← Authors

Haibing Guan

20 papers · 2019–2026 · 10 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (10) πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (9) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (43) πŸŒ‰ Interdisciplinary Bridge 🀝 Dynamic Duo (14) ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (100) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (7) πŸ’Ž Century Club (18)

Conferences

AAAI (5) ICCV (4) ECCV (3) CVPR (2) AISTATS (1) EMNLP (1) ICML (1) IJCAI (1) NIPS (1) OSDI (1)

Top co-authors

Yang Hua (15) Tao Song (14) Ruhui Ma (12) Zhengui XUE (10) Hao Wang (10) Jiaru Zhang (6) Xiaoyu Wu (3) Jianqing Zhang (3) Hanming Deng (3) Chumeng Liang (2)

Research topics

Privacy (2)

Keywords

federated learning (4) diffusion model (2) copyright protection (2) bayesian neural network (2) adversarial learning (2) uncertainty quantification (2) personalized federated learning (2) model personalization (2) epistemic uncertainty (2) adversarial robustness (1) model quantization (1) parameter estimation (1) self-supervised learning (1) knowledge transfer (1) feature extraction (1) image classification (1) temporal information (1) distributed learning (1) fourier analysis (1) domain adaptation (1)

Papers

Poisoning with a Pill: Circumventing Detection in Federated Learning AAAI 2026
SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization AAAI 2026
FlexQuant: A Flexible and Efficient Dynamic Precision Switching Framework for LLM Quantization EMNLP 2025
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning AISTATS 2025
Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-wise Gradient Alignment ICCV 2025
CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion CVPR 2024
SkyMask: Attack-agnostic Robust Federated Learning with Fine-grained Learnable Masks ECCV 2024
FedALA: Adaptive Local Aggregation for Personalized Federated Learning AAAI 2023
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning ICCV 2023
Eliminating Domain Bias for Federated Learning in Representation Space NIPS 2023
Security and Performance in the Delegated User-level Virtualization OSDI 2023
Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples ICML 2023
Improving Bayesian Neural Networks by Adversarial Sampling AAAI 2022
Self-Supervised Vessel Segmentation via Adversarial Learning ICCV 2021
Robust Bayesian Neural Networks by Spectral Expectation Bound Regularization CVPR 2021
Themis: A Fair Evaluation Platform for Computer Vision Competitions IJCAI 2021
Dual Adversarial Network for Deep Active Learning ECCV 2020
FTL: A universal framework for training low-bit DNNs via Feature Transfer ECCV 2020
Reinforcing Neural Network Stability with Attractor Dynamics AAAI 2020
Object Guided External Memory Network for Video Object Detection ICCV 2019