Exploring Neuron Interactions and Emergence in LLMs: From the Multifractal Analysis Perspective

1 code implementