Hello! I’m currently engaged as a researcher with Bytedance Research’s Machine Translation Team in Singapore. Before this, I was a researcher at Huawei Noah’s Ark Lab, also based in Singapore.

My academic journey includes a collaborative PhD program with Alibaba DAMO Academy and Singapore University of Technology and Design (SUTD). I hold a Master of Engineering from Massachusetts Institute of Technology (MIT) and a Bachelor of Engineering from SUTD, graduating with top honors.

My research, primarily in Natural Language Processing (NLP), has led me to contribute to prominent conferences like ACL, EMNLP, NAACL, and AAAI. Additionally, I explore other machine learning areas, particularly Computer Vision (CV) and Speech Recognition.

Presently, I’m immersed in advancing Multimodal Machine Translation. If you’re considering a research internship/full time in our dynamic group, I encourage you to reach out to me via email.

Academic Services

Program Committee/Reviewers: Standing reviewer of Computational Linguistics (CL), COLM 2024, ACL Rolling Review 2021-Present, EMNLP 2023, CL 2023, NeurIPS 2023, AAAI 2023, NeurIPS 2022, EMNLP 2022, ICML 2022, AAAI 2022, ICML 2021, ACL 2021, EMNLP 2021, NAACL 2021, AAAI 2021, ACL 2020, EMNLP 2020

Publications

• PROXYQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models
  Haochen Tan, Zhijiang Guo, Zhan Shi, Lu Xu, Zhili Liu, Xiaoguang Li, Yasheng Wang, Lifeng Shang, Qun Liu, Linqi Song
  In Proceedings of ACL, 2024

• Parameter-Efficient Conversational Recommender System as a Language Processing Task
  Mathieu Ravaut, Hao Zhang, Lu Xu, Aixin Sun, Yong Liu
  In Proceedings of EACL, 2024

• Decomposed Prompt Tuning via Low-Rank Reparameterization
  Yao Xiao, Lu Xu, Jiaxi Li, Wei Lu, Xiaoli Li
  In Findings of EMNLP, 2023

• Sampling Better Negatives for Distantly Supervised Named Entity Recognition
  Lu Xu, Lidong Bing, Wei Lu
  In Findings of ACL, 2023

• Class-Adaptive Self-Training for Relation Extraction with Incompletely Annotated Training Data
  Qingyu Tan, Lu Xu, Lidong Bing, Hwee Tou Ng
  In Findings of ACL, 2023

• Revisiting DocRED–Addressing the False Negative Problem in Relation Extraction
  Qingyu Tan*, Lu Xu*, Lidong Bing, Hwee Tou Ng, Sharifah Mahani Aljunied
  In Proceedings of EMNLP, 2022

• Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction
  Lu Xu*, Yew Ken Chia*, and Lidong Bing
  In Proceedings of ACL, 2021

• Better Feature Integration for Named Entity Recognition
  Lu Xu, Zhanming Jie, Wei Lu, and Lidong Bing
  In Proceedings of NAACL, 2021

• Position-Aware Tagging for Aspect Sentiment Triplet Extraction
  Lu Xu*, Hao Li*, Wei Lu, and Lidong Bing
  In Proceedings of EMNLP, 2020

• Aspect Sentiment Classification with Aspect-Specific Opinion Spans
  Lu Xu, Lidong Bing, Wei Lu, and Fei Huang
  In Proceedings of EMNLP, 2020

• Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis
  Haiyun Peng, Lu Xu, Lidong Bing, Fei Huang, Wei Lu, and Luo Si
  In Proceedings of AAAI, 2020