The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …

Large language models (LLMs) have demonstrated impressive capabilities, but the bar for
clinical applications is high. Attempts to assess the clinical knowledge of models typically …

Reasoning, as an essential ability for complex problem-solving, can provide back-end
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …

Guided image synthesis enables everyday users to create and edit photo-realistic images
with minimum effort. The key challenge is balancing faithfulness to the user input (eg, hand …

We show that diffusion models can achieve image sample quality superior to the current
state-of-the-art generative models. We achieve this on unconditional image synthesis by …

The performance of Large Language Models (LLMs) in reasoning tasks depends heavily on
prompt design, with Chain-of-Thought (CoT) and self-consistency being critical methods that …

A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Microgrids have recently emerged as a building block for smart grids combining distributed
renewable energy sources (RESs), energy storage devices, and load management …