9 citations · 25 across the 10 of their papers we have counts for
6 papers · 1 filter
MEMD-ABSA: A Multi-Element Multi-Domain Dataset for Aspect-Based Sentiment Analysis
Hongjie Cai, Nan Song, Zengzhi Wang +7
Aspect-based sentiment analysis is a long-standing research interest in the field of opinion mining, and in recent years, researchers have gradually shifted their focus from simple…
BootAug: Boosting Text Augmentation via Hybrid Instance Filtering Framework
Heng Yang, Ke Li
Text augmentation is an effective technique for addressing the problem of insufficient data in natural language processing. However, existing text augmentation methods tend to focu…
PyABSA: A Modularized Framework for Reproducible Aspect-based Sentiment Analysis
Heng Yang, Chen Zhang, Ke Li
The advancement of aspect-based sentiment analysis (ABSA) has urged the lack of a user-friendly framework that can largely lower the difficulty of reproducing state-of-the-art ABSA…
LSA: Modeling Aspect Sentiment Coherency via Local Sentiment Aggregation
Heng Yang, Ke Li
Aspect sentiment coherency is an intriguing yet underexplored topic in the field of aspect-based sentiment classification. This concept reflects the common pattern where adjacent a…
Efficient MDI Adaptation for n-gram Language Models
Ruizhe Huang, Ke Li, Ashish Arora +2
This paper presents an efficient algorithm for n-gram language model adaptation under the minimum discrimination information (MDI) principle, where an out-of-domain language model…
Speaker Adaptation for End-to-End CTC Models
Ke Li, Jinyu Li, Yong Zhao +2
We propose two approaches for speaker adaptation in end-to-end (E2E) automatic speech recognition systems. One is Kullback-Leibler divergence (KLD) regularization and the other is…