23 citations · 59 across the 13 of their papers we have counts for
14 papers
A Large Language Model Enhanced Conversational Recommender System
Yue Feng, Shuchang Liu, Zhenghai Xue +5
Conversational recommender systems (CRSs) aim to recommend high-quality items to users through a dialogue interface. It usually contains multiple sub-tasks, such as user preference…
Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue System
Zhiyuan Hu, Yue Feng, Anh Tuan Luu +2
Dialogue systems and large language models (LLMs) have gained considerable attention. However, the direct utilization of LLMs as task-oriented dialogue (TOD) models has been found…
PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation
Zhiyuan Hu, Chumin Liu, Yue Feng +2
Controllable text generation is a challenging and meaningful field in natural language generation (NLG). Especially, poetry generation is a typical one with well-defined and strict…
Schema-Guided User Satisfaction Modeling for Task-Oriented Dialogues
Yue Feng, Yunlong Jiao, Animesh Prasad +3
User Satisfaction Modeling (USM) is one of the popular choices for task-oriented dialogue systems evaluation, where user satisfaction typically depends on whether the user's task g…
A Survey on Asking Clarification Questions Datasets in Conversational Systems
Hossein A. Rahmani, Xi Wang, Yue Feng +3
The ability to understand a user's underlying needs is critical for conversational systems, especially with limited input from users in a conversation. Thus, in such a domain, Aski…
Towards Asking Clarification Questions for Information Seeking on Task-Oriented Dialogues
Yue Feng, Hossein A. Rahmani, Aldo Lipani +1
Task-oriented dialogue systems aim at providing users with task-specific services. Users of such systems often do not know all the information about the task they are trying to acc…
A Graph-Guided Reasoning Approach for Open-ended Commonsense Question Answering
Zhen Han, Yue Feng, Mingming Sun
Recently, end-to-end trained models for multiple-choice commonsense question answering (QA) have delivered promising results. However, such question-answering systems cannot be dir…
Topic-Aware Response Generation in Task-Oriented Dialogue with Unstructured Knowledge Access
Yue Feng, Gerasimos Lampouras, Ignacio Iacobacci
To alleviate the problem of structured databases' limited coverage, recent task-oriented dialogue systems incorporate external unstructured knowledge to guide the generation of sys…
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…
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…
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…
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…
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…
Temporal Identification of Latent Communities on Twitter
Hossein Fani, Fattane Zarrinkalam, Xin Zhao +3
User communities in social networks are usually identified by considering explicit structural social connections between users. While such communities can reveal important informat…