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, Large Language Models, Multi-Modal LLMs, and AI for Science. I am currently working on Spiking Neural Networks for Sequential Tasks and Biologically-Plausible Learning Algorithms.

First-author publications in ICML, NeurIPS, and ICLR.

Co-author publications in ACL, EMNLP, and COLING.

I serve as the reviewer for conferences (ICML, ICLR, NeurIPS, ACL, IJCAI, COLING) and journals (Neural Networks).

Phone/Wechat: 13967492189. Please feel free to reach out to me.

📖 Educations

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

💻 Internships

• 2023.11 - 2025.02, Microsoft Research Asia, Artificial Intelligence & Machine Learning Group.
• 2025.03 - Current, Shanghai AI Lab, AI for Science Group.

🔥 News

• 2024.12:  🎉🎉 One paper on Jailbreak of LLMs was accepted by COLING-2025!
• 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(2501.16745)

Toward Relative Positional Encoding in Spiking Transformers
Changze Lv, Yansen Wang, Dongqi Han, et al.

• A relative positional encoding for spiking Transformers based on Gray Code.
• |

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(2501.09976)

Dendritic Localized Learning: Toward Biologically Plausible Algorithm
Changze Lv*, Jingwen Xu*, Yiyang Lu*, et al.

• A novel biologically plausible training method.
• 

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.
• 

Large Language Models

Arxiv(2503.04355)

Layer-Specific Scaling of Positional Encodings for Superior Long-Context Modeling
Zhenghua Wang*, Yiran Ding*, Changze Lv*, et al.

• A layer-specific positional encoding scaling method.
• 

Others

• Revisiting Jailbreaking for Large Language Models: A Representation Engineering Perspective
  Tianlong Li, Zhenghua Wang, Wenhao Liu, Muling Wu, Shihan Dou, Changze Lv, Xiaohua Wang, Xiaoqing Zheng, Xuanjing Huang
  

• 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
  |

• 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
  

• Explainable Synthetic Image Detection through Diffusion Timestep Ensembling
  Yixin Wu, Feiran Zhang, Tianyuan Shi, Ruicheng Yin, Zhenghua Wang, Zhenliang Gan, Xiaohua Wang, Changze Lv, 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
  

• Multi-Programming Language Sandbox for LLMs
  Shihan Dou, Jiazheng Zhang, Jianxiang Zang, Yunbo Tao, Haoxiang Jia, Shichun Liu, Yuming Yang, Shenxi Wu, Shaoqing Zhang, Muling Wu, Changze Lv, Limao Xiong, Wenyu Zhan, Lin Zhang, Rongxiang Weng, Jingang Wang, Xunliang Cai, Yueming Wu, Ming Wen, Rui Zheng, Tao Ji, Yixin Cao, Tao Gui, Xipeng Qiu, Qi Zhang, Xuanjing Huang
  

🎖 Honors and Awards

• 2025 Stars of Tomorrow Internship Program of Microsoft Research Asia (微软亚洲研究院“明日之星”)
• 2024 Outstanding Student Leader of Fudan University (复旦大学优秀学生干部)
• 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)

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