Hi, my name is Wei Liu (刘威). Currently, I am a final-year graduate student at ShanghaiTech University, advised by Prof. Kewei Tu. I am also an incoming PhD at HKUST NLP, supervised by Prof. Junxian He.
I am focusing on natural language processing (NLP) and machine learning (ML).
To be more specific, my research interests lie in:
- Efficiency in Large Language Models (LLMs): Enhancing efficiency in training, inference, and handling long-range scenarios for Large Language Models (LLMs)
- Large Language Models (LLMs): Explorations of the emergent capabilities and applications in complex scenarios.
- Structured Predictions: Parsing and application of parsing algorithm in downstream tasks.
- Deep Generative Models: Deep Latent-variable models.
News
- [01/2024] Our Deita paper What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning has been accepted by ICLR2024!
- [12/2023] Our Deita (Data-Efficient Instruction Tuning for Alignment) Project has been released! Utilizing only 6K samples of SFT data selected by Deita, along with 10K randomly selected preference data, our Deita-7B model has achieved remarkable results, scoring 7.55 on the MT-Bench benchmark, 90.06% on AlpacaEval, and 69.86 on the OpenLLM Benchmark! Welcome to try!
📝 Publications (* denotes equal contribution)
In Proceedings of ICLR, 2024. project
Wei Liu*, Weihao Zeng*, Keqing He, Yong Jiang, Junxian He
MathAttack: Attacking Large Language Models Towards Math Solving Ability
In Proceedings of AAAI, 2024.
Zihao Zhou, Qiufeng Wang, Mingyu Jin, Jie Yao, Jianan Ye, Wei Liu, Wei Wang, Xiaowei Huang, Kaizhu Huang
SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding
In Proceedings of AAAI, 2024. code
Tianyu Yu*, Chengyue Jiang*, Chao Lou*, Shen Huang*, Xiaobin Wang, Wei Liu, Jiong Cai, Yangning Li, Yinghui Li, Kewei Tu, Hai-Tao Zheng, Ningyu Zhang, Pengjun Xie, Fei Huang, Yong Jiang
Simple Hardware-Efficient PCFGs with Independent Left and Right Productions
Wei Liu*, Songlin Yang*, Yoon Kim, Kewei Tu
In Findings of EMNLP, 2023. code
Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural Networks
Zhaohui Yan, Songlin Yang, Wei Liu, Kewei Tu
In Proceedings of EMNLP, 2023. code
Structured Mean-Field Variational Inference for Higher-Order Span-Based Semantic Role Labeling
In Findings of ACL, 2023. code
Wei Liu, Songlin Yang, Kewei Tu
Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGs
Songlin Yang*, Wei Liu*, Kewei Tu
In Proceedings of NAACL, 2022(Top-3 Score in ARR Jan 2022). code
Knowledge-Based Chat Detection With False Mention Discrimination
Wei Liu, Peijie Huang, Dongzhu Liang, Zihao Zhou
In Proceedings of ICASSP, 2021.
A Knowledge-gated Mechanism for Utterance Domain Classification
Zefeng Du, Peijie Huang, Yuhong He, Wei Liu & Jiankai Zhu
In Proceedings of NLPCC, 2019.
👥 Service
- Reviewer: ARR, ACL, NAACL, EMNLP, COLM
💻 Internships
-
2023.11 - present, Shanghai AI Laboratory
-
2022.07 - 2023.10, Alibaba DAMO Academy
🏆 Awards
- 2023 National Scholarship in China
📖 Educations
- 2021.09 - Present, ShanghaiTech University, M.S. in computer science
- 2017.09 - 2021.06, South China Agricultural University, B.E. in computer science