few-shot learning

Towards Few-Annotation Learning for Object Detection: Are Transformer-Based Models More Efficient? WACV 2023 Towards Informative Few-Shot Prompt with Maximum Information Gain for In-Context Learning EMNLP 2023 Towards Last-layer Retraining for Group Robustness with Fewer Annotations NeurIPS 2023 Towards LLM-driven Dialogue State Tracking EMNLP 2023 Towards Reasoning in Large Language Models: A Survey ACL 2023 Toward Understanding Generative Data Augmentation NeurIPS 2023 Train-Once-for-All Personalization CVPR 2023 Transcending Scaling Laws with 0.1% Extra Compute EMNLP 2023 Transductive Feature Space Regularization for Few-shot Bioacoustic Event Detection Interspeech 2023 Transductive Few-Shot Learning With Prototype-Based Label Propagation by Iterative Graph Refinement CVPR 2023 Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models EMNLP 2023 Transfer-Free Data-Efficient Multilingual Slot Labeling EMNLP 2023 Translating a low-resource language using GPT-3 and a human-readable dictionary ACL 2023 Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning ICML 2023 Turning a CLIP Model Into a Scene Text Detector CVPR 2023 Two-Shot Video Object Segmentation CVPR 2023 Type-Aware Decomposed Framework for Few-Shot Named Entity Recognition EMNLP 2023 Understanding Demonstration-based Learning from a Causal Perspective ACL 2023 Understanding Few-Shot Learning: Measuring Task Relatedness and Adaptation Difficulty via Attributes NeurIPS 2023 Understanding In-Context Learning via Supportive Pretraining Data ACL 2023 Unifying Cross-Lingual Transfer across Scenarios of Resource Scarcity EMNLP 2023 UniSumm and SummZoo: Unified Model and Diverse Benchmark for Few-Shot Summarization ACL 2023 Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching ICLR 2023 Universal Information Extraction as Unified Semantic Matching AAAI 2023 Universal Information Extraction with Meta-Pretrained Self-Retrieval ACL 2023