Ising machines are hardware solvers that aim to find the absolute or approximate ground
states of the Ising model. The Ising model is of fundamental computational interest because …

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 …

We introduce EgoSchema, a very long-form video question-answering dataset, and
benchmark to evaluate long video understanding capabilities of modern vision and …

Recent studies have discovered that Chain-of-Thought prompting (CoT) can dramatically
improve the performance of Large Language Models (LLMs), particularly when dealing with …

Lithium-ion batteries are used in a wide range of applications including energy storage
systems, electric transportations, and portable electronic devices. Accurately obtaining the …

Algorithmic reasoning requires capabilities which are most naturally understood through
recurrent models of computation, like the Turing machine. However, Transformer models …

Quantum random sampling is the leading proposal for demonstrating a computational
advantage of quantum computers over classical computers. Recently the first large-scale …

Abstract Model complexity is a fundamental problem in deep learning. In this paper, we
conduct a systematic overview of the latest studies on model complexity in deep learning …

Scientists have grappled with reconciling biological evolution 1, 2 with the immutable laws of
the Universe defined by physics. These laws underpin life's origin, evolution and the …

On-chip spectrometers with compact footprints are being extensively investigated owing to
their promising future in critical applications such as sensing, surveillance and spectral …