few-shot classification

Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model ACML 2024 Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model CVPR 2024 First-order ANIL provably learns representations despite overparametrisation ICLR 2024 Frozen Feature Augmentation for Few-Shot Image Classification CVPR 2024 MCPNet: An Interpretable Classifier via Multi-Level Concept Prototypes CVPR 2024 MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation ICLR 2024 MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence ICML 2024 BYOC: Personalized Few-Shot Classification with Co-Authored Class Descriptions EMNLP 2023 CALIP: Zero-Shot Enhancement of CLIP with Parameter-Free Attention AAAI 2023 CMVAE: Causal Meta VAE for Unsupervised Meta-Learning AAAI 2023 ConEntail: An Entailment-based Framework for Universal Zero and Few Shot Classification with Supervised Contrastive Pretraining EACL 2023 Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification WACV 2023 CORL: Compositional Representation Learning for Few-Shot Classification WACV 2023 Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification NeurIPS 2023 Few-shot Classification via Ensemble Learning with Multi-Order Statistics IJCAI 2023 Geodesic Multi-Modal Mixup for Robust Fine-Tuning NeurIPS 2023 Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification CVPR 2023 Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification NeurIPS 2023 Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning ICML 2023 Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models EMNLP 2023 Uncertainty Estimation by Fisher Information-based Evidential Deep Learning ICML 2023 A Closer Look at Embedding Propagation for Manifold Smoothing JMLR 2022 Adaptive Poincaré Point to Set Distance for Few-Shot Classification AAAI 2022 An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning NeurIPS 2022 Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification NAACL 2022