| 2024 | ACL | REFINESUMM: Self-Refining MLLM for Generating a Multimodal Summarization Dataset. | Vaidehi Patil, Leonardo F. R. Ribeiro, Mengwen Liu, Mohit Bansal, Markus Dreyer |
| 2023 | EACL | Evaluating the Tradeoff Between Abstractiveness and Factuality in Abstractive Summarization. | Markus Dreyer, Mengwen Liu, Feng Nan, Sandeep Atluri, Sujith Ravi |
| 2023 | EACL | Faithfulness-Aware Decoding Strategies for Abstractive Summarization. | David Wan, Mengwen Liu, Kathleen R. McKeown, Markus Dreyer, Mohit Bansal |
| 2022 | NAACL | FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations. | Leonardo F. R. Ribeiro, Mengwen Liu, Iryna Gurevych, Markus Dreyer, Mohit Bansal |
| 2021 | NAACL | Efficiently Summarizing Text and Graph Encodings of Multi-Document Clusters. | Ramakanth Pasunuru, Mengwen Liu, Mohit Bansal, Sujith Ravi, Markus Dreyer |
| 2019 | ACL | Multi-Task Networks with Universe, Group, and Task Feature Learning. | Shiva Pentyala, Mengwen Liu, Markus Dreyer |
| 2017 | IJCNN | 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 |
| 2016 | CIKM | Mobile App Retrieval for Social Media Users via Inference of Implicit Intent in Social Media Text. | Dae Hoon Park, Yi Fang, Mengwen Liu, ChengXiang Zhai |
| 2016 | ICTIR | A Unified Energy-based Framework for Learning to Rank. | Yi Fang, Mengwen Liu |
| 2016 | SIGIR | Retrieving Non-Redundant Questions to Summarize a Product Review. | Mengwen Liu, Yi Fang, Dae Hoon Park, Xiaohua Hu, Zhengtao Yu |
| 2015 | ACL | Tackling Sparsity, the Achilles Heel of Social Networks: Language Model Smoothing via Social Regularization. | Rui Yan, Xiang Li, Mengwen Liu, Xiaohua Hu |
| 2015 | SIGIR | Leveraging User Reviews to Improve Accuracy for Mobile App Retrieval. | Dae Hoon Park, Mengwen Liu, ChengXiang Zhai, Haohong Wang |