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Paper Citation Record · LEDGER

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting

As of 9 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2507.20834.

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

pith.paper-citation-record.v1
2507.20834 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:17:46.565951Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T02:07:57.055712Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

53 of 53 outbound references displayed

  • verified exact0
  • verified fuzzy45
  • unresolved6
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e87f0dd0-161a-4c6f-a371-7943c3e68476 · outbound

This paper cites Analysis of representations for domain adaptation.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Analysis of representations for domain adaptation

Reference 1

Resolution
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Source-reported events for the cited work

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

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Observation a53a75d9-9601-4b18-bc5c-7cf6747271a8 · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Food-101 – mining discriminative components with random forests

Reference 2

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Source-reported events for the cited work

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

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Observation d61bc0de-2536-4925-8934-03bc7a17a1cb · outbound

This paper cites Self-supervised learning for few-shot im- age classification.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Self-supervised learning for few-shot im- age classification

Reference 3

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

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Observation 063c82c7-3e62-41da-8ded-91ccccaf2107 · outbound

This paper cites A Closer Look at Few-shot Classification.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting A Closer Look at Few-shot Classification

Reference 4

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Source-reported events for the cited work

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Observation aa5d77e4-db46-4068-a48d-f5bcae3e25c8 · outbound

This paper cites Describing textures in the wild.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Describing textures in the wild

Reference 5

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Source-reported events for the cited work

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

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Observation 6669eafe-2a71-4808-9650-122de2c2e10c · outbound

This paper cites Salun: Empowering machine un- learning via gradient-based weight saliency in both image classification and generation.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Salun: Empowering machine un- learning via gradient-based weight saliency in both image classification and generation

Reference 6

Resolution
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Source-reported events for the cited work

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

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Observation 8dd26877-cdac-4764-974d-d044718cc924 · outbound

This paper cites Learning gen- erative visual models from few training examples: An in- cremental bayesian approach tested on 101 object cate- gories.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Learning gen- erative visual models from few training examples: An in- cremental bayesian approach tested on 101 object cate- gories

Reference 7

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Source-reported events for the cited work

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

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Observation c311a435-f698-46df-b080-f1749172b1ff · outbound

This paper cites Fast machine unlearning without retraining through selective synaptic dampening.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Fast machine unlearning without retraining through selective synaptic dampening

Reference 8

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Source-reported events for the cited work

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

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Observation cf1df365-9633-442d-bf7e-4483d4ec0a72 · outbound

This paper cites Gen- eralization bounds for few-shot transfer learning with pre- trained classifiers.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Gen- eralization bounds for few-shot transfer learning with pre- trained classifiers

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 20ec5353-ac32-40e7-a6f5-e6d465c01fb1 · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Clip-adapter: Better vision-language models with feature adapters

Reference 10

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Source-reported events for the cited work

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

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Observation 2e1c73c0-c711-467f-a51d-43cb341d4071 · outbound

This paper cites Amne- siac machine learning, 2020.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Amne- siac machine learning, 2020

Reference 11

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Source-reported events for the cited work

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

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Observation 0cd64bc4-4868-4eb5-97ee-574dc66f5659 · outbound

This paper cites A kernel method for the two- sample-problem.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting A kernel method for the two- sample-problem

Reference 12

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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 2026-08-09T06:31:02.800959+00:00.

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Observation b68934a5-a705-49eb-9e1a-7aace2365897 · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Visual-language prompt tuning with knowledge-guided context optimization

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 2cfe05d8-a056-4b3d-b51c-a3dc26bd3af7 · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Tcp: Textual-based class-aware prompt tuning for visual-language model

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.628871Z

Source-reported events for the cited work

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

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Observation e87595d4-4d34-4af2-ad30-fce2353705cc · outbound

This paper cites Fine-grained visual-textual representation learning.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Fine-grained visual-textual representation learning

Reference 15

Resolution
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Source-reported events for the cited work

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

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Observation 2372bef2-687a-4518-bee5-1e5fda07e29a · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 16

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d4a46fef-096c-4858-84ab-45b6a75009a3 · outbound

This paper cites Pushing the limits of simple pipelines for few-shot learning: External data and fine-tuning make a difference.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Pushing the limits of simple pipelines for few-shot learning: External data and fine-tuning make a difference

Reference 17

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Source-reported events for the cited work

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

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Observation 92a673a4-df35-4787-b15e-1d0d747a1c94 · outbound

This paper cites Maple: Multi-modal prompt learning.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Maple: Multi-modal prompt learning

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation ed19e21b-4f83-495c-a386-9a8c0d95ee9e · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Self-regulating prompts: Foundational model adaptation without forgetting

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 2026-08-09T06:31:02.800959+00:00.

