I’m currently a Ph.D. student (from fall, 2022) at the School of Computer Science of Fudan University and a member of the FudanNLP Lab, advised by A.P. Xiaoqing Zheng (郑骁庆) and Prof. Xuanjing Huang (黄萱菁).

My research interests cover Brain-inspired Computing and Large Language Models. I am currently working on Spiking Neural Networks for Sequential Tasks, which includes natural language processing and time series analysis.

First-author Publications: ICLR 2023, ICML 2024, NeurIPS 2024.

Co-author Publications: EMNLP, ACL.

I serve as the reviewer for conferences (ICLR 2025, NeurIPS 2024) and journals (Neural Networks).

🔥 News

• 2024.09:  🎉🎉 One paper on positional encoding for SNNs was accepted by NeurIPS-2024-Spotlight!
• 2024.09:  🎉🎉 Two papers on RAG and LLM safety were accepted by EMNLP-2024-Main/Findings!
• 2024.05:  🎉🎉 Two papers on LLM alignment and PEFT were accepted by ACL-2024-Main!
• 2024.05:  🎉🎉 One paper on time-series forecasting with spiking neural networks was accepted by ICML-2024!
• 2023.10:  🎉🎉 One paper on parameter-efficient-fine-tuning was accepted by EMNLP-2023-Findings!
• 2023.01:  🎉🎉 One paper on spiking neural networks for text classification was accepted by ICLR-2023!

📝 Publications

Spiking Neural Networks

NeurIPS 2024 (Spotlight)

Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators
Changze Lv, Dongqi Han, Yansen Wang, et al.

• A bio-inspired novel positional encoding method for spiking neural networks.
• |

ICML-2024 (Poster)

Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
Changze Lv, Yansen Wang, Dongqi Han, et al.

• A framework for spiking neural networks in time-series forecasting tasks.
• |

ICLR-2023 (Poster)

Spiking Convolutional Neural Networks for Text Classification
Changze Lv, Jianhan Xu, Xiaoqing Zheng

• A “conversion+ fine-tuning” two-step method for training SNNs for text classification.
• |

Arxiv(2308.15122)

SpikeBERT: A Language Spikformer Trained with Two-stage Knowledge Distillation from BERT
Changze Lv, Tianlong Li, Jianhan Xu, et al.

• A spiking language model for language understanding based on Spikformer.
• |

Brain-Inspired Learning

Arxiv(2406.16062)

Towards Biologically Plausible Computing: A Comprehensive Comparison
Changze Lv, Yufei Gu, Zhengkang Guo, et al.

• A comprehensive comparison of various brain-inspired training methods.
• 

Others

• Searching for Best Practices in Retrieval-Augmented Generation
  Xiaohua Wang, Zhenghua Wang, Xuan Gao, Feiran Zhang, Yixin Wu, Zhibo Xu, Tianyuan Shi, Zhengyuan Wang, Shizheng Li, Qi Qian, Ruicheng Yin, Changze Lv, Xiaoqing Zheng, Xuanjing Huang
  |

• Promoting Data and Model Privacy in Federated Learning through Quantized LoRA
  JianHao Zhu, Changze Lv, Xiaohua Wang, Muling Wu, Wenhao Liu, Tianlong Li, Zixuan Ling, Cenyuan Zhang, Xiaoqing Zheng, Xuanjing Huang
  

• Aligning large language models with human preferences through representation engineering
  Wenhao Liu, Xiaohua Wang, Muling Wu, Tianlong Li, Changze Lv, Zixuan Ling, Jianhao Zhu, Cenyuan Zhang, Xiaoqing Zheng, Xuanjing Huang
  |

• Advancing Parameter Efficiency in Fine-tuning via Representation Editing
  Muling Wu, Wenhao Liu, Xiaohua Wang, Tianlong Li, Changze Lv, Zixuan Ling, Jianhao Zhu, Cenyuan Zhang, Xiaoqing Zheng, Xuanjing Huang
  |

• Parameter Efficient Multi-task Fine-tuning by Learning to Transfer Token-wise Prompts
  Muling Wu, Wenhao Liu, Jianhan Xu, Changze Lv, Zixuan Ling, Tianlong Li, Longtao Huang, Xiaoqing Zheng, Xuan-Jing Huang
  |

• Open the Pandora’s Box of LLMs: Jailbreaking LLMs through Representation Engineering
  Tianlong Li, Shihan Dou, Wenhao Liu, Muling Wu, Changze Lv, Xiaoqing Zheng, Xuanjing Huang
  

• Tailoring Personality Traits in Large Language Models via Unsupervisedly-Built Personalized Lexicons
  Tianlong Li, Shihan Dou, Changze Lv, Wenhao Liu, Jianhan Xu, Muling Wu, Zixuan Ling, Xiaoqing Zheng, Xuanjing Huang
  

• SpikeCLIP: A Contrastive Language-Image Pretrained Spiking Neural Network
  Tianlong Li, Wenhao Liu, Changze Lv, Jianhan Xu, Cenyuan Zhang, Muling Wu, Xiaoqing Zheng, Xuanjing Huang
  

• Decoding Continuous Character-based Language from Non-invasive Brain Recordings
  Cenyuan Zhang, Xiaoqing Zheng, Ruicheng Yin, Shujie Geng, Jianhan Xu, Xuan Gao, Changze Lv, Zixuan Ling, Xuanjing Huang, Miao Cao, Jianfeng Feng
  

🎖 Honors and Awards

• 2023 Outstanding Student of Fudan University (复旦大学优秀学生)
• 2022 Excellent graduates of Fudan University (复旦大学优秀毕业生)
• 2021 Shanghai Scholarship (上海市奖学金)
• 2021 First Prize for Outstanding Undergraduate Student Scholarship, Fudan University (复旦大学一等奖学金)
• 2020 Meritorious Prize in the Mathematical Contest in Modeling/Interdisciplinary Contest In Modeling (美国数学建模大赛M奖)
• 2019 Third Prize in the National College Student Mathematics Competition (全国大学生数学竞赛三等奖)

📖 Educations

• 2022.09 - Current, Ph.D. Student in Computer Science (School of Computer Science, Fudan University).
• 2019.09 - 2022.06, Bachelor in Economics (School of Economics and Management, Fudan University, Second Degree)
• 2018.09 - 2022.06, Bachelor in Software Engineering (School of Software, Fudan University)

💻 Internships

• 2023.11 - Current, Microsoft Research Asia, Artificial Intelligence & Machine Learning Group, MSRA.