Neural network based methods have obtained great progress on a variety of natural language
processing tasks. However, in most previous works, the models are learned based on …

This article surveys and organizes research works in a new paradigm in natural language
processing, which we dub “prompt-based learning.” Unlike traditional supervised learning, …

Li‐rich cathode materials have attracted increasing attention because of their high reversible
discharge capacity (>250 mA hg −1 ), which originates from transition metal (TM) ion redox …

A wide variety of NLP applications, such as machine translation, summarization, and dialog,
involve text generation. One major challenge for these applications is how to evaluate …

Complex genomic rearrangements (CGRs) consisting of two or more breakpoint junctions
have been observed in genomic disorders. Recently, a chromosome catastrophe …

Background The novel human coronavirus disease 2019 (COVID-19) pandemic has
claimed more than 600,000 lives worldwide, causing tremendous public health, social, and …

This paper creates a paradigm shift with regard to the way we build neural extractive
summarization systems. Instead of following the commonly used framework of extracting sentences …

Large language models (LLMs) have demonstrated an impressive ability to perform arithmetic
and symbolic reasoning tasks, when provided with a few examples at test time (" few-shot …

Earth-abundant first-row (3d) transition metal–based catalysts have been developed for the
oxygen-evolution reaction (OER); however, they operate at overpotentials substantially …

Large language models are trained in two stages:(1) unsupervised pretraining from raw text,
to learn general-purpose representations, and (2) large scale instruction tuning and …