Conversational multi-doc question answering aims to answer specific questions based on the retrieved documents as well as the contextual conversations.
We introduce UFO, an innovative UI-Focused agent to fulfill user requests tailored to applications on Windows OS, harnessing the capabilities of GPT-Vision.
On segment anything task such as zero-shot instance segmentation, our EfficientSAMs with SAMI-pretrained lightweight image encoders perform favorably with a significant gain (e. g., ~4 AP on COCO/LVIS) over other fast SAM models.
Ranked #3 on Zero-Shot Instance Segmentation on LVIS v1.0 val
In visual speech processing, context modeling capability is one of the most important requirements due to the ambiguous nature of lip movements.
Experimentally, we test our Score Entropy Discrete Diffusion models (SEDD) on standard language modeling tasks.
Either they are too slow for meaningful research to be performed without enormous computational resources, like Crafter, NetHack and Minecraft, or they are not complex enough to pose a significant challenge, like Minigrid and Procgen.