Aligned Contrastive Loss for Long-Tailed Recognition | Paper Citation Record

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This paper cites A systematic study of the class imbalance problem in convo- lutional neural networks.Neural networks, 106:249–259,.

Aligned Contrastive Loss for Long-Tailed Recognition A systematic study of the class imbalance problem in convo- lutional neural networks.Neural networks, 106:249–259,

Reference 1

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This paper cites What is the effect of im- portance weighting in deep learning? InInternational con- ference on machine learning, pages 872–881.

Aligned Contrastive Loss for Long-Tailed Recognition What is the effect of im- portance weighting in deep learning? InInternational con- ference on machine learning, pages 872–881

Reference 2

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This paper cites Unsupervised learning of visual features by contrasting cluster assignments.Ad- vances in neural information processing systems, 33:9912– 9924, 2020.

Aligned Contrastive Loss for Long-Tailed Recognition Unsupervised learning of visual features by contrasting cluster assignments.Ad- vances in neural information processing systems, 33:9912– 9924, 2020

Reference 3

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This paper cites A simple framework for contrastive learning of visual representations.

Aligned Contrastive Loss for Long-Tailed Recognition A simple framework for contrastive learning of visual representations

Reference 4

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This paper cites Big self-supervised mod- els are strong semi-supervised learners.Advances in neural information processing systems, 33:22243–22255, 2020.

Aligned Contrastive Loss for Long-Tailed Recognition Big self-supervised mod- els are strong semi-supervised learners.Advances in neural information processing systems, 33:22243–22255, 2020

Reference 5

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This paper cites Exploring simple siamese rep- resentation learning.

Aligned Contrastive Loss for Long-Tailed Recognition Exploring simple siamese rep- resentation learning

Reference 6

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This paper cites An empirical study of training self-supervised vision transformers.

Aligned Contrastive Loss for Long-Tailed Recognition An empirical study of training self-supervised vision transformers

Reference 7

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This paper cites AutoAugment: Learning Augmentation Policies from Data.

Aligned Contrastive Loss for Long-Tailed Recognition AutoAugment: Learning Augmentation Policies from Data

Reference 8

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This paper cites Parametric contrastive learning.

Aligned Contrastive Loss for Long-Tailed Recognition Parametric contrastive learning

Reference 9

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This paper cites Generalized parametric contrastive learn- ing.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

Aligned Contrastive Loss for Long-Tailed Recognition Generalized parametric contrastive learn- ing.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023

Reference 10

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This paper cites Class-balanced loss based on effective number of samples.

Aligned Contrastive Loss for Long-Tailed Recognition Class-balanced loss based on effective number of samples

Reference 11

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This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

Aligned Contrastive Loss for Long-Tailed Recognition Improved Regularization of Convolutional Neural Networks with Cutout

Reference 12

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Aligned Contrastive Loss for Long-Tailed Recognition Unresolved cited work

Reference 13

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This paper cites Prob- abilistic contrastive learning for long-tailed visual recogni- tion.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.

Aligned Contrastive Loss for Long-Tailed Recognition Prob- abilistic contrastive learning for long-tailed visual recogni- tion.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024

Reference 14

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This paper cites Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error.

Aligned Contrastive Loss for Long-Tailed Recognition Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error

Reference 15

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This paper cites Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020.

Aligned Contrastive Loss for Long-Tailed Recognition Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020

Reference 16

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This paper cites Deep residual learning for image recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Deep residual learning for image recognition

Reference 17

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This paper cites Momentum contrast for unsupervised visual rep- resentation learning.

Aligned Contrastive Loss for Long-Tailed Recognition Momentum contrast for unsupervised visual rep- resentation learning

Reference 18

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This paper cites Disentangling label dis- tribution for long-tailed visual recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Disentangling label dis- tribution for long-tailed visual recognition

Reference 19

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This paper cites Subclass-balancing contrastive learning for long- tailed recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Subclass-balancing contrastive learning for long- tailed recognition

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:33.123506Z

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This paper cites Learning deep representation for imbalanced classifi- cation.

Aligned Contrastive Loss for Long-Tailed Recognition Learning deep representation for imbalanced classifi- cation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:33.108538Z

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This paper cites Decoupling Representation and Classifier for Long-Tailed Recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Decoupling Representation and Classifier for Long-Tailed Recognition

Reference 22

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This paper cites Exploring balanced feature spaces for representation learn- ing.

Aligned Contrastive Loss for Long-Tailed Recognition Exploring balanced feature spaces for representation learn- ing

Reference 23

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This paper cites Cost-sensitive learn- ing of deep feature representations from imbalanced data.

Aligned Contrastive Loss for Long-Tailed Recognition Cost-sensitive learn- ing of deep feature representations from imbalanced data

Reference 24

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This paper cites Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673,.

Aligned Contrastive Loss for Long-Tailed Recognition Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673,

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This paper cites Targeted su- pervised contrastive learning for long-tailed recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Targeted su- pervised contrastive learning for long-tailed recognition

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:33.055675Z

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This paper cites Inducing neural collapse in deep long- tailed learning.

Aligned Contrastive Loss for Long-Tailed Recognition Inducing neural collapse in deep long- tailed learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:33.041577Z

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This paper cites Large-scale long-tailed recognition in an open world.

Aligned Contrastive Loss for Long-Tailed Recognition Large-scale long-tailed recognition in an open world

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This paper cites Long-tail learning via logit adjustment.

Aligned Contrastive Loss for Long-Tailed Recognition Long-tail learning via logit adjustment

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This paper cites Decoupled Training for Long-Tailed Classification With Stochastic Representations.

