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Protein Representation Learning via Knowledge Enhanced Reasoning
Published in International Conference on Learning Representations (ICLR), 2023, CCF-A, 2023
Knowledge-enhanced protein representation learning through post-training and reasoning.
Recommended citation: Yunxiang Fu, Hong-Yu Zhou, Zhicheng Zhang, Cheng Bian, Yizhou Yu. "Protein Representation Learning via Knowledge Enhanced Reasoning." International Conference on Learning Representations (ICLR), 2023.
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DreamDA: Generative Data Augmentation with Diffusion Models
Published in Journal submission, 2024
Generative data augmentation with diffusion models.
Recommended citation: Yunxiang Fu, Chaoqi Chen, Yu Qiao, Yizhou Yu. "DreamDA: Generative Data Augmentation with Diffusion Models." Journal submission.
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LaMamba-Diff: Linear-Time High-Fidelity Diffusion Models Based on Local Attention and Mamba
Published in British Machine Vision Conference (BMVC), 2025, 2024
Linear-time high-fidelity diffusion models using local attention and Mamba.
Recommended citation: Yunxiang Fu, Chaoqi Chen, Yizhou Yu. "LaMamba-Diff: Linear-Time High-Fidelity Diffusion Models Based on Local Attention and Mamba." British Machine Vision Conference (BMVC), 2025.
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SparX: A Sparse Cross-Layer Connection Mechanism for Hierarchical Vision Mamba and Transformer Networks
Published in AAAI Conference on Artificial Intelligence (AAAI), 2025, CCF-A, 2024
Sparse cross-layer connections for hierarchical Vision Mamba and Transformer networks.
Recommended citation: Meng Lou, Yunxiang Fu, Yizhou Yu. "SparX: A Sparse Cross-Layer Connection Mechanism for Hierarchical Vision Mamba and Transformer Networks." AAAI Conference on Artificial Intelligence (AAAI), 2025.
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SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025, CCF-A, 2024
Omni-scale context modeling for semantic segmentation with state space models and local attention.
Recommended citation: Yunxiang Fu, Meng Lou, Yizhou Yu. "SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation." IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
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Scaling Continual Learning to 300+ Tasks with Bi-Level Routing Mixture-of-Experts
Published in International Conference on Machine Learning (ICML), 2026, CCF-A, 2026
Scaling continual learning to long task sequences with bi-level routing mixture-of-experts.
Recommended citation: Meng Lou, Yunxiang Fu, Yizhou Yu. "Scaling Continual Learning to 300+ Tasks with Bi-Level Routing Mixture-of-Experts." International Conference on Machine Learning (ICML), 2026.
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One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning
Published in NeurIPS 2026 submission, 2026
Task-conditioned feature transformations for parameter-efficient continual learning with one shared adapter.
Recommended citation: Yunxiang Fu, Meng Lou, Yizhou Yu. "One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning." NeurIPS 2026 submission.