360 citations · 475 across the 11 of their papers we have counts for
20 papers
Continual Training of Language Models for Few-Shot Learning
Zixuan Ke, Haowei Lin, Yijia Shao +3
Recent work on applying large language models (LMs) achieves impressive performance in many NLP applications. Adapting or posttraining an LM using an unlabeled domain corpus can pr…
Zero-Shot Aspect-Based Sentiment Analysis
Lei Shu, Hu Xu, Bing Liu +1
Aspect-based sentiment analysis (ABSA) typically requires in-domain annotated data for supervised training/fine-tuning. It is a big challenge to scale ABSA to a large number of new…
User Memory Reasoning for Conversational Recommendation
Hu Xu, Seungwhan Moon, Honglei Liu +3
We study a conversational recommendation model which dynamically manages users' past (offline) preferences and current (online) requests through a structured and cumulative user me…
DomBERT: Domain-oriented Language Model for Aspect-based Sentiment Analysis
Hu Xu, Bing Liu, Lei Shu +1
This paper focuses on learning domain-oriented language models driven by end tasks, which aims to combine the worlds of both general-purpose language models (such as ELMo and BERT)…
Hybridization-Induced Gapped and Gapless States on the Surfaces of Magnetic Topological Insulators
Xiao-Ming Ma, Zhongjia Chen, Eike F. Schwier +25
The layered MnBi2nTe3n+1 family represents the first intrinsic antiferromagnetic topological insulator (AFM TI, protected by a combination symmetry ) ever discovered, providing an…
Controlled CNN-based Sequence Labeling for Aspect Extraction
Lei Shu, Hu Xu, Bing Liu
One key task of fine-grained sentiment analysis on reviews is to extract aspects or features that users have expressed opinions on. This paper focuses on supervised aspect extracti…