a few examples: A survey on few-shot learning

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.836375Z digest=sha256:d4ad8c00ecbed92e3d3b385489638c1f9b9f429d4b4e6248f9dc438383202c9b

Observation 06e74c82-167d-4449-9f2a-c5972f39aa05 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Sun database: Large-scale scene recognition from abbey to zoo

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T11:16:55.838750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T11:16:55.838750Z digest=sha256:79a9cad095aaa65328cb0353bb8f5229e681e20309120e878914f6f606ddec6c

Observation af54916c-72b1-45d1-afbb-8940e57624cb · outbound

This paper cites Information-theoretic analysis of generalization capability of learning algorithms.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Information-theoretic analysis of generalization capability of learning algorithms

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:56.011664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.841156Z digest=sha256:9ae8e1c0a63bb38a30a376716a37397e9e29f3a6ecdbaf39da8f25365de8570c

Observation 9cbcc46a-c5a9-487c-95c9-f28a5c142a25 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Low-rank few-shot adaptation of vision-language models

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:56.003320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.843625Z digest=sha256:8e09d5f6765ad81c5ccf2db5546386ee97fd8762edae6d8ccc1eea0521a4ce51

Observation 7fce3fef-c95b-4b8e-8f8f-971b40630ea1 · outbound

This paper cites Tip-adapter: Training-free adaption of clip for few-shot classification.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Tip-adapter: Training-free adaption of clip for few-shot classification

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:55.995427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.845863Z digest=sha256:2a9c07856d6e3e50358f648ab0b96bb93a6805d183a9ab88200bf82270c9a8e0

Observation f63ec6af-3d41-4fc2-acda-9c46899a1baf · outbound

This paper cites LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T11:16:55.848370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T11:16:55.848370Z digest=sha256:7eb93a6de01b79f817d4d6e9d4c0b477c10707b7375962871eea097755dc25bf

Observation 89b7c98a-9707-4226-bc89-810b4e4639aa · outbound

This paper cites Metadiff: Meta-learning with conditional diffusion for few-shot learning.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Metadiff: Meta-learning with conditional diffusion for few-shot learning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:55.987047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.850992Z digest=sha256:2aa057c5caec5f95c9b126135aa1020197fb6ae797fc58b5225f0c8f41512550

Observation f849a88f-4123-49cb-a6b7-5616e843bf41 · outbound

This paper cites Vision-language models for vision tasks: A survey.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Vision-language models for vision tasks: A survey

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T11:16:55.853874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T11:16:55.853874Z digest=sha256:719b038d09ad888c868456f2d15e4961fc2b7d7ee7d578436e72e0302b5c065c

Observation 90fd58fe-f399-4b4f-a840-1b46090bcbc7 · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Conditional prompt learning for vision-language models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-10T11:16:55.856136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T11:16:55.856136Z digest=sha256:b0740df5fa5c85a96b46941315f36cf0f804d1b2409834094d3f9eb8c56b231b

Observation 2ff9b27f-5e0a-4dbf-a873-3e93b541050d · outbound

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

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Learning to prompt for vision-language models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T11:16:55.858668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T11:16:55.858668Z digest=sha256:6e805e7072cc62498ecdc9421f68a24fcdb29f70a443da3d0bf2efd02d0dfaa7

Observation 3eeadd1f-056f-4921-addb-a7bf17dbf710 · outbound

This paper cites A comprehensive survey on pretrained foundation models: A history from bert to chatgpt.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning A comprehensive survey on pretrained foundation models: A history from bert to chatgpt

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:55.968549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.860967Z digest=sha256:3b90c83973b383334e5f6ece737de7910df2fa8708a91c72e0b097a24f49dc7f

Observation b1590b2e-38ba-4756-b716-f1c709b429db · outbound

This paper cites Less is more: A closer look at semantic-based few-shot learning.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Less is more: A closer look at semantic-based few-shot learning

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:55.960626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.863289Z digest=sha256:361534fa879232390b9cddfa586b0732e754579fd045391c4c237731c4060d3f

Observation 4f70963f-176c-41d8-8167-f1868c471c5f · outbound

This paper cites Transductive few-shot learning with prototype-based label propagation by iterative graph refinement.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Transductive few-shot learning with prototype-based label propagation by iterative graph refinement

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T11:16:55.865641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T11:16:55.865641Z digest=sha256:35dfc11c46b9452d1132c6b9595085be2ae192ad45f9e96b29d470f8f8850aa2

Observation 1025d07f-df4f-4225-af26-e2468b510cff · outbound

This paper cites Asymmetry in low-rank adapters of foundation models.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning Asymmetry in low-rank adapters of foundation models

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T11:16:55.948202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T11:16:55.868295Z digest=sha256:65962b885049602100766a894f77581d4c2e8cef5c8759dd05f58195d359492e

Observation e5a737c6-6bc2-4ec5-b2d3-96086d5606b8 · outbound

This paper cites write newline.

One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning write newline

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T11:16:55.871753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T11:16:55.871753Z digest=sha256:b3043ed3e90c00c9a827054ad5dad4b940906d546941a5e211931d7af55c77fa

Pith citing papers

No inbound Pith citation observations are available.