labeled data

AutoAL: Automated Active Learning with Differentiable Query Strategy Search ICML 2025 STAR: Self-Automated Back-Querying for Production Data Generation IJCNLP 2025 Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift ICML 2025 VietASR: Achieving Industry-level Vietnamese ASR with 50-hour labeled data and Large-Scale Speech Pretraining Interspeech 2025 A Survey of Data-Efficient Graph Learning IJCAI 2024 Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning NeurIPS 2024 Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data EMNLP 2023 Can semi-supervised learning use all the data effectively? A lower bound perspective NeurIPS 2023 Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models EMNLP 2023 A Few More Examples May Be Worth Billions of Parameters EMNLP 2022 Can Yes-No Question-Answering Models be Useful for Few-Shot Metaphor Detection? EMNLP 2022 Minimal Supervision for Morphological Inflection EMNLP 2021 Do Not Have Enough Data? Deep Learning to the Rescue! AAAI 2020 Reactive Supervision: A New Method for Collecting Sarcasm Data EMNLP 2020 Commonsense about Human Senses: Labeled Data Collection Processes EMNLP 2019 Multi-task Learning with Labeled and Unlabeled Tasks ICML 2017 Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing JMLR 2016 The Value of Labeled and Unlabeled Examples when the Model is Imperfect NeurIPS 2007