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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.
Privilege-induced style drift can undermine reasoning model performance, but RLCSD effectively redirects the learning signal to focus on what truly matters鈥攖ask-relevant tokens.
VLMs struggle to spot even simple CSS changes in web interfaces, achieving only 40% accuracy on a new benchmark, DiffSpot, suggesting a surprising lack of fine-grained visual understanding.
