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Lossless Acceleration for Seq2seq Generation with Aggressive Decoding, , , , and . arXiv preprint arXiv:2205.10350, (2022)Gatekeeper to save COGS and improve efficiency of Text Prediction., , , , and . EMNLP (Industry Track), page 46-53. Association for Computational Linguistics, (2023)Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models., , , , , , , , , and 10 other author(s). CoRR, (2024)Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation., , , , , and . EMNLP (Findings), page 3909-3925. Association for Computational Linguistics, (2023)RTP-LX: Can LLMs Evaluate Toxicity in Multilingual Scenarios?, , , , , , , , , and 23 other author(s). CoRR, (2024)xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token., , , , , , , and . CoRR, (2024)EdgeFormer: A Parameter-Efficient Transformer for On-Device Seq2seq Generation., , and . EMNLP, page 10786-10798. Association for Computational Linguistics, (2022)In-context Autoencoder for Context Compression in a Large Language Model., , , , , and . ICLR, OpenReview.net, (2024)