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OpenEnded, a corpus of English practice speech from Mandarin speakers in open-response tasks, is introduced and it is shown that ALM-generated pseudo-labels improve training over original ALM scoring, while VoxPA achieves the best performance among all baselines.
Hidden Decoding achieves unprecedented performance improvements in large language models by scaling computation along the sequence length without modifying the Transformer architecture.
By rebalancing proposal distributions, this method sets a new benchmark in few-shot object detection, achieving significant performance gains without added latency.
