3 accepted papers
While scaling training compute has led to remarkable improvements in large language models (LLMs), scaling inference compute only recently began to yield analogous gains. We hypothesize that a core missing component is a lack of diverse LLM outputs, leading to inefficient search due to models repeat…
Existing GAN-based approaches to caricature generation mainly focus on exaggerating a character’s global facial structure. This often leads to the failure in highlighting significant facial features such as big eyes and hook nose. To address this limitation, we propose a new approach termed as G2L-C…
Deformable object manipulation has been considered a challenging task for robots for its complex dynamics and the infinite dimensional configuration space. Fabric unfolding manipulation takes on critical significance in the textile industry and household services. Accordingly, enabling robots to pos