Aligned Contrastive Loss for Long-Tailed Recognition Decoupled Training for Long-Tailed Classification With Stochastic Representations

Reference 30

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This paper cites Representation Learning with Contrastive Predictive Coding.

Aligned Contrastive Loss for Long-Tailed Recognition Representation Learning with Contrastive Predictive Coding

Reference 31

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This paper cites Dynamic sampling in convolutional neural networks for imbalanced data classification.

Aligned Contrastive Loss for Long-Tailed Recognition Dynamic sampling in convolutional neural networks for imbalanced data classification

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This paper cites Balanced meta-softmax for long-tailed visual recog- nition.Advances in neural information processing systems, 33:4175–4186, 2020.

Aligned Contrastive Loss for Long-Tailed Recognition Balanced meta-softmax for long-tailed visual recog- nition.Advances in neural information processing systems, 33:4175–4186, 2020

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.997235Z

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This paper cites Relay back- propagation for effective learning of deep convolutional neu- ral networks.

Aligned Contrastive Loss for Long-Tailed Recognition Relay back- propagation for effective learning of deep convolutional neu- ral networks

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This paper cites Meta-weight-net: Learning an explicit mapping for sample weighting.Advances in neu- ral information processing systems, 32, 2019.

Aligned Contrastive Loss for Long-Tailed Recognition Meta-weight-net: Learning an explicit mapping for sample weighting.Advances in neu- ral information processing systems, 32, 2019

Reference 35

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This paper cites Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels.

Aligned Contrastive Loss for Long-Tailed Recognition Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels

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This paper cites Long- tailed classification by keeping the good and removing the bad momentum causal effect.Advances in Neural Informa- tion Processing Systems, 33:1513–1524, 2020.

Aligned Contrastive Loss for Long-Tailed Recognition Long- tailed classification by keeping the good and removing the bad momentum causal effect.Advances in Neural Informa- tion Processing Systems, 33:1513–1524, 2020

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.958277Z

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This paper cites The inaturalist species classification and de- tection dataset.

Aligned Contrastive Loss for Long-Tailed Recognition The inaturalist species classification and de- tection dataset

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This paper cites Contrastive learning based hybrid networks for long- tailed image classification.

Aligned Contrastive Loss for Long-Tailed Recognition Contrastive learning based hybrid networks for long- tailed image classification

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.936048Z

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This paper cites Learn- ing to model the tail.Advances in neural information pro- cessing systems, 30, 2017.

Aligned Contrastive Loss for Long-Tailed Recognition Learn- ing to model the tail.Advances in neural information pro- cessing systems, 30, 2017

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.922685Z

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This paper cites Aggregated residual transformations for deep neural networks.

Aligned Contrastive Loss for Long-Tailed Recognition Aggregated residual transformations for deep neural networks

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This paper cites Decoupled contrastive learning for long-tailed recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Decoupled contrastive learning for long-tailed recognition

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Aligned Contrastive Loss for Long-Tailed Recognition Unresolved cited work

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Observation cd4b1677-1134-44b7-8ccd-124a3759de5d · outbound

This paper cites Fairness-aware contrastive learning with partially annotated sensitive attributes.

Aligned Contrastive Loss for Long-Tailed Recognition Fairness-aware contrastive learning with partially annotated sensitive attributes

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Observation 1946d27f-4bce-4f38-a835-ff9ab197ff9e · outbound

This paper cites Distribution alignment: A unified frame- work for long-tail visual recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Distribution alignment: A unified frame- work for long-tail visual recognition

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Observation 34a46ce7-e106-4797-8983-b6bdaec7cd8b · outbound

This paper cites Deep long-tailed learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(9):10795–10816, 2023.

Aligned Contrastive Loss for Long-Tailed Recognition Deep long-tailed learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(9):10795–10816, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.845757Z

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Observation 09edfe46-7db3-43de-af05-ecc846b0d4a8 · outbound

This paper cites Im- proving calibration for long-tailed recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Im- proving calibration for long-tailed recognition

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.831697Z

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This paper cites Places: A 10 million image database for scene recognition.IEEE transactions on pattern analysis and machine intelligence, 40(6):1452–1464, 2017.

Aligned Contrastive Loss for Long-Tailed Recognition Places: A 10 million image database for scene recognition.IEEE transactions on pattern analysis and machine intelligence, 40(6):1452–1464, 2017

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Observation 1bd47a6a-37eb-47bf-853d-4953e09f5909 · outbound

This paper cites Bbn: Bilateral-branch network with cumulative learn- ing for long-tailed visual recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Bbn: Bilateral-branch network with cumulative learn- ing for long-tailed visual recognition

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.809154Z

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Observation 72cff29e-a661-4bf1-a323-c1881a6c0f5b · outbound

This paper cites Generalized logit adjustment: Calibrating fine-tuned models by removing label bias in foundation models.Advances in Neural Information Processing Systems, 36, 2024.

Aligned Contrastive Loss for Long-Tailed Recognition Generalized logit adjustment: Calibrating fine-tuned models by removing label bias in foundation models.Advances in Neural Information Processing Systems, 36, 2024

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.795710Z

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Observation 94ef28f9-20bd-4f97-b18e-1fc282f55db6 · outbound

This paper cites Balanced contrastive learn- ing for long-tailed visual recognition.

Aligned Contrastive Loss for Long-Tailed Recognition Balanced contrastive learn- ing for long-tailed visual recognition

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:57:32.782554Z

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