most citedA Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systems

9 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2023

mPMR: A Multilingual Pre-trained Machine Reader at Scale

Weiwen Xu, Xin Li, Wai Lam +1

We present multilingual Pre-trained Machine Reader (mPMR), a novel method for multilingual machine reading comprehension (MRC)-style pre-training. mPMR aims to guide multilingual p…

cs.CL2022★ 4 cited

From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Model to Pre-trained Machine Reader

Weiwen Xu, Xin Li, Wenxuan Zhang +4

We present Pre-trained Machine Reader (PMR), a novel method for retrofitting pre-trained masked language models (MLMs) to pre-trained machine reading comprehension (MRC) models wit…

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★ 1 cited

PeerDA: Data Augmentation via Modeling Peer Relation for Span Identification Tasks

Weiwen Xu, Xin Li, Yang Deng +2

Span identification aims at identifying specific text spans from text input and classifying them into pre-defined categories. Different from previous works that merely leverage the…

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.CL2022

Improving Lexical Embeddings for Robust Question Answering

Weiwen Xu, Bowei Zou, Wai Lam +1

Recent techniques in Question Answering (QA) have gained remarkable performance improvement with some QA models even surpassed human performance. However, the ability of these mode…