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Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation.

, , , , , , , and . CoRR, (2024)

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Input Length Matters: An Empirical Study Of RNN-T And MWER Training For Long-form Telephony Speech Recognition., , , , , , and . CoRR, (2021)A Large Scale Speech Sentiment Corpus., , , , , and . LREC, page 6549-6555. European Language Resources Association, (2020)Improving the Fusion of Acoustic and Text Representations in RNN-T., , , , and . ICASSP, page 8117-8121. IEEE, (2022)Exploring Targeted Universal Adversarial Perturbations to End-to-End ASR Models., , , and . Interspeech, page 3460-3464. ISCA, (2021)Instruction-Following Speech Recognition., , , and . CoRR, (2023)Hyper-parameter Tuning under a Budget Constraint., , and . CoRR, (2019)Hyper-parameter Tuning under a Budget Constraint., , , and . IJCAI, page 5744-5750. ijcai.org, (2019)Kernel Approximation Methods for Speech Recognition., , , , , , , , , and 2 other author(s). J. Mach. Learn. Res., (2019)Improving Streaming Automatic Speech Recognition With Non-Streaming Model Distillation On Unsupervised Data., , , , , , , , , and . CoRR, (2020)Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness., , , , , , , and . CoRR, (2023)