The demand for automated customer support approaches in customer-centric environments
has increased significantly in the past few years. Natural Language Processing (NLP) …

Abstract Machine translation is an important and challenging task that aims at automatically
translating natural language sentences from one language into another. Recently …

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis
(ABSA), aiming to analyze and understand people's opinions at the aspect level, has been …

Despite the success, the process of fine-tuning large-scale PLMs brings prohibitive
adaptation costs. In fact, fine-tuning all the parameters of a colossal model and retaining …

Activity and property prediction models are the central workhorses in drug discovery and
materials sciences, but currently, they have to be trained or fine-tuned for new tasks. Without …

Pretrained language models have served as important backbones for natural language
processing. Recently, in-domain pretraining has been shown to benefit various domain …

Generative methods greatly promote aspect-based sentiment analysis via generating a
sequence of sentiment elements in a specified format. However, existing studies usually …

Most downstream adaptation methods tune all or part of the parameters of pre-trained
models (PTMs) through gradient descent, where the tuning cost increases linearly with the …

Neural Code Intelligence--leveraging deep learning to understand, generate, and optimize
code--holds immense potential for transformative impacts on the whole society. Bridging the …

This case study investigates the task of job classification in a real-world setting, where the
goal is to determine whether an English-language is appropriate for a graduate or entry …