Clustering-based aggregate value regression | Paper Citation Record

Observation 90d1ca91-8276-4079-bd95-5608a80f50b5 · outbound

This paper cites Food-101–Mining Discriminative Components with Random Forests.

Clustering-based aggregate value regression Food-101–Mining Discriminative Components with Random Forests

Reference 1

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Observation 8b78154c-4f1e-44fc-9371-d680e3521bfb · outbound

This paper cites Information maximization for few-shot learning.

Clustering-based aggregate value regression Information maximization for few-shot learning

Reference 2

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Observation 39a59357-48a0-4112-b2de-7da251277a48 · outbound

This paper cites Describing Textures in the Wild.

Clustering-based aggregate value regression Describing Textures in the Wild

Reference 3

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Observation 3fbe639c-9639-45b1-8055-62c4d1d3b442 · outbound

This paper cites Imagenet: A Large-Scale Hierarchical Image Database.

Clustering-based aggregate value regression Imagenet: A Large-Scale Hierarchical Image Database

Reference 4

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Observation 1de50f76-72a8-4b45-9d8d-bb7ae6851b80 · outbound

This paper cites A normality test for multivariate dependent samples.Signal Processing, 201:108705, 2022.

Clustering-based aggregate value regression A normality test for multivariate dependent samples.Signal Processing, 201:108705, 2022

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Observation 90a68c74-1e9f-477d-8865-e6e25aee306b · outbound

This paper cites Joint normality test via two-dimensional projection.

Clustering-based aggregate value regression Joint normality test via two-dimensional projection

Reference 6

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Observation 56e020ab-3681-4916-afea-9e6bf667f38a · outbound

This paper cites Frus- tratingly easy test-time adaptation of vision-language models.

Clustering-based aggregate value regression Frus- tratingly easy test-time adaptation of vision-language models

Reference 7

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Observation 7f71ffdb-64fa-4fce-9bc1-f928ee83b0da · outbound

This paper cites Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories.

Clustering-based aggregate value regression Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories

Reference 8

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Observation d6fa09dd-05e1-4810-ad63-53d2ca21cdbd · outbound

This paper cites Diverse data augmenta- tion with diffusions for effective test-time prompt tuning.

Clustering-based aggregate value regression Diverse data augmenta- tion with diffusions for effective test-time prompt tuning

Reference 9

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Observation 2694e7e9-c4ca-4b2c-886c-dd0c199cc657 · outbound

This paper cites Online Gaussian Test-Time Adaptation of Vision-Language Models.

Clustering-based aggregate value regression Online Gaussian Test-Time Adaptation of Vision-Language Models

Reference 10

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Observation b7de665f-88e3-428d-b8a0-3744c53d1413 · outbound

This paper cites Clip-adapter: Better vision-language models with feature adapters.IJCV, 132(2), 2024.

Clustering-based aggregate value regression Clip-adapter: Better vision-language models with feature adapters.IJCV, 132(2), 2024

Reference 11

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Observation c40554e3-ee62-4180-b2cb-6dc86e23d573 · outbound

This paper cites Dota: Distributional test-time adaptation of vision-language models.arXiv preprint arXiv:2409.19375, 2024.

Clustering-based aggregate value regression Dota: Distributional test-time adaptation of vision-language models.arXiv preprint arXiv:2409.19375, 2024

Reference 12

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Observation c7e527ae-31af-406b-8402-07807ebac181 · outbound

This paper cites Discriminant analysis by gaussian mixtures.Journal of the Royal Statistical Society Series B: Statistical Methodology, 58(1):155–176, 1996.

Clustering-based aggregate value regression Discriminant analysis by gaussian mixtures.Journal of the Royal Statistical Society Series B: Statistical Methodology, 58(1):155–176, 1996

Reference 13

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Observation 355b4cb0-8060-4ba6-9953-819e6659e807 · outbound

This paper cites an unresolved cited work.

Clustering-based aggregate value regression Unresolved cited work

Reference 14

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Observation 64b9fd22-761f-4cc9-9657-9319104a64b4 · outbound

This paper cites The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization.

Clustering-based aggregate value regression The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization

Reference 15

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Observation 45a9910b-80fd-4e3b-8800-919a8e19b593 · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

Clustering-based aggregate value regression Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 16

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Observation 7ea610a9-deb9-4e5a-a088-33f06114cfa6 · outbound

This paper cites Natural Adversarial Examples.

