activity
20192023
most citedAnswering Complex Questions by Joining Multi-Document Evidence with Quasi Knowledge Graphs

43 citations · 61 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2023

IntentDial: An Intent Graph based Multi-Turn Dialogue System with Reasoning Path Visualization

Zengguang Hao, Jie Zhang, Binxia Xu +3

Intent detection and identification from multi-turn dialogue has become a widely explored technique in conversational agents, for example, voice assistants and intelligent customer…

cs.CL2021★ 11 cited

R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling

Xiang Hu, Haitao Mi, Zujie Wen +4

Human language understanding operates at multiple levels of granularity (e.g., words, phrases, and sentences) with increasing levels of abstraction that can be hierarchically combi…

cs.CL2020

Interactive Question Clarification in Dialogue via Reinforcement Learning

Xiang Hu, Zujie Wen, Yafang Wang +2

Coping with ambiguous questions has been a perennial problem in real-world dialogue systems. Although clarification by asking questions is a common form of human interaction, it is…

cs.CL2020★ 6 cited

DAN: Dual-View Representation Learning for Adapting Stance Classifiers to New Domains

Chang Xu, Cecile Paris, Surya Nepal +3

We address the issue of having a limited number of annotations for stance classification in a new domain, by adapting out-of-domain classifiers with domain adaptation. Existing app…

cs.CV2020

Long Short-Term Sample Distillation

Liang Jiang, Zujie Wen, Zhongping Liang +7

In the past decade, there has been substantial progress at training increasingly deep neural networks. Recent advances within the teacher--student training paradigm have establishe…

cs.LG2019★ 1 cited

Which Channel to Ask My Question? Personalized Customer Service Request Stream Routing using Deep Reinforcement Learning

Zining Liu, Chong Long, Xiaolu Lu +3

Customer services are critical to all companies, as they may directly connect to the brand reputation. Due to a great number of customers, e-commerce companies often employ multipl…

cs.IR2019★ 43 cited

Answering Complex Questions by Joining Multi-Document Evidence with Quasi Knowledge Graphs

Xiaolu Lu, Soumajit Pramanik, Rishiraj Saha Roy +3

Direct answering of questions that involve multiple entities and relations is a challenge for text-based QA. This problem is most pronounced when answers can be found only by joini…