Publications
Lab published papers.
A curated publication list focused on trustworthy AI, federated learning, privacy, robustness, and efficient machine learning.
We prioritize publishing in top-tier, peer-reviewed AI/ML venues. Our recent contributions have been accepted at leading conferences such as CVPR, NeurIPS, ECCV, ICML, ICLR, AAAI, ACL, and WACV.
Lab Published Papers
2026
- Interleaved Selective State Space Models for Efficient WiFi-Based 3D Multi-Person Pose Estimation ICML 2026, conference, Ranking (ICORE2026): A* ICML
- Rethinking Molecular Graph Backdoors under Chemistry-aware Admission arXiv preprint arXiv
- H-SFP: Hierarchical Federated Learning with Decoupled Split-Model Prototyping ECCV 2026, conference, Ranking (ICORE2026): A*
- When Generator Replay Degrades: Projected Rehearsal Orchestration for Heterogeneous Federated Class-Incremental Learning arXiv preprint arXiv
- BackFed: A Standardized and Efficient Benchmark Framework for Evaluating Backdoor Attacks in Federated Learning ICLR 2026 Workshop on Principled Design for Trustworthy AI, workshop, Ranking (ICORE2026): Workshop (ICLR A*) OpenReview
- HFedATM: Hierarchical Federated Domain Generalization via Optimal Transport and Regularized Mean Aggregation CVPR 2026, conference, Ranking (ICORE2026): A* CVFarXiv
- Memory-efficient Continual Learning with Prototypical Exemplar Condensation CVPR 2026 Findings, conference, Ranking (ICORE2026): A* (CVPR) arXiv
- Onboarding Without Forgetting: Hypernetwork Personalization with Data-Free Replay for Personalized Federated Learning CVPR 2026 Findings, conference, Ranking (ICORE2026): A* (CVPR) CVFarXiv
- Clean-Label Physical Backdoor Attacks with Data Distillation AAAI 2026, conference, Ranking (ICORE2026): A* AAAIarXiv
2025
- An Empirical Study of Federated Learning on IoT-Edge Devices: Resource Allocation and Heterogeneity IEEE Transactions on Neural Networks and Learning Systems, journal, Impact Factor (JCR 2024): 8.9 DOIarXiv
- SC-GIR: Goal-oriented Semantic Communication via Invariant Representation Learning for Image Transmission IEEE Transactions on Mobile Computing, journal, Impact Factor (JCR 2024): 9.2 DOIarXiv
- Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks ICLR 2025, conference, Ranking (CORE2023): A* OpenReviewICLR
- FedDDF: Dynamic Dataset Filtering in Federated Large Language Model Training FL-AsiaCCS 2025, workshop, Ranking (CORE2023): Workshop (AsiaCCS A) DOI
- FedKoE: Enhancing Federated Multimodal Learning through Knowledge of Experts FL-AsiaCCS 2025, workshop, Ranking (CORE2023): Workshop (AsiaCCS A) DOI
- FLAT: Latent-Driven Arbitrary-Target Backdoor Attacks in Federated Learning arXiv preprint arXiv
2024
- Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions Engineering Applications of Artificial Intelligence, journal, Impact Factor (JCR 2024): 8.0 DOI
- Benchmarking Federated Few-Shot Learning for Video-Based Action Recognition IEEE Access, journal, Impact Factor (JCR 2024): 3.6 DOI
- Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning IEEE Transactions on Emerging Topics in Computing, journal, Impact Factor (JCR 2024): 5.4 Paper
- Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization CVPR 2024, conference, Ranking (CORE2023): A* CVFarXiv
- Fooling the Textual Fooler via Randomizing Latent Representations Findings of ACL 2024, conference, Ranking (CORE2023): A* (ACL) ACL AnthologyarXiv
- HPE-Li: WiFi-enabled Lightweight Dual Selective Kernel Convolution for Human Pose Estimation ECCV 2024, conference, Ranking (CORE2023): A* Paper
- Towards Efficient Communication Federated Recommendation System via Low-rank Training The Web Conference 2024, conference, Ranking (CORE2023): A* DOIarXiv
- Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks ICLR 2024, conference, Ranking (CORE2023): A* arXiv
- FedFSLAR: A Federated Learning Framework for Few-shot Action Recognition WACV 2024 Workshop, workshop, Ranking (CORE2023): Workshop (WACV A) Paper
- Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape arXiv preprint arXiv
- Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks in Federated Learning arXiv preprint arXiv
2023
- FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Co-Training IEEE Transactions on Network and Service Management, journal, Impact Factor (JCR 2023): 4.7 DOIarXiv
- An Empirical Study of Federated Unlearning: Efficiency and Effectiveness ACML 2023, conference, Ranking (CORE2023): Unranked Paper
- FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection IJCNN 2023, conference, Ranking (CORE2023): B DOIarXiv
- IBA: Towards Irreversible Backdoor Attacks in Federated Learning NeurIPS 2023, conference, Ranking (CORE2023): A* Paper
2022
- Toward Efficient Hierarchical Federated Learning Design Over Multi-Hop Wireless Communications Networks IEEE Access, journal, Impact Factor (JCR 2022): 3.9 Paper
- Emerging Privacy and Trust Issues for Autonomous Vehicle Systems ICOIN 2022, conference, Ranking (CORE2021): Unlisted Paper
- On the Trade-off Between Privacy Protection and Data Utility for Chest X-ray Images ATC 2022, conference, Ranking (CORE2021): Unlisted Paper
2021
- Efficient two-party integer comparison with block vectorization mechanism IEEE Access, journal, Impact Factor (JCR 2021): 3.476 Paper