Researchers have developed a new method to synthesize full-cycle biventricular motion from a single end-diastolic mesh. This task is challenging due t...
Researchers have developed a system called Q-Guide for multimodal visual question answering. This system allows AI models to read and understand docum...
Researchers have proposed a new approach to improving generation in AI models called Truncate-bad, Upweight-good Policy (TUP). This method involves re...
Researchers have developed a new approach to robotic grasping called GOAG, which uses deep generative models to learn a compact representation of a gr...
A new study examines how large language models (LLMs) assign credit to individual steps in a task. The researchers found that none of the current meth...
Researchers have studied how the AdamW optimizer affects training dynamics beyond a single update cycle. They found that past gradient information sto...
Researchers have developed CoToGrasp, a new AI framework for synthesizing grasps that are conditioned on specific contact topologies. Unlike existing ...
Researchers have developed a method to use aggregate mobility statistics to inform language models used in crowd simulation. The approach involves fin...
Researchers have found a limitation in using classical world models to align agent policies with reality. They created true worlds where finite classi...
Researchers have proposed a new fine-tuning method called LoRA-GA$^2$, which aims to close the performance gap between low-rank adaptation (LoRA) and ...
Researchers have proposed a new method for assigning credits in long-horizon reinforcement learning. The approach, called MileGPO, identifies meaningf...
Researchers have developed a new type of convolutional kernel called Core-KAN that can adapt to varying scales and structures in images. Unlike tradit...