3 citations · 6 across the 5 of their papers we have counts for
5 papers
LAS: Loss-less ANN-SNN Conversion for Fully Spike-Driven Large Language Models
Long Chen, Xiaotian Song, Yanan Sun
Spiking Large Language Models (LLMs) have emerged as an energy-efficient alternative to conventional LLMs through their event-driven computation. To effectively obtain spiking LLMs…
FAS: Fast ANN-SNN Conversion for Spiking Large Language Models
Long Chen, Xiaotian Song, Andy Song +3
Spiking Large Language Models have been shown as a good alternative to LLMs in various scenarios. Existing methods for creating Spiking LLMs, i.e., direct training and ANN-SNN conv…
Revisiting Neural Networks for Continual Learning: An Architectural Perspective
Aojun Lu, Tao Feng, Hangjie Yuan +2
Efforts to overcome catastrophic forgetting have primarily centered around developing more effective Continual Learning (CL) methods. In contrast, less attention was devoted to ana…
Differentiable Genetic Programming for High-dimensional Symbolic Regression
Peng Zeng, Xiaotian Song, Andrew Lensen +4
Symbolic regression (SR) is the process of discovering hidden relationships from data with mathematical expressions, which is considered an effective way to reach interpretable mac…
Efficient Evaluation Methods for Neural Architecture Search: A Survey
Xiaotian Song, Xiangning Xie, Zeqiong Lv +4
Neural Architecture Search (NAS) has received increasing attention because of its exceptional merits in automating the design of Deep Neural Network (DNN) architectures. However, t…