Clustering-based aggregate value regression Natural Adversarial Examples

Reference 17

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Observation fa4324ce-67e4-4d57-a137-fd3c082adb02 · outbound

This paper cites A class of invariant consistent tests for multivariate normality.

Clustering-based aggregate value regression A class of invariant consistent tests for multivariate normality

Reference 18

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Observation 397582c5-e774-42f2-a9fa-3d3c014ba65c · outbound

This paper cites Test-time classifier adjustment module for model-agnostic domain generalization.

Clustering-based aggregate value regression Test-time classifier adjustment module for model-agnostic domain generalization

Reference 19

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Observation 2a20ae8d-6097-433a-a3f3-2cbdcb2afe22 · outbound

This paper cites Transductive inference for text classification using support vector machines.

Clustering-based aggregate value regression Transductive inference for text classification using support vector machines

Reference 20

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Observation 569e8fe7-5169-4eb3-8de1-eac3ef82e9f0 · outbound

This paper cites Label propagation for zero-shot classification with vision-language models.

Clustering-based aggregate value regression Label propagation for zero-shot classification with vision-language models

Reference 21

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Observation 7ebc2282-a86a-4294-a74a-444d235bcc3f · outbound

This paper cites Efficient test-time adaptation of vision-language models.

Clustering-based aggregate value regression Efficient test-time adaptation of vision-language models

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Observation 81837e87-b5d0-4867-a0d5-99dd83e54e41 · outbound

This paper cites 3D Object Representations for Fine-Grained Categorization.

Clustering-based aggregate value regression 3D Object Representations for Fine-Grained Categorization

Reference 23

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Observation fc0f9e89-3981-483e-9717-8224f5c8cac7 · outbound

This paper cites Estimation of the precision matrix of a singular wishart distribution and its application in high-dimensional data.

Clustering-based aggregate value regression Estimation of the precision matrix of a singular wishart distribution and its application in high-dimensional data

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Observation 7da17092-8ba0-4ebe-9071-75090ee8de85 · outbound

This paper cites Ra-tta: Retrieval-augmented test-time adaptation for vision-language models.

Clustering-based aggregate value regression Ra-tta: Retrieval-augmented test-time adaptation for vision-language models

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Observation d0846674-d7c5-4538-890f-7f44c7df4faa · outbound

This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation.

Clustering-based aggregate value regression BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

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Observation 0e1ea2d1-0263-4aab-9a9a-a59cdbabfb00 · outbound

This paper cites Align Before Fuse: Vision and Language Representation Learning with Momentum Distillation.

Clustering-based aggregate value regression Align Before Fuse: Vision and Language Representation Learning with Momentum Distillation

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Observation 7d37d181-df6a-43bd-8eff-2da847c72e74 · outbound

This paper cites Using discriminant analysis for multi-class classification: an experimental investigation.Knowledge and information systems, 10:453–472, 2006.

Clustering-based aggregate value regression Using discriminant analysis for multi-class classification: an experimental investigation.Knowledge and information systems, 10:453–472, 2006

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Observation 111fba3a-d99a-4450-8576-b5fdcb20ccfb · outbound

This paper cites Text and image are mutually beneficial: Enhancing training-free few-shot classification with clip.

Clustering-based aggregate value regression Text and image are mutually beneficial: Enhancing training-free few-shot classification with clip

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Observation 002f8c12-d5e0-4a28-934f-770d85ead807 · outbound

This paper cites Efficient and context-aware label propagation for zero-/few-shot training-free adaptation of vision-language model.

Clustering-based aggregate value regression Efficient and context-aware label propagation for zero-/few-shot training-free adaptation of vision-language model

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Observation aae444ed-16b2-4cba-b0c0-fa43a6968a8c · outbound

This paper cites Learning to propagate labels: Transductive propagation network for few-shot learning.

Clustering-based aggregate value regression Learning to propagate labels: Transductive propagation network for few-shot learning

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Observation 4863d18e-ed57-4585-aa11-7ab230f5bdba · outbound

This paper cites Swapprompt: Test-time prompt adaptation for vision-language models.

