Paras Chopra

The paper introduces hybrid neural world models that provide fast, multi-horizon predictions for complex physical dynamics, implicitly handling sharp events like shocks and contacts without explicit training on discontinuities.

This paper demonstrates that large language models spontaneously develop geometric structures corresponding to human perceptual domains (like color or pitch) within their internal layers, suggesting this structure is transient and emerges during the model's processing pipeline.