7 accepted papers
Embodied agents face a fundamental limitation: once deployed in real-world environments, they cannot easily acquire new knowledge to improve task performance. In this paper, we propose Dejavu, a general post-deployment learning framework that augments a frozen Vision-Language-Action (VLA) policy wit
Enabling robots to imitate artists who observe objects in the 3D world and physically draw them in a specific style is a challenging problem. Shuimohua (Sumi-e) is a typical non-photorealistic oriental ink painting art that uses simple ink, water and brush to paint and convey poetic imagery. Althoug…
Knowledge graph question answering (KGQA) aims to answer natural language questions by reasoning across multiple triples in knowledge graphs (KGs). To enhance model interpretability, reinforcement learning based methods are introduced. However, existing methods struggle with effectively reasoning ov…
Large Language Models infuse newfound vigor into the advancement of the medical domain, yet the scarcity of data poses a significant bottleneck hindering community progress. In this paper, we release the largest ever medical Question Answering (QA) dataset with 26 Million QA pairs named Huatuo-26M.…
Creating visually pleasing stylized ink paintings from 3D models is a challenge in robotic manipulation. We propose a semi-automatic framework that can extract expressive strokes from 3D models and draw them in oriental ink painting styles by using a robotic arm. The framework consists of a simulati
This work aims to transfer a Generative Adversarial Network (GAN) pre-trained on one image domain to another domain referred to as few as just one reference image. The challenge is that, under limited supervision, it is extremely difficult to synthesize photo realistic and highly diverse images whil…
Adaptive gradient methods have achieved remarkable success in training deep neural networks on a wide variety of tasks. However, not much is known about the mathematical and statistical properties of this family of methods. This work aims at providing a series of theoretical analyses of its statisti…