Samuel Webster

Models using classical dimensionality reduction for saliency acquisition can outperform state-of-the-art methods without any human input or domain expertise.

LLMs' attention patterns subtly shift with emotional tone, and explicitly accounting for these shifts during training improves reading comprehension even on neutral datasets.