activity
20162021
most citedAchieving Forgetting Prevention and Knowledge Transfer in Continual Learning

44 citations · 64 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CL2021

Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks

Zixuan Ke, Hu Xu, Bing Liu

This paper studies continual learning (CL) of a sequence of aspect sentiment classification (ASC) tasks. Although some CL techniques have been proposed for document sentiment class…

cs.CL2021

CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks

Zixuan Ke, Bing Liu, Hu Xu +1

This paper studies continual learning (CL) of a sequence of aspect sentiment classification(ASC) tasks in a particular CL setting called domain incremental learning (DIL). Each tas…

cs.CL2021★ 44 cited

Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning

Zixuan Ke, Bing Liu, Nianzu Ma +2

Continual learning (CL) learns a sequence of tasks incrementally with the goal of achieving two main objectives: overcoming catastrophic forgetting (CF) and encouraging knowledge t…

cs.CL2020★ 7 cited

Understanding Pre-trained BERT for Aspect-based Sentiment Analysis

Hu Xu, Lei Shu, Philip S. Yu +1

This paper analyzes the pre-trained hidden representations learned from reviews on BERT for tasks in aspect-based sentiment analysis (ABSA). Our work is motivated by the recent pro…

cs.CL2020

NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions

Zhiyu Chen, Honglei Liu, Hu Xu +3

Existing conversational systems are mostly agent-centric, which assumes the user utterances would closely follow the system ontology (for NLU or dialogue state tracking). However,…

cs.CL2020

Controllable Text Generation with Focused Variation

Lei Shu, Alexandros Papangelis, Yi-Chia Wang +5

This work introduces Focused-Variation Network (FVN), a novel model to control language generation. The main problems in previous controlled language generation models range from t…

cs.CL2019★ 7 cited

A Failure of Aspect Sentiment Classifiers and an Adaptive Re-weighting Solution

Hu Xu, Bing Liu, Lei Shu +1

Aspect-based sentiment classification (ASC) is an important task in fine-grained sentiment analysis.~Deep supervised ASC approaches typically model this task as a pair-wise classif…

cs.CL2019

Modeling Multi-Action Policy for Task-Oriented Dialogues

Lei Shu, Hu Xu, Bing Liu +1

Dialogue management (DM) plays a key role in the quality of the interaction with the user in a task-oriented dialogue system. In most existing approaches, the agent predicts only o…

cs.CL2019

Flexibly-Structured Model for Task-Oriented Dialogues

Lei Shu, Piero Molino, Mahdi Namazifar +4

This paper proposes a novel end-to-end architecture for task-oriented dialogue systems. It is based on a simple and practical yet very effective sequence-to-sequence approach, wher…

cs.CL2016★ 6 cited

Supervised Opinion Aspect Extraction by Exploiting Past Extraction Results

Lei Shu, Bing Liu, Hu Xu +1

One of the key tasks of sentiment analysis of product reviews is to extract product aspects or features that users have expressed opinions on. In this work, we focus on using super…