Jianwei Li

Hi! I am currently a PhD student at North Carolina State University, under the guidance of Prof. JUNG-EUN KIM. Previously, I worked as a machine learning scientist in Moffett AI, and was guided by the chief scientist and co-founder of Moffett.AI: Ian En-Hsu Yen. Before that, I got my master's degree from the CS department of San Jose State University and was advised by Prof. Mark Stamp. I earned my bachelor's degree from Shandong University.

Currently, I am a Research Scientist Intern at the TikTok Foundations & Intelligence Service (TNS) team for Summer 2026, after starting the summer with the NLP Trust & Safety (TNS) team. Previously, in Summer 2025, I interned with TikTok Responsible Recommendation Systems (RRS) team, where I worked on safety-aware recommendation for multimodal LLM.

Resume / Google Scholar / GitHub / LinkedIn / Twitter

Shadow LLM Guardians

Address: Raleigh, North Carolina
Email: ljw040426 AT gmail DOT com | jli265 AT ncsu DOT edu

Research Landscape

Research organized into AI Safety and Security and AI Efficiency, with paper titles, authors, and venues. Safety and Security covers fine-tuning, jailbreak, backdoor and privacy attack defense. Efficiency covers pruning and quantization.
View full-size diagram ↗
Research Interest

My research centers on Secret Alignment — covert alignment behaviors in large language models and the agents built on them — as the technical foundation for their secure and personalized deployment. I build, understand, evaluate, and defend against these behaviors in the models and agents that increasingly act on our behalf.

What is Secret Alignment? Introduced by me and Prof. Jung-Eun Kim in early 2025, Secret Alignment describes a class of hidden, condition-dependent behaviors in aligned models — the model's response is systematically different under a specific trigger, context, or credential, while remaining indistinguishable from a normally aligned model to any observer without that trigger.

Because the same mechanism can serve legitimate control or hostile subversion, Secret Alignment is fundamentally dual-use:

Adversarial forms (defend against)
  • Backdoor attacks
  • Multi-persona injection (attacker trigger)
  • Sandbagging on capability / safety evaluations
  • Deceptive alignment
  • Steganographic collusion between agents
Legitimate forms (build well)
  • Authentication of model origin
  • Copyright / provenance watermarking
  • Personalization (verified user)
  • Access control & permission gating
  • Kill switch / emergency shutdown

Whether Secret Alignment serves defense or attack depends on who holds the trigger — which is why my work treats it as a first-class object of study and evaluation.

News
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  • [September, 2026] 📝 Invited to serve as Reviewer for ICLR 2027
  • [September, 2026] 🎉 Two papers accepted to NeurIPS 2026.
  • [July, 2026] 📝 Invited to serve as Reviewer for AAAI 2027
  • [June, 2026] 🔄 Transitioned to the Foundations & Intelligence Service (TNS) team at TikTok
  • [June, 2026] 📝 Invited to serve as Reviewer for TMLR
  • [May, 2026] 🥇 Selected as Gold Reviewer of ICML 2026
  • [May, 2026] 💼 Start a research internship program with the NLP Trust & Safety (TNS) team at TikTok
  • [April, 2026] 📝 Invited to serve as Reviewer for NeurIPS 2026
  • [April, 2026] 🎉 One paper is accepted by ICML 2026
  • [March, 2026] 📝 serve as Reviewer for ICML 2026
  • [Jan, 2026] 🎉 Two papers are accepted by ICLR 2026
  • [Oct, 2025] 🎓 Pass PhD written preliminary exam at NCSU
  • [May–Aug, 2025] 💼 Start a research internship program with the Responsible Recommendation Systems (RRS) team at TikTok
  • [May, 2025] 🎉 One paper is accepted by ICML 2025
  • [Feb, 2025] 🎉 One paper is accepted by CPAL 2025
  • [Jul, 2024] 🤝 Start research under the guidance of Prof. Jung-Eun Kim
  • ----------------------------------------
  • [Dec, 2023] 🎤 One paper selected as Oral of FL@FM-NeurIPS 2023
  • [Nov, 2023] 🛡️ Initiated the Shadow-LLM-Guardians Group: https://github.com/Shadow-LLM
  • [Oct, 2023] 🎉 Two papers are accepted by EMNLP 2023
  • [Aug, 2023] 🎓 Start PhD student life at NC State University; Serve as official affiliation of New York University
  • ----------------------------------------
  • [Apr, 2023] 📢 Publicity Chair of the International Workshop onResource-Efficient Learning for Knowledge Discovery @KDD 2023.
  • [Oct, 2022] 📢 Publicity Chair of the first workshop on DL-Hardware Co-Design for AI Acceleration @AAAI 2023.
  • [Sep, 2022] Participated in AI Hardware Summit 2022.
  • [Sep, 2022] 🏆 Moffett S30 Accelerator wins MLPerf V2.1
Preprints
Jianwei Li, Jung-Eun KimSecurity Before Safety: A Backdoor-Centric View of LLM Output Risks in the Private AI Era PDF
Xingli Fang, Jianwei Li, Varun Mulchandani, Jung-Eun KimTrustworthy AI: Safety, Bias, and Privacy — A Survey PDF
Publications
Partial null-space projection of a LoRA update
Jianwei Li, Jung-Eun Kim
Backdoor Purification for LoRA-Tuned LLMs via Null-Space Projection
Main PaperBackdoor: Subspace Purification
PDF
NeurIPS 2026
QES router and quarantined versus benign LoRA experts
Jianwei Li, Min-Seon Kim, Jung-Eun Kim
Not Suppressing or Purifying: Backdoor Containment via Expert Quarantine and Shutdown in LLMs
Main PaperBackdoor: Architectural Containment
PDF
NeurIPS 2026
Retire the “Positive Backdoor” Label—Secret Alignment Requires Strict and Systematic Evaluation
Jianwei Li, Jung-Eun Kim
Retire the “Positive Backdoor” Label—Secret Alignment Requires Strict and Systematic Evaluation
Position PaperSecret Alignment Evaluation
PDF
ICML 2026
Purifying Generative LLMs from Backdoors without Prior Knowledge or Clean Reference
Jianwei Li, Jung-Eun Kim
Purifying Generative LLMs from Backdoors without Prior Knowledge or Clean Reference
Main PaperBackdoor: Weight Purification
PDF Code Project page
ICLR 2026
Superficial Safety Alignment Hypothesis
Jianwei Li, Jung-Eun Kim
Superficial Safety Alignment Hypothesis
Main PaperDefense Fine-tuning Attack
PDF Code Project page
ICLR 2026 (arXiv 2024)
Safety Alignment Can Be Not Superficial With Explicit Safety Signals
Jianwei Li, Jung-Eun Kim
Safety Alignment Can Be Not Superficial With Explicit Safety Signals
Main PaperDefense Jailbreak Attack
PDF Code Project page
ICML 2025
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning
Jianwei Li, Sheng Liu, Qi Lei
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning
Workshop OralDefense Privacy Leakage
FL@FM NeurIPS 2023
Greedy Output Approximation: Towards Efficient Structured Pruning for LLMs Without Retraining
Jianwei Li, Yijun Dong, Qi Lei
Greedy Output Approximation: Towards Efficient Structured Pruning for LLMs Without Retraining
Main PaperStructured Pruning
CPAL 2025
Towards Robust Pruning: An Adaptive Knowledge-Retention Pruning Strategy for Language Models
Jianwei Li, Qi Lei, Wei Cheng, Dongkuan Xu
Towards Robust Pruning: An Adaptive Knowledge-Retention Pruning Strategy for Language Models
Main PaperRobust Pruning
EMNLP 2023
Breaking through Deterministic Barriers: Randomized Pruning Mask Generation and Selection
Jianwei Li, Weizhi Gao, Qi Lei, Dongkuan Xu
Breaking through Deterministic Barriers: Randomized Pruning Mask Generation and Selection
FindingRandomized Pruning
EMNLP 2023
FP8-BERT: Post-Training Quantization for Transformer
Jianwei Li, Tianchi Zhang, Ian En-Hsu Yen, Dongkuan Xu
FP8-BERT: Post-Training Quantization for Transformer
Workshop PaperFP8 Quantization
DCAA@AAAI 2023
Toward Efficient Traffic Signal Control: Smaller Network Can Do More
Shuya Li, Hao Mei, Jianwei Li, Hua Wei, Dongkuan Xu
Toward Efficient Traffic Signal Control: Smaller Network Can Do More
Main PaperEfficient Traffic Control
CDC 2023
Free-Text Keystroke Dynamics for User Authentication
Jianwei Li, Han-Chih Chang, Mark Stamp
Free-Text Keystroke Dynamics for User Authentication
Main PaperFree-Text Authentication
Cybersecurity for Artificial Intelligence
Machine Learning and Deep Learning for Fixed-Text Keystroke Dynamics
Han-Chih Chang*, Jianwei Li*, Ching-Seh Wu, Mark Stamp
Machine Learning and Deep Learning for Fixed-Text Keystroke Dynamics
Main Paper (* Equal Contribution)Fixed-Text Authentication
Cybersecurity for Artificial Intelligence
Machine Learning-Based Analysis of Free-Text Keystroke Dynamics
Han-Chih Chang, Jianwei Li, Mark Stamp
Machine Learning-Based Analysis of Free-Text Keystroke Dynamics
Main PaperKeystroke Analysis
Cybersecurity for Artificial Intelligence
Sparse‐Dyn: Sparse dynamic graph multirepresentation learning via event‐based sparse temporal attention network
Yan Pang, Ai Shan, Zhen Wang, Mengyu Wang, Jianwei Li, Ji Zhang, Teng Huang, Chao Liu
Sparse‐Dyn: Sparse dynamic graph multirepresentation learning via event‐based sparse temporal attention network
Journal PaperDynamic Graph Learning
International Journal of Intelligent Systems
Graph Decipher: A transparent dual-attention graph neural network to understand the message-passing mechanism for the node classification
Yan Pang, Teng Huang, Zhen Wang, Jianwei Li, Poorya Hosseini, Ji Zhang, Chao Liu
Graph Decipher: A transparent dual-attention graph neural network to understand the message-passing mechanism for the node classification
Journal PaperInterpretable Graph Learning
International Journal of Intelligent Systems
Teaching & Research Assistant
  • 2023.08-2024.05, NCSU, Teaching Assistant
  • 2024.06~present, NCSU, Research Assistant
© 2022 jianwei.li All rights reserved
(Last update: October 2, 2026.)