An error detecting and tagging framework for reducing data entry errors in electronic medical records (EMR) system. - Yuan Ling; Yuan An; Mengwen Liu; Xiaohua Hu 001 (BIBM, 2013)

An evaluation of identification of suspected autism spectrum disorder (ASD) cases in early intervention (EI) records. - Mengwen Liu; Yuan An; Xiaohua Hu 001; Debra Langer; Craig Newschaffer; Lindsay Shea (BIBM, 2013)

Relation extraction from biomedical literature with minimal supervision and grouping strategy. - Mengwen Liu; Yuan Ling; Yuan An; Xiaohua Hu 001 (BIBM, 2014)

Pairwise Topic Model via relation extraction. - Xiaoli Song; Yue Shang; Yuan Ling; Mengwen Liu; Xiaohua Hu 001 (IEEE BigData, 2014)

Tackling Sparsity, the Achilles Heel of Social Networks: Language Model Smoothing via Social Regularization. - Rui Yan 001; Xiang Li 065; Mengwen Liu; Xiaohua Hu 001 (ACL (2), 2015)

Scalable user intent mining using a multimodal Restricted Boltzmann Machine. - Yue Shang; Wanying Ding; Mengwen Liu; Xiaoli Song; Tony Hu; Yuan An; Haohong Wang; Lifan Guo (ICNC, 2015)

Leveraging User Reviews to Improve Accuracy for Mobile App Retrieval. - Dae Hoon Park; Mengwen Liu; ChengXiang Zhai; Haohong Wang (SIGIR, 2015)

Mobile App Retrieval for Social Media Users via Inference of Implicit Intent in Social Media Text. - Dae Hoon Park; Yi Fang 008; Mengwen Liu; ChengXiang Zhai (CIKM, 2016)

A Unified Energy-based Framework for Learning to Rank. - Yi Fang 008; Mengwen Liu (ICTIR, 2016)

Retrieving Non-Redundant Questions to Summarize a Product Review. - Mengwen Liu; Yi Fang 008; Dae Hoon Park; Xiaohua Hu 001; Zhengtao Yu 001 (SIGIR, 2016)

Bacterial named entity recognition based on dictionary and conditional random field. - Xiaoyan Wang; Xingpeng Jiang; Mengwen Liu; Tingting He 003; Xiaohua Hu 001 (BIBM, 2017)

Integrating extra knowledge into word embedding models for biomedical NLP tasks. - Yuan Ling; Yuan An; Mengwen Liu; Sadid A. Hasan; Ye-tian Fan; Xiaohua Hu 001 (IJCNN, 2017)

Which used product is more sellable? A time-aware approach. - Mengwen Liu; Wanying Ding; Dae Hoon Park; Yi Fang 008; Rui Yan 001; Xiaohua Hu 001 (Inf. Retr. J., 2017)

Product review summarization through question retrieval and diversification. - Mengwen Liu; Yi Fang 008; Alexander G. Choulos; Dae Hoon Park; Xiaohua Hu 001 (Inf. Retr. J., 2017)

A New TV World for Kids - When ZUI Meets Deep Learning. - Haohong Wang; Yaoyuan Fu; Yang Li 091; Guanghan Ning; Zhihai He; Mengwen Liu (MIPR, 2018)

Multi-Task Networks with Universe, Group, and Task Feature Learning. - Shiva Pentyala; Mengwen Liu; Markus Dreyer (ACL (1), 2019)

Efficiently Summarizing Text and Graph Encodings of Multi-Document Clusters. - Ramakanth Pasunuru; Mengwen Liu; Mohit Bansal; Sujith Ravi; Markus Dreyer (NAACL-HLT, 2021)

Transductive Learning for Abstractive News Summarization. - Arthur Brazinskas; Mengwen Liu; Ramesh Nallapati; Sujith Ravi; Markus Dreyer (CoRR, 2021)

Analyzing the Abstractiveness-Factuality Tradeoff With Nonlinear Abstractiveness Constraints. - Markus Dreyer; Mengwen Liu; Feng Nan; Sandeep Atluri; Sujith Ravi (CoRR, 2021)

FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations. - Leonardo F. R. Ribeiro; Mengwen Liu; Iryna Gurevych; Markus Dreyer; Mohit Bansal (NAACL-HLT, 2022)

Evaluating the Tradeoff Between Abstractiveness and Factuality in Abstractive Summarization. - Markus Dreyer; Mengwen Liu; Feng Nan; Sandeep Atluri; Sujith Ravi (EACL (Findings), 2023)

Faithfulness-Aware Decoding Strategies for Abstractive Summarization. - David Wan; Mengwen Liu; Kathleen R. McKeown; Markus Dreyer; Mohit Bansal (EACL, 2023)

REFINESUMM: Self-Refining MLLM for Generating a Multimodal Summarization Dataset. - Vaidehi Patil; Leonardo F. R. Ribeiro; Mengwen Liu; Mohit Bansal; Markus Dreyer (ACL (1), 2024)

An enhanced network model for PCB defect detection: CDS-YOLO. - Mingrui Shao; Long Min; Mengwen Liu; Xuelin Li; Jingjing liu; Xiaozhou Li (J. Real Time Image Process., 2024)

A multi-domain constraint learning system inspired by adaptive cognitive graphs for emotion recognition. - Dongrui Gao; Mengwen Liu; Haokai Zhang; Manqing Wang; Hongli Chang; Gaoxiang Ouyang; Shihong Liu; Pengrui Li (Neural Networks, 2025)