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Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems., , , , , , , , , and 31 other author(s). KDD, page 2893-2902. ACM, (2022)AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model., , , , , , , , , and 6 other author(s). CoRR, (2022)Recipes for Sequential Pre-training of Multilingual Encoder and Seq2Seq Models., , , , , and . ACL (Findings), page 9380-9394. Association for Computational Linguistics, (2023)LINGUIST: Language Model Instruction Tuning to Generate Annotated Utterances for Intent Classification and Slot Tagging., , , , and . COLING, page 218-241. International Committee on Computational Linguistics, (2022)Sampling bias in NLU models: Impact and Mitigation., , , , , and . INTERSPEECH, page 755-759. ISCA, (2023)GeMQuAD : Generating Multilingual Question Answering Datasets from Large Language Models using Few Shot Learning., , , and . CoRR, (2024)CLASP: Few-Shot Cross-Lingual Data Augmentation for Semantic Parsing., , , , , and . AACL/IJCNLP (2), page 444-462. Association for Computational Linguistics, (2022)Weakly Supervised Data Augmentation Through Prompting for Dialogue Understanding., , , , , , , and . CoRR, (2022)PLACES: Prompting Language Models for Social Conversation Synthesis., , , , , , , and . EACL (Findings), page 814-838. Association for Computational Linguistics, (2023)