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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.
