Graph Convolutional Networks (GCNs) and their variants have experienced significant
attention and have become the de facto methods for learning graph representations. GCNs …

China is the world’s most populous country and a major emitter of greenhouse gases.
Consequently, much research has focused on China’s influence on climate change but somewhat …

This paper is a study of fine-tuning of BERT contextual representations, with focus on
commonly observed instabilities in few-sample scenarios. We identify several factors that cause …

We propose BERTScore, an automatic evaluation metric for text generation. Analogously to
common metrics, BERTScore computes a similarity score for each token in the candidate …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

Histones are subject to a vast array of posttranslational modifications including acetylation,
methylation, phosphorylation, and ubiquitylation. The writers of these modifications play …

An extensive dataset on rice phenology in China, including 202 series broadly covering the
past three decades (1980s–2000s), was compiled. From these data, we estimated the …

Recent advances in Large Language Models (LLM) have made automatic code generation
possible for real-world programming tasks in general-purpose programming languages such …

Language models (LMs) are becoming the foundation for almost all major language
technologies, but their capabilities, limitations, and risks are not well understood. We present …

Asynchronous online discussion environments are important platforms to support learning.
Research suggests, however, threaded forums, one of the most popular asynchronous …