59 citations · 241 across the 30 of their papers we have counts for
11 papers · 1 filter
Integrating Pretrained Language Model for Dialogue Policy Learning
Hongru Wang, Huimin Wang, Zezhong Wang +1
Reinforcement Learning (RL) has been witnessed its potential for training a dialogue policy agent towards maximizing the accumulated rewards given from users. However, the reward c…
Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning
Hongru Wang, Zhijing Jin, Jiarun Cao +2
Standard few-shot relation classification (RC) is designed to learn a robust classifier with only few labeled data for each class. However, previous works rarely investigate the ef…
RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Models
Lingzhi Wang, Huang Hu, Lei Sha +3
Conversational Recommender System (CRS), which aims to recommend high-quality items to users through interactive conversations, has gained great research interest recently. A CRS i…
Neural News Recommendation with Collaborative News Encoding and Structural User Encoding
Zhiming Mao, Xingshan Zeng, Kam-Fai Wong
Automatic news recommendation has gained much attention from the academic community and industry. Recent studies reveal that the key to this task lies within the effective represen…
Prior Omission of Dissimilar Source Domain(s) for Cost-Effective Few-Shot Learning
Zezhong Wang, Hongru Wang, Kwan Wai Chung +3
Few-shot slot tagging is an emerging research topic in the field of Natural Language Understanding (NLU). With sufficient annotated data from source domains, the key challenge is h…
TopicRefine: Joint Topic Prediction and Dialogue Response Generation for Multi-turn End-to-End Dialogue System
Hongru Wang, Mingyu Cui, Zimo Zhou +2
A multi-turn dialogue always follows a specific topic thread, and topic shift at the discourse level occurs naturally as the conversation progresses, necessitating the model's abil…
Re-entry Prediction for Online Conversations via Self-Supervised Learning
Lingzhi Wang, Xingshan Zeng, Huang Hu +2
In recent years, world business in online discussions and opinion sharing on social media is booming. Re-entry prediction task is thus proposed to help people keep track of the dis…
MCML: A Novel Memory-based Contrastive Meta-Learning Method for Few Shot Slot Tagging
Hongru Wang, Zezhong Wang, Wai Chung Kwan +1
Meta-learning is widely used for few-shot slot tagging in task of few-shot learning. The performance of existing methods is, however, seriously affected by \textit{sample forgettin…
Successful New-entry Prediction for Multi-Party Online Conversations via Latent Topics and Discourse Modeling
Lingzhi Wang, Jing Li, Xingshan Zeng +1
With the increasing popularity of social media, online interpersonal communication now plays an essential role in people's everyday information exchange. Whether and how a newcomer…
Continuity of Topic, Interaction, and Query: Learning to Quote in Online Conversations
Lingzhi Wang, Jing Li, Xingshan Zeng +2
Quotations are crucial for successful explanations and persuasions in interpersonal communications. However, finding what to quote in a conversation is challenging for both humans…
Quotation Recommendation and Interpretation Based on Transformation from Queries to Quotations
Lingzhi Wang, Xingshan Zeng, Kam-Fai Wong
To help individuals express themselves better, quotation recommendation is receiving growing attention. Nevertheless, most prior efforts focus on modeling quotations and queries se…