activity
20192022
most citedLogician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction

10 citations · 13 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20222 cited

Learning to Execute Actions or Ask Clarification Questions

Zhengxiang Shi, Yue Feng, Aldo Lipani

Collaborative tasks are ubiquitous activities where a form of communication is required in order to reach a joint goal. Collaborative building is one of such tasks. We wish to deve…

cs.CL20221 cited

Dynamic Schema Graph Fusion Network for Multi-Domain Dialogue State Tracking

Yue Feng, Aldo Lipani, Fanghua Ye +2

Dialogue State Tracking (DST) aims to keep track of users' intentions during the course of a conversation. In DST, modelling the relations among domains and slots is still an under…

cs.CL2022

ASSIST: Towards Label Noise-Robust Dialogue State Tracking

Fanghua Ye, Yue Feng, Emine Yilmaz

The MultiWOZ 2.0 dataset has greatly boosted the research on dialogue state tracking (DST). However, substantial noise has been discovered in its state annotations. Such noise brin…

cs.CL2020

A Sequence-to-Sequence Approach to Dialogue State Tracking

Yue Feng, Yang Wang, Hang Li

This paper is concerned with dialogue state tracking (DST) in a task-oriented dialogue system. Building a DST module that is highly effective is still a challenging issue, although…

cs.CL201910 cited

Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction

Mingming Sun, Xu Li, Xin Wang +3

In this paper, we consider the problem of open information extraction (OIE) for extracting entity and relation level intermediate structures from sentences in open-domain. We focus…