activity
20182023
most citedAdvances and Challenges in Conversational Recommender Systems: A Survey

343 citations · 1.7k across the 34 of their papers we have counts for

collaborators

35 papers

cs.IR2023

Vague Preference Policy Learning for Conversational Recommendation

Gangyi Zhang, Chongming Gao, Wenqiang Lei +6

Conversational recommendation systems (CRS) commonly assume users have clear preferences, leading to potential over-filtering of relevant alternatives. However, users often exhibit…

cs.CL2023★ 1 cited

Knowing-how & Knowing-that: A New Task for Machine Comprehension of User Manuals

Hongru Liang, Jia Liu, Weihong Du +4

The machine reading comprehension (MRC) of user manuals has huge potential in customer service. However, current methods have trouble answering complex questions. Therefore, we int…

cs.CL2023★ 2 cited

A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospects

Yang Deng, Wenqiang Lei, Wai Lam +1

Proactive dialogue systems, related to a wide range of real-world conversational applications, equip the conversational agent with the capability of leading the conversation direct…

cs.CL2023★ 5 cited

Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaboration

Yang Deng, Lizi Liao, Liang Chen +3

Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation. However, despite their…

cs.CL2023★ 1 cited

Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors

Keqin Bao, Yu Wan, Dayiheng Liu +5

Fine-grained information on translation errors is helpful for the translation evaluation community. Existing approaches can not synchronously consider error position and type, fail…

cs.LG2023★ 1 cited

FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion

Wentao Shi, Junkang Wu, Xuezhi Cao +4

Learning hyperbolic embeddings for knowledge graph (KG) has gained increasing attention due to its superiority in capturing hierarchies. However, some important operations in hyper…

cs.CL2022★ 1 cited

Reconciliation of Pre-trained Models and Prototypical Neural Networks in Few-shot Named Entity Recognition

Youcheng Huang, Wenqiang Lei, Jie Fu +1

Incorporating large-scale pre-trained models with the prototypical neural networks is a de-facto paradigm in few-shot named entity recognition. Existing methods, unfortunately, are…

cs.CL2022

ConReader: Exploring Implicit Relations in Contracts for Contract Clause Extraction

Weiwen Xu, Yang Deng, Wenqiang Lei +3

We study automatic Contract Clause Extraction (CCE) by modeling implicit relations in legal contracts. Existing CCE methods mostly treat contracts as plain text, creating a substan…

cs.CL2022★ 2 cited

Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task

Keqin Bao, Yu Wan, Dayiheng Liu +5

In this paper, we present our submission to the sentence-level MQM benchmark at Quality Estimation Shared Task, named UniTE (Unified Translation Evaluation). Specifically, our syst…

cs.CL2022★ 3 cited

Alibaba-Translate China's Submission for WMT 2022 Metrics Shared Task

Yu Wan, Keqin Bao, Dayiheng Liu +5

In this report, we present our submission to the WMT 2022 Metrics Shared Task. We build our system based on the core idea of UNITE (Unified Translation Evaluation), which unifies s…

cs.CL2022★ 4 cited

PACIFIC: Towards Proactive Conversational Question Answering over Tabular and Textual Data in Finance

Yang Deng, Wenqiang Lei, Wenxuan Zhang +2

To facilitate conversational question answering (CQA) over hybrid contexts in finance, we present a new dataset, named PACIFIC. Compared with existing CQA datasets, PACIFIC exhibit…

cs.IR2022★ 126 cited

KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos

Chongming Gao, Shijun Li, Yuan Zhang +5

Recommender systems deployed in real-world applications can have inherent exposure bias, which leads to the biased logged data plaguing the researchers. A fundamental way to addres…

cs.CL2022

Draft, Command, and Edit: Controllable Text Editing in E-Commerce

Kexin Yang, Dayiheng Liu, Wenqiang Lei +3

Product description generation is a challenging and under-explored task. Most such work takes a set of product attributes as inputs then generates a description from scratch in a s…

cs.CV2022★ 37 cited

Towards Complex Document Understanding By Discrete Reasoning

Fengbin Zhu, Wenqiang Lei, Fuli Feng +3

Document Visual Question Answering (VQA) aims to understand visually-rich documents to answer questions in natural language, which is an emerging research topic for both Natural La…

cs.AI2022★ 1 cited

RDU: A Region-based Approach to Form-style Document Understanding

Fengbin Zhu, Chao Wang, Wenqiang Lei +2

Key Information Extraction (KIE) is aimed at extracting structured information (e.g. key-value pairs) from form-style documents (e.g. invoices), which makes an important step towar…

cs.CL2022★ 20 cited

Tailor: A Prompt-Based Approach to Attribute-Based Controlled Text Generation

Kexin Yang, Dayiheng Liu, Wenqiang Lei +4

Attribute-based Controlled Text Generation (CTG) refers to generating sentences that satisfy desirable attributes (e.g., emotions and topics). Existing works often utilize fine-tun…

cs.IR2022★ 9 cited

A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systems

Yang Deng, Wenxuan Zhang, Weiwen Xu +3

Recent years witnessed several advances in developing multi-goal conversational recommender systems (MG-CRS) that can proactively attract users' interests and naturally lead user-e…

cs.IR2022★ 9 cited

Interacting with Non-Cooperative User: A New Paradigm for Proactive Dialogue Policy

Wenqiang Lei, Yao Zhang, Feifan Song +5

Proactive dialogue system is able to lead the conversation to a goal topic and has advantaged potential in bargain, persuasion and negotiation. Current corpus-based learning manner…

cs.IR2022★ 12 cited

CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System

Chongming Gao, Shiqi Wang, Shijun Li +6

While personalization increases the utility of recommender systems, it also brings the issue of filter bubbles. E.g., if the system keeps exposing and recommending the items that t…

cs.IR2022★ 155 cited

KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems

Chongming Gao, Shijun Li, Wenqiang Lei +6

The progress of recommender systems is hampered mainly by evaluation as it requires real-time interactions between humans and systems, which is too laborious and expensive. This is…

cs.CL2022★ 7 cited

A Dual Prompt Learning Framework for Few-Shot Dialogue State Tracking

Yuting Yang, Wenqiang Lei, Pei Huang +3

Dialogue state tracking (DST) module is an important component for task-oriented dialog systems to understand users' goals and needs. Collecting dialogue state labels including slo…

cs.AI2021★ 86 cited

DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network

Junkang Wu, Wentao Shi, Xuezhi Cao +5

Knowledge graph completion (KGC) has become a focus of attention across deep learning community owing to its excellent contribution to numerous downstream tasks. Although recently…

cs.CL2021★ 9 cited

TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance

Fengbin Zhu, Wenqiang Lei, Youcheng Huang +5

Hybrid data combining both tabular and textual content (e.g., financial reports) are quite pervasive in the real world. However, Question Answering (QA) over such hybrid data is la…

cs.IR2021★ 343 cited

Advances and Challenges in Conversational Recommender Systems: A Survey

Chongming Gao, Wenqiang Lei, Xiangnan He +2

Recommender systems exploit interaction history to estimate user preference, having been heavily used in a wide range of industry applications. However, static recommendation model…