1 citations · 1 across the 29 of their papers we have counts for
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DASH: Fast Differentiable Architecture Search for Hybrid Attention in Minutes on a Single GPU
Weizhe Chen, Miao Zhang, Junpeng Jiang +3
Hybrid attention architectures are becoming an increasingly important paradigm for improving LLM inference efficiency while preserving model quality, making hybrid architecture des…
SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting
Haomiao Qiu, Miao Zhang, Ziyue Qiao +3
Continual Learning requires a model to learn multiple tasks in sequence while maintaining both stability:preserving knowledge from previously learned tasks, and plasticity:effectiv…
Boost Post-Training Quantization via Null Space Optimization for Large Language Models
Jiaqi Zhao, Miao Zhang, Deng Xiang +3
Existing post-training quantization methods for large language models (LLMs) offer remarkable success. However, the increasingly marginal performance gains suggest that existing qu…
Train with Perturbation, Infer after Merging: A Two-Stage Framework for Continual Learning
Haomiao Qiu, Miao Zhang, Ziyue Qiao +1
Continual Learning (CL) aims to enable models to continuously acquire new knowledge from a sequence of tasks with avoiding the forgetting of learned information. However, existing…