Clustering-based aggregate value regression Swapprompt: Test-time prompt adaptation for vision-language models

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Observation e93fba51-403d-48a0-ab30-f3aa4582f735 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Clustering-based aggregate value regression Fine-Grained Visual Classification of Aircraft

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Observation 447bddbc-e365-46c2-b941-1a472b7151b5 · outbound

This paper cites Test-time prompt tuning for zero-shot generalization in vision-language models.

Clustering-based aggregate value regression Test-time prompt tuning for zero-shot generalization in vision-language models

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Observation ebe59501-a5dc-410e-b687-1d890056db51 · outbound

This paper cites Black-box test-time prompt tuning for vision-language models.

Clustering-based aggregate value regression Black-box test-time prompt tuning for vision-language models

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Observation 1850004a-c0ca-42c3-b62a-361fd3934d3a · outbound

This paper cites A random-projection based test of gaussianity for stationary processes.Computational Statistics & Data Analysis, 75:124–141, 2014.

Clustering-based aggregate value regression A random-projection based test of gaussianity for stationary processes.Computational Statistics & Data Analysis, 75:124–141, 2014

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Observation b46de9d6-7537-493b-8652-abd1f8ab5a81 · outbound

This paper cites Automated Flower Classification over a Large Number of Classes.

Clustering-based aggregate value regression Automated Flower Classification over a Large Number of Classes

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Observation e2874cb3-e58f-4d54-a276-4131a85998df · outbound

This paper cites Cats and Dogs.

Clustering-based aggregate value regression Cats and Dogs

Reference 38

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Observation edecc1ae-dafc-41dd-b97f-bcac466f34a8 · outbound

This paper cites The matrix cookbook.Technical University of Denmark, 7(15):510, 2008.

Clustering-based aggregate value regression The matrix cookbook.Technical University of Denmark, 7(15):510, 2008

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Observation 7d0f67cd-8566-42a9-85ac-b809310390d8 · outbound

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

Clustering-based aggregate value regression Learning transferable visual models from natural language supervision

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Observation ab303d02-910e-4206-a492-737a4d9f5e20 · outbound

This paper cites Do imagenet classifiers generalize to imagenet? InICML, 2019.

Clustering-based aggregate value regression Do imagenet classifiers generalize to imagenet? InICML, 2019

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Observation 6f84c52a-c69e-4cba-839c-822755393e11 · outbound

This paper cites An extension of shapiro and wilk’s w test for normality to large samples.

Clustering-based aggregate value regression An extension of shapiro and wilk’s w test for normality to large samples

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Observation 41539fea-444c-484d-abae-62906e86481a · outbound

This paper cites Align your prompts: Test-time prompting with distribution alignment for zero-shot generalization.

Clustering-based aggregate value regression Align your prompts: Test-time prompting with distribution alignment for zero-shot generalization

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Observation d839f897-7875-4b26-8910-aa7763776cb9 · outbound

This paper cites An analysis of variance test for normality.Biometrika, 52(3):591– 611, 1965.

Clustering-based aggregate value regression An analysis of variance test for normality.Biometrika, 52(3):591– 611, 1965

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Observation f6b610c0-94f4-4320-8257-94b9d4f41f78 · outbound

This paper cites High-dimensional linear discriminant analysis classifier for spiked covariance model.Journal of Machine Learning Research, 21(112):1–24, 2020.

Clustering-based aggregate value regression High-dimensional linear discriminant analysis classifier for spiked covariance model.Journal of Machine Learning Research, 21(112):1–24, 2020

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Observation 7206b777-a3b2-40e3-8f9d-7e2e864798aa · outbound

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

Clustering-based aggregate value regression UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

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This paper cites Just shift it: Test-time prototype shifting for zero-shot generalization with vision-language models.

Clustering-based aggregate value regression Just shift it: Test-time prototype shifting for zero-shot generalization with vision-language models

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Observation e535d5c7-8b48-487f-ba52-ba8945c5ef9b · outbound

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

Clustering-based aggregate value regression Sus-x: Training-free name-only transfer of vision-language models

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Observation 162ff320-0092-479c-a30b-ecb1ddc0b4fd · outbound

This paper cites Discriminative gaussian process latent variable model for classification.

Clustering-based aggregate value regression Discriminative gaussian process latent variable model for classification

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This paper cites Tent: Fully test-time adaptation by entropy minimization.

