activity
20192023
most citedDialogAct2Vec: Towards End-to-End Dialogue Agent by Multi-Task Representation Learning

2 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2023

Gated Mechanism Enhanced Multi-Task Learning for Dialog Routing

Ziming Huang, Zhuoxuan Jiang, Ke Wang +3

Currently, human-bot symbiosis dialog systems, e.g., pre- and after-sales in E-commerce, are ubiquitous, and the dialog routing component is essential to improve the overall effici…

cs.LG2021★ 1 cited

Multi-Domain Transformer-Based Counterfactual Augmentation for Earnings Call Analysis

Zixuan Yuan, Yada Zhu, Wei Zhang +3

Earnings call (EC), as a periodic teleconference of a publicly-traded company, has been extensively studied as an essential market indicator because of its high analytical value in…

cs.CL2021★ 2 cited

On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation

Wei Zhang, Ziming Huang, Yada Zhu +3

In the recent advances of natural language processing, the scale of the state-of-the-art models and datasets is usually extensive, which challenges the application of sample-based…

cs.CL2019★ 2 cited

DialogAct2Vec: Towards End-to-End Dialogue Agent by Multi-Task Representation Learning

Zhuoxuan Jiang, Ziming Huang, Dong Sheng Li +1

In end-to-end dialogue modeling and agent learning, it is important to (1) effectively learn knowledge from data, and (2) fully utilize heterogeneous information, e.g., dialogue ac…

cs.CL2019★ 2 cited

Towards End-to-End Learning for Efficient Dialogue Agent by Modeling Looking-ahead Ability

Zhuoxuan Jiang, Xian-Ling Mao, Ziming Huang +2

Learning an efficient manager of dialogue agent from data with little manual intervention is important, especially for goal-oriented dialogues. However, existing methods either tak…