Author

Yik-Chung Wu

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#machine learning Preprint Sep 2026

Automatic Rank Allocation for Low-Rank Adaptation in Large Language Models via lp Regularization

Low-rank adaptation (LoRA) has become a popular parameter-efficient fine-tuning method for large language models. A key challenge in LoRA is how to determine the rank of each adaptation matrix, as rank directly controls its capacity and efficiency. Existing adaptive-rank methods typically allocate ranks according to ma...

Ze-Bang Xie, Chuan-Yang Zheng, Yik-Chung Wu et al. · 0 citations

#artificial intelligence Jun 2026

Memory-Native Non-Terrestrial Networks for Embodied Intelligence

This paper proposes the memory-native NTN (Mem-NTN) paradigm that leverages long-horizon contexts for memory-augmented system optimization and establishes a dual-memory architecture that distinguishes between physical memory representing the state of the world and digital memory encoding historical network experience.

Chengyang Li, Yi-Kun Wang, Jia-Hui He et al. · IEEE Communications Standard... · 0 citations

Preprint Aug 2026

FluxBin: Flexible LUT-based Ultra-low-bit LLM Inference by Algorithm-Kernel Synergy

FluxBin is proposed, an algorithm-kernel co-design that synergizes post-training quantization with a highly optimized CUDA kernel and introduces Decoupled Row-Column Binary Decomposition to enhance representational capacity while maintaining hardware efficiency.

Qingyao Yang, Run-Ming Yang, He Xiao et al. · 0 citations