papers

Publications (11)

cs.CL2016

Detecting "Smart" Spammers On Social Network: A Topic Model Approach

Linqing Liu, Yao Lu, Ye Luo +3

Spammer detection on social network is a challenging problem. The rigid anti-spam rules have resulted in emergence of "smart" spammers. They resemble legitimate users who are diffi…

cs.CL2017

Generative Adversarial Network for Abstractive Text Summarization

Linqing Liu, Yao Lu, Min Yang +3

In this paper, we propose an adversarial process for abstractive text summarization, in which we simultaneously train a generative model G and a discriminative model D. In particul…

cs.LG2023

When Do Flat Minima Optimizers Work?

Jean Kaddour, Linqing Liu, Ricardo Silva +1

Recently, flat-minima optimizers, which seek to find parameters in low-loss neighborhoods, have been shown to improve a neural network's generalization performance over stochastic…

cs.CL2022

Query Expansion Using Contextual Clue Sampling with Language Models

Linqing Liu, Minghan Li, Jimmy Lin +2

Query expansion is an effective approach for mitigating vocabulary mismatch between queries and documents in information retrieval. One recent line of research uses language models…

cs.CL2021

PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them

Patrick Lewis, Yuxiang Wu, Linqing Liu +5

Open-domain Question Answering models which directly leverage question-answer (QA) pairs, such as closed-book QA (CBQA) models and QA-pair retrievers, show promise in terms of spee…

cs.CL2019

Distilling Task-Specific Knowledge from BERT into Simple Neural Networks

Raphael Tang, Yao Lu, Linqing Liu +3

In the natural language processing literature, neural networks are becoming increasingly deeper and complex. The recent poster child of this trend is the deep language representati…