Jiancheng Liu
12 papers · 2023–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🐝 Cross-Pollinator (12) 🌍 Conference Polyglot (5) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5)
🐝
Cross-Pollinator
(12)
🤝
Dynamic Duo
(11)
💎
Century Club
(12)
⚡
Prolific Year
(9)
📈
Trend Setter
❓
The Questioner
(2)
Conferences
NIPS (6)
ECCV (2)
ICLR (2)
EMNLP (1)
WACV (1)
Top co-authors
Keywords
machine unlearning
(4)
large language model
(2)
knowledge editing
(2)
gradient-based optimization
(1)
preference optimization
(1)
supervised learning
(1)
adversarial training
(1)
model architecture
(1)
influence function
(1)
text-to-image generation
(1)
diffusion model
(1)
model editing
(1)
data privacy
(1)
second-order optimization
(1)
feature mapping
(1)
model unlearning
(1)
partial differential equation
(1)
graph transformer
(1)
self-supervised learning
(1)
transfer learning
(1)
Papers
Can Adversarial Examples Be Parsed to Reveal Victim Model Information?
WACV 2025
Towards Universal Mesh Movement Networks
NIPS 2024
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
NIPS 2024
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
NIPS 2024
UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
NIPS 2024
Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning
ECCV 2024
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training
ICLR 2024
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
ICLR 2024
To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now
ECCV 2024
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning
EMNLP 2024
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning
NIPS 2023
Model Sparsity Can Simplify Machine Unlearning
NIPS 2023