Clustering-based aggregate value regression Tent: Fully test-time adaptation by entropy minimization

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Observation 5f555050-64ef-4ebe-80e8-5515718e6d20 · outbound

This paper cites Learning Robust Global Representations by Penalizing Local Rredictive Power.

Clustering-based aggregate value regression Learning Robust Global Representations by Penalizing Local Rredictive Power

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Observation 2ddeb9a1-8c32-4145-ad68-e8f0277f3b28 · outbound

This paper cites A hard-to-beat baseline for training-free clip-based adaptation.

Clustering-based aggregate value regression A hard-to-beat baseline for training-free clip-based adaptation

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This paper cites Is less more? exploring token condensation as training-free adaptation for clip.

Clustering-based aggregate value regression Is less more? exploring token condensation as training-free adaptation for clip

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Observation a1689d06-8da2-4e84-bef0-fe47e69904f1 · outbound

This paper cites Sun Database: Large-Scale Scene Recognition from Abbey to Zoo.

Clustering-based aggregate value regression Sun Database: Large-Scale Scene Recognition from Abbey to Zoo

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This paper cites Dynaprompt: Dynamic test-time prompt tuning.

Clustering-based aggregate value regression Dynaprompt: Dynamic test-time prompt tuning

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Observation 9dea127c-df4e-499f-a6df-aa24b25d14cd · outbound

This paper cites C-tpt: Calibrated test-time prompt tuning for vision-language models via text feature dispersion.

Clustering-based aggregate value regression C-tpt: Calibrated test-time prompt tuning for vision-language models via text feature dispersion

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Observation 6d269f3b-4654-4d03-88c0-a90b19c14e8b · outbound

This paper cites Task residual for tuning vision- language models.

Clustering-based aggregate value regression Task residual for tuning vision- language models

Reference 57

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This paper cites On the test-time zero-shot generalization of vision- language models: Do we really need prompt learning? InCVPR, 2024.

Clustering-based aggregate value regression On the test-time zero-shot generalization of vision- language models: Do we really need prompt learning? InCVPR, 2024

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This paper cites Realistic test-time adaptation of vision-language models.

Clustering-based aggregate value regression Realistic test-time adaptation of vision-language models

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Observation 100871cc-205f-4ed6-a375-846a5ba4df64 · outbound

This paper cites Boosting vision-language models with transduction.

Clustering-based aggregate value regression Boosting vision-language models with transduction

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Observation 26a95091-b029-4fad-95d1-6b0033a7c385 · outbound

This paper cites Boosting vision-language models for histopathology classification: Predict all at once.

Clustering-based aggregate value regression Boosting vision-language models for histopathology classification: Predict all at once

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Observation 1388aee8-9ae9-4bb7-bc11-1804b6419dd0 · outbound

This paper cites Dual prototype evolving for test-time generalization of vision-language models.

Clustering-based aggregate value regression Dual prototype evolving for test-time generalization of vision-language models

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Clustering-based aggregate value regression Historical test-time prompt tuning for vision foundation models

Reference 63

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Clustering-based aggregate value regression Tip-adapter: Training-free adaption of clip for few-shot classification

Reference 64

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Clustering-based aggregate value regression Boostadapter: Improving vision-language test-time adaptation via regional bootstrapping

Reference 65

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Clustering-based aggregate value regression Dual memory networks: A versatile adaptation approach for vision-language models

Reference 66

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Clustering-based aggregate value regression Dpcore: Dynamic prompt coreset for continual test-time adaptation

Reference 67

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Clustering-based aggregate value regression Learning with local and global consistency

Reference 68

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Clustering-based aggregate value regression Bayesian test-time adaptation for vision-language models

Reference 69

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This paper cites Not all features matter: Enhancing few-shot clip with adaptive prior refinement.

Clustering-based aggregate value regression Not all features matter: Enhancing few-shot clip with adaptive prior refinement

Reference 70

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Clustering-based aggregate value regression Enhancing zero-shot vision models by label-free prompt distribution learning and bias correcting

Reference 71

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Clustering-based aggregate value regression Awt: Transferring vision-language models via augmentation, weighting, and transportation

Reference 72

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This paper cites Efficient Test-Time Prompt Tuning for Vision-Language Models.

Clustering-based aggregate value regression Efficient Test-Time Prompt Tuning for Vision-Language Models

Reference 73

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Clustering-based aggregate value regression Laplacian regularized few-shot learning

Reference 74

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