activity
20202022
most citedTopicRefine: Joint Topic Prediction and Dialogue Response Generation for Multi-turn End-to-End Dialogue System

7 citations · 11 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL20221 cited

DIGAT: Modeling News Recommendation with Dual-Graph Interaction

Zhiming Mao, Jian Li, Hongru Wang +2

News recommendation (NR) is essential for online news services. Existing NR methods typically adopt a news-user representation learning framework, facing two potential limitations.…

cs.CL20211 cited

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…

cs.LG20211 cited

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…

cs.CL20211 cited

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…

cs.CL20217 cited

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…

cs.CL2020

CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task Learning

Hongru Wang, Xiangru Tang, Sunny Lai +4

This paper describes our system submitted to task 4 of SemEval 2020: Commonsense Validation and Explanation (ComVE) which consists of three sub-tasks. The task is to directly valid…