Practices for Governing Agentic AI Systems

A crucial area of interest is generating images from text, particularly focusing on preserving human identity accurately. This task demands high detail and fidelity, especially when dealing with human faces involving complex and nuanced semantics. While existing models adeptly handle general styles and objects, they often need to improve when producing images that maintain the…

Mobile device agents utilizing Multimodal Large Language Models (MLLM) have gained popularity due to the rapid advancements in MLLMs, showcasing notable visual comprehension capabilities. This progress has made MLLM-based agents viable for diverse applications. The emergence of mobile device agents represents a novel application, requiring these agents to operate devices based on screen content and…

The evolution of language models is a critical component in the dynamic field of natural language processing. These models, essential for emulating human-like text comprehension and generation, are instrumental in various applications, from translation to conversational interfaces. The core challenge tackled in this area is refining model efficiency, particularly in managing lengthy data sequences. Traditional…

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Mathematical reasoning, part of our advanced thinking, reveals the complexities of human intelligence. It involves logical thinking and specialized knowledge, not just in words but also in pictures, crucial for understanding abilities. This has practical uses in AI. However, current AI datasets often focus narrowly, missing a full exploration of combining visual language understanding with…