Summary of Multi-layer Transformers Gradient Can Be Approximated in Almost Linear Time, by Yingyu Liang et al.
Multi-Layer Transformers Gradient Can be Approximated in Almost Linear Timeby Yingyu Liang, Zhizhou Sha, Zhenmei…
Multi-Layer Transformers Gradient Can be Approximated in Almost Linear Timeby Yingyu Liang, Zhizhou Sha, Zhenmei…
Deep Analysis of Time Series Data for Smart Grid Startup Strategies: A Transformer-LSTM-PSO Model Approachby…
LLM-Barber: Block-Aware Rebuilder for Sparsity Mask in One-Shot for Large Language Modelsby Yupeng Su, Ziyi…
A Unified Framework for Interpretable Transformers Using PDEs and Information Theoryby Yukun ZhangFirst submitted to…
Linear Attention is Enough in Spatial-Temporal Forecastingby Xinyu NingFirst submitted to arxiv on: 17 Aug…
Beyond Uniform Query Distribution: Key-Driven Grouped Query Attentionby Zohaib Khan, Muhammad Khaquan, Omer Tafveez, Burhanuddin…
Quantum-inspired Interpretable Deep Learning Architecture for Text Sentiment Analysisby Bingyu Li, Da Zhang, Zhiyuan Zhao,…
Enhancing Visual Question Answering through Ranking-Based Hybrid Training and Multimodal Fusionby Peiyuan Chen, Zecheng Zhang,…