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Observation 58a058f3-1c47-41b5-a624-701f1a0acca5 · outbound

This paper cites Novel dataset for fine-grained image categorization.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Novel dataset for fine-grained image categorization

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation f4efcd33-869e-4e5f-978d-1e77ada0f895 · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting 3d object representations for fine-grained categorization

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 09556911-1a32-489d-ad09-11f4e930223c · outbound

This paper cites Clip adaptation by intra-modal overlap reduction.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Clip adaptation by intra-modal overlap reduction

Reference 22

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Source-reported events for the cited work

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

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Observation a76679e7-8828-4022-be5b-7ddd9491769f · outbound

This paper cites Kravets and V.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Kravets and V

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation f20802f4-4ae7-4902-80c1-59c7cf5dbb0f · outbound

This paper cites Namboodiri.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Namboodiri

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 221b4a48-3b3d-468e-8bf1-123010e200c6 · outbound

This paper cites Fine-grained visual classi- fication of aircraft, 2013.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Fine-grained visual classi- fication of aircraft, 2013

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation c99e44f6-affa-42af-84fb-9a2eb67442cc · outbound

This paper cites McInnes, J.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting McInnes, J

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.443666Z

Source-reported events for the cited work

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

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Observation 93f4f82e-b1f1-4bcf-970c-7b1dea0b8e41 · outbound

This paper cites Nilsback and Andrew Zisserman.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Nilsback and Andrew Zisserman

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.303151Z

Source-reported events for the cited work

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

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Observation 1a2f9074-be74-4770-9908-629fe5f2b143 · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Learning transferable visual models from natural language supervision

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 0954d543-7579-4a23-8b5b-414ecd494b0a · outbound

This paper cites Transtrum, James P.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Transtrum, James P

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.270536Z

Source-reported events for the cited work

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

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Observation e6d01a97-17f7-4d1a-8e25-b714f87c8ddc · outbound

This paper cites Consistency-guided prompt learning for vision-language models.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Consistency-guided prompt learning for vision-language models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.253970Z

Source-reported events for the cited work

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

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Observation a5001b1c-894b-45e3-b841-1dcef81a5b2c · outbound

This paper cites Membership inference attacks against machine learning models.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Membership inference attacks against machine learning models

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.236615Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:45.934876Z digest=sha256:90b2fcccd624c4d3407cc7d79ee82fda112108377ccf54fb8ea8fad1438dcf46

Observation f9967565-1ada-4777-b2d2-9bbb2fc581bf · outbound

This paper cites Plantdoc: A dataset for visual plant disease detection.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Plantdoc: A dataset for visual plant disease detection

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.218885Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.055416Z digest=sha256:20c5f895cf99d428a0a0349aae5e98cac41fe7d0e4d762f6402a44ed5e6bec6b

Observation ebdfa429-2fc2-4765-a9f5-a24c588fdbec · outbound

This paper cites Ucf101: A dataset of 101 human actions classes from videos in the wild, 2012.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Ucf101: A dataset of 101 human actions classes from videos in the wild, 2012

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.201265Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.188494Z digest=sha256:057097d8d9cc18a30f95d159cf2c68a7d4d40c4445e16e984cbfa612729bf291

Observation 909d7083-e049-43d9-8d35-7742fe696834 · outbound

This paper cites Thudi, G.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Thudi, G

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.185538Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.328351Z digest=sha256:3d697b810ce31fb1e9dbba172740a0ca1b7b0bae2b92a178661d2cdc3498c901

Observation 45ffc4d1-7323-4be9-b0da-f89653b611f7 · outbound

This paper cites Sus-x: Training-free name-only transfer of vision-language models.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Sus-x: Training-free name-only transfer of vision-language models

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.169528Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.456332Z digest=sha256:cf0f9b406becaf5875bdc92132f1cfe58dc487f6f63d36c3ec325064112a1a63

Observation 1e0e1660-4bde-4013-85ba-eaa08c421423 · outbound

This paper cites Matching networks for one shot learning.Ad- vances in neural information processing systems , 29, 2016.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Matching networks for one shot learning.Ad- vances in neural information processing systems , 29, 2016

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.153191Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.461679Z digest=sha256:7d912d05162016100270379d3477cd3a73cc4d058a92e2a50f52d0af7dc6d0f4

Observation c32a8145-62bc-4915-8b0b-5c49ec31846a · outbound

This paper cites Machine unlearning of features and la- bels.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Machine unlearning of features and la- bels

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.136502Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.467642Z digest=sha256:054bbaa9eab2d76b289179361498007079c5984367e78c3c3badab084598517a

Observation 34356e77-4f59-4267-b23c-32ca03bd907f · outbound

This paper cites Ehinger, Aude Oliva, and Antonio Torralba.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Ehinger, Aude Oliva, and Antonio Torralba

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.120703Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.473171Z digest=sha256:301aaabb93023206bd297aa516481e2498bc11b494d5af01886dc034dd2a0fa4

Observation 95521bed-b3d3-4868-bcd2-73ca75a93dba · outbound

This paper cites Sep: Self-enhanced prompt tuning for visual-language model,.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Sep: Self-enhanced prompt tuning for visual-language model,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.104885Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.480530Z digest=sha256:503a5eca1283df1bff33cab1eeae3b248761e48b984540437d01a19805405d53

Observation 4860d833-5e6c-4da6-abd0-33e415fb6809 · outbound

This paper cites an unresolved cited work.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-06T13:17:47.083027Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.490062Z digest=sha256:8172608e1847a037227472d88b0521d85a45fc5ff121b322f961bc53dcbd50b0

Observation 5e7ca6f1-8b13-4c7a-b9b5-f7e5ff812198 · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Low-rank few-shot adaptation of vision-language models

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.066177Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.498152Z digest=sha256:11e3908906f542629a00adbe63582e00c214c8a7dffa47bb587eaf2ba7644871

Observation 747dc2a3-5556-4c44-a87e-d36366b2bad6 · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Tip- adapter: Training-free adaption of clip for few-shot classi- fication

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.048312Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.505098Z digest=sha256:12e426e6430d9aeffb817e1898a6cd85efcaefcf477dbf771aaf362d4a10c371

Observation c9bcd62f-6b86-4389-86b0-ec195df1349e · outbound

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

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Learning to prompt for vision-language models

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.032178Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.510319Z digest=sha256:ace140a900674aa569c3bc4bf80f159aa564783477a396f007835e6641d5c530

Observation 543a361e-45b7-4828-ac6c-5885429606a0 · outbound

This paper cites Conditional prompt learning for vision-language mod- els.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Conditional prompt learning for vision-language mod- els

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:47.011756Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.517118Z digest=sha256:afaa434d4742d4fb6a307c8150549ec22260e75d5750c5903b8f3ebbfb5b66c3

Observation 3fa67172-6409-4bb2-8bf1-f3d575f9338b · outbound

This paper cites Prompt-aligned gradient for prompt tuning.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Prompt-aligned gradient for prompt tuning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:46.992721Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.523000Z digest=sha256:84e5c9ba2b98265e413f9a628990195b256df6a6a559f26e1041faee695bee3c

Observation a48813ed-26d0-439d-abb1-17d2ef7a1323 · outbound

This paper cites an unresolved cited work.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-06T13:17:46.971725Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.527499Z digest=sha256:5f6d07a9be134645618e492f064e6e322e47c5aeac0f595b0611a9671c4d12e8

Observation c264a5d7-3882-4804-a609-b2de63d30652 · outbound

This paper cites Our work builds upon the Self- Enhanced Prompt Tuning (SEP) method, which refines vi- sual prompts using a Token Fusion Module (TFM).

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Our work builds upon the Self- Enhanced Prompt Tuning (SEP) method, which refines vi- sual prompts using a Token Fusion Module (TFM)

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:46.954257Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.532634Z digest=sha256:9ed4c4212122e9aa3a6a5334fce987b5efdb0c12aa8e471a993a0a8b19075a8f

Observation 232ea8ac-63d0-4512-b6ce-a8a57cc1b5ef · outbound

This paper cites Ablation on α parameter of SEPRES.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Ablation on α parameter of SEPRES

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:46.936831Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.537273Z digest=sha256:9cfcb7de050dcf068cbfad5ef5800ffac5c405cc276912c238fd9b0d9c78ed2f

Observation a6c5c238-6288-434c-82e6-5bb2c5062d00 · outbound

This paper cites 4.1 of the main paper.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting 4.1 of the main paper

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:17:46.920396Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.542594Z digest=sha256:8ddbc005a18e4822c8e1e36679d7dca52ced3f78e20ed523de6da5283252049f

Observation 4eafbfeb-3f29-4b8a-8fd3-6827a90722ff · outbound

This paper cites an unresolved cited work.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-06T13:17:46.903485Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.548634Z digest=sha256:9d1326a078f2232a9e2fa2f7871f76f6bef57d71a56d71ee748216733a003bb7

Observation e61fdcd5-7465-489d-aa29-f3d1f88e83f7 · outbound

This paper cites an unresolved cited work.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-06T13:17:46.885505Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.553775Z digest=sha256:11b50c1cd64d129f4707b56f3d17813d47fa4e57662ae3a261e4265c2f315876

Observation 35733d7f-11fc-4d66-b7f4-e8836b043eea · outbound

This paper cites 5.3 evaluated under two distinct settings - excluding a subset and unlearning a subset.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting 5.3 evaluated under two distinct settings - excluding a subset and unlearning a subset

Reference 52

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T13:17:46.846620Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.560929Z digest=sha256:85aa1731b1c0c62642ff154a75133431332c41ff9ce67c1dd30f19d681bef5c7

Observation a9e8f19b-9671-4e38-beb4-7a0eb4a78047 · outbound

This paper cites Default runs unlearned CLIP.

Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting Default runs unlearned CLIP

Reference 53

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T13:17:46.749919Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T13:17:46.565951Z digest=sha256:6f3e7c8c6bdc5b380b8461cec418c64bf591eb5ddc28294c98e3451e64ecf127

Pith citing papers

Observation fd8765f9-8732-4ee0-aa3b-513ba2534aac · inbound

TCLA: Training-Free Class-wise Logit Adaptation for Medical Vision-Language Models cites this paper.

TCLA: Training-Free Class-wise Logit Adaptation for Medical Vision-Language Models Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-13T02:07:57.055712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T02:07:57.055712Z digest=sha256:4614e3c973d1aac29c64ae40c6c9172b4268e40a41496710c5de08678d1e8260