Multi-modal Learning
Learning generalist agents, able to solve multitudes of tasks in different domains is a long-standing problem. Reinforcement learning …
The ability to predict outcomes of interactions between embodied agents and objects is paramount in the robotic setting. While …
We introduce Visual Caption Restoration (VCR), a novel vision-language task that challenges models to accurately restore partially …
The ability of large language models (LLMs) to mimic human-like intelligence has led to a surge in LLM-based autonomous agents. Though …
Learning generalist embodied agents, able to solve multitudes of tasks in different domains is a long-standing problem. Reinforcement …
One of the challenges in robotics is to enable robotic units with the reasoning capability that would be robust enough to execute …
Scalable Vector Graphics (SVGs) have become integral in modern image rendering and graphic design applications due to their infinite …
Text-conditioned image generation models have recently shown immense qualitative success using denoising diffusion processes. However, …
Large pre-trained models have proved to be remarkable zero- and (prompt-based) few-shot learners in unimodal vision and language tasks. …
The generative modeling landscape has experienced tremendous growth in recent years, particularly in generating natural images and art. …