The human ability to learn, generalize, and control complex manipulation tasks through multi-
modality feedback suggests a unique capability, which we refer to as dexterity intelligence …

Large language models excel at a wide range of complex tasks. However, enabling general
inference in the real world, eg, for robotics problems, raises the challenge of grounding. We …

Large Language Models (LLMs) are a type of artificial intelligence that uses information from
very large datasets to model the use of language and generate content. While LLMs like …

Diffusion models have gained increasing attention for their impressive generation abilities
but currently struggle with rendering accurate and coherent text. To address this issue, we …

Unconstrained handwritten text recognition is a challenging computer vision task. It is
traditionally handled by a two-step approach, combining line segmentation followed by text …

In this study, we are interested in imbuing robots with the capability of physically-grounded
task planning. Recent advancements have shown that large language models (LLMs) …

This paper presents a comprehensive evaluation of the Optical Character Recognition
(OCR) capabilities of the recently released GPT-4V (ision), a Large Multimodal Model …

Abstract Chain-of-Thought (CoT) guides large language models (LLMs) to reason step-by-
step and can motivate their logical reasoning ability. While effective for logical tasks CoT is …

Existing full text datasets of US public domain newspapers do not recognize the often
complex layouts of newspaper scans, and as a result the digitized content scrambles texts …

With the rapid development of IT operations, it has become increasingly crucial to efficiently
manage and analyze large volumes of data for practical applications. The techniques of …