4 citations · 6 across the 14 of their papers we have counts for
4 papers · 1 filter
Utility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs
Minghui Xu, Qi Luo, Kun Li +1
Traditional ``row-count quality coefficient'' approaches fail to capture the nonlinear utility of data for Large Language Model (LLM) capabilities. We present a utility-aw…
M100: An Orchestrated Dataflow Architecture Powering General AI Computing
Yan Xie, Changkui Mao, Changsong Wu +34
As deep learning-based AI technologies gain momentum, the demand for general-purpose AI computing architectures continues to grow. While GPGPU-based architectures offer versatility…
Long Exposure: Accelerating Parameter-Efficient Fine-Tuning for LLMs under Shadowy Sparsity
Tuowei Wang, Kun Li, Zixu Hao +5
The adaptation of pre-trained large language models (LLMs) to diverse downstream tasks via fine-tuning is critical for numerous applications. However, the inefficiency of parameter…
Neuralink: Fast LLM Inference on Smartphones with Neuron Co-Activation Linking
Tuowei Wang, Ruwen Fan, Minxing Huang +6
Large Language Models (LLMs) have achieved remarkable success across various domains, yet deploying them on mobile devices remains an arduous challenge due to their extensive compu…