2 papers
cs.CV2026
What to Remove, What to Preserve: Dual-Ambiguity Rectification for All-in-One Image Restoration
Cencen Liu, Wen Yin, Dongyang Zhang +6
All-in-one image restoration aims to handle diverse degradations within a unified framework. Existing methods commonly encode heterogeneous degradation conditions in a shared laten…
cs.LG2025
OMoE: Diversifying Mixture of Low-Rank Adaptation by Orthogonal Finetuning
Jinyuan Feng, Zhiqiang Pu, Tianyi Hu +3
Building mixture-of-experts (MoE) architecture for Low-rank adaptation (LoRA) is emerging as a potential direction in parameter-efficient fine-tuning (PEFT) for its modular design…