Natural language processing (NLP) continues to evolve with new methods like in-context learning (ICL), which offers innovative ways to enhance large language models (LLMs). ICL involves conditioning ...

In the rapidly evolving field of household robotics, a significant challenge has emerged in executing personalized organizational tasks, such as arranging groceries in a refrigerator. These tasks ...

The routing mechanism of MoE models evokes a great privacy challenge. Optimize LLM large language model performance by selectively activating only a fraction of its total parameters while making it ...

High-performance computing has become crucial for various businesses, including scientific research and Artificial Intelligence (AI), in today's data-driven society. By providing strong, scalable, and ...

AI's rapid rise has been driven by powerful language models, transforming industries from customer service to content creation. However, many languages, particularly those from ...

In the world of information retrieval, one of the most challenging tasks is to create a system that can seamlessly understand and retrieve relevant content across different formats, such as text and ...

AI has made significant strides in developing large language models (LLMs) that excel in complex tasks such as text generation, summarization, and conversational AI. Models like LaPM 540B and ...

AI's rapid rise has been driven by powerful language models, transforming industries from customer service to content creation. However, many languages, particularly those from ...

AI's rapid rise has been driven by powerful language models, transforming industries from customer service to content creation. However, many languages, particularly those from ...

Automatic differentiation has transformed the development of machine learning models by eliminating complex, application-dependent gradient derivations. This transformation helps to calculate Jacobian ...

Foundation models show impressive capabilities across tasks and modalities, outperforming traditional AI approaches often task-specific and limited by modality. In medicine, however, developing such ...