Adequate knowledge of climatic change over the Tibetan Plateau (TP) with an average elevation
of more than 4000 m above sea level (asl) has been insufficient for a long time owing to …

The learning rate warmup heuristic achieves remarkable success in stabilizing training,
accelerating convergence and improving generalization for adaptive stochastic optimization …

Pretraining large neural language models, such as BERT, has led to impressive gains on
many natural language processing (NLP) tasks. However, most pretraining efforts focus on …

The spatial and temporal distribution of summer monsoon precipitation (or effective moisture)
during the Holocene has been reconstructed on the basis of geological data, including …

In the past few years, the development of sequencespecific DNA nucleases has progressed
rapidly and such nucleases have shown their power in generating efficient targeted …

Recent progress in pre-trained neural language models has significantly improved the
performance of many natural language processing (NLP) tasks. In this paper we propose a new …

This paper presents a new Unified pre-trained Language Model (UniLM) that can be fine-tuned
for both natural language understanding and generation tasks. The model is pre-trained …

In this paper, we present a Multi-Task Deep Neural Network (MT-DNN) for learning
representations across multiple natural language understanding (NLU) tasks. MT-DNN not only …

Two atmospheric circulation systems, the mid-latitude Westerlies and the Asian summer
monsoon (ASM), play key roles in northern-hemisphere climatic changes. However, the …

The CRISPR (clustered regularly interspaced short palindromic repeat)/Cas (CRISPR-associated)
system has emerged as a powerful tool for targeted gene editing in many organisms, …