Xin Liu (刘鑫)

• I am a Ph.D. candidate in Computer Science & Engineering at the University of Michigan as a member of the LAUNCH lab, supervised by Prof. Lu Wang. My research interests focus on Language Generation, particularly the factualness and calibration of language models. Previously, I received my master’s and bachelor’s degrees at Xiamen University, where I was advised by Prof. Jinsong Su.

• Email: Please arrange edu @ . liuxincs umich to get my email address.

• Google Scholar, DBLP

News

• [Sep 2024] Paper Enhancing Language Model Factuality via Activation-Based Confidence Calibration and Guided Decoding is accepted to EMNLP2024.
• [May 2024] Paper Enhanced Language Model Truthfulness with Learnable Intervention and Uncertainty Expression is accepted as a findings paper pf ACL2024.
• [Jan 2024] Paper LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses is accepted to ICLR 2024.
• [May 2023] Paper BOLT: Fast Energy-based Controlled Text Generation with Tunable Biases gets accepted by ACL 2023.
• [Aug 2022] Join the LAUNCH lab at the University of Michigan as a Ph.D. student, advised by Prof. Lu Wang.
• [Mar 2022] Be nominated as the Alibaba Group Outstanding Science Research Intern (13 nominations out of 1,000+ candidates).
• [Dec 2021] Paper KGR^4: Retrieval, Retrospect, Refine and Rethink for Commonsense Generation is accepted by AAAI2022.
• [May 2021] Our model KGR^4 achieves 1st place in CommonGen leaderboard.

Education

• [Aug 2022-] Ph.D. in Computer Science, University of Michigan. Advisor: Prof. Lu Wang.
• [Aug 2019-Jun 2022] M.S. in Software Engineering, Xiamen University. Advisor: Prof. Jinsong Su.
• [Aug 2015-Jun 2019] B.S. in Software Engineering, Xiamen University.

Internship Experience

• [Oct 2020-present] Research Intern in Alibaba Damo Academy. Advisor: Dr. Baosong Yang and Dr. Dayiheng Liu.
• [Mar 2019-Feb 2020] Research Intern in NLP Department of Baidu. Advisor: Dr. Kai Liu.

Publications

• Xin Liu, Muhammad Khalifa, Lu Wang. LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses. ICLR 2024
• Xin Liu, Muhammad Khalifa, Lu Wang. BOLT: Fast Energy-based Controlled Text Generation with Tunable Biases. In the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023)
• Xin Liu, Dayiheng Liu, Baosong Yang, Junwei Ding, Wenqing Yao, Weihua Luo, Haiying Zhang, Jinsong Su. KGR^4: Retrieval, Retrospect, Refine and Rethink for Commonsense Generation. In the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022)
• Xin Liu, Baosong Yang, Dayiheng Liu, Haibo Zhang, Weihua Luo, Min Zhang, Haiying Zhang, Jinsong Su. Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation. In the 59th Annual Meeting of the Association for Computational Linguistics (ACL 2021)
• Xin Liu*, Kai Liu*, Xiang Li*, Jinsong Su, Yubin Ge, Bin Wang, Jiebo Luo. An Iterative Multi-Source Mutual Knowledge Transfer Framework for Machine Reading Comprehension. In the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI 2020)
• Kai Liu*, Xin Liu*, An Yang, Jing Liu, Jinsong Su, Sujian Li, Qiaoqiao She. A Robust Adversarial Training Approach to Machine Reading Comprehension. In the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020)
• Qian Lin, Huating Wen, Jing Yang, Xin Liu, Huan Lin, Hongji Wang, Jinsong Su. The construction of internal hierarchical structure corpus for Chinese words. Journal of Xiamen University (NATURAL SCIENCE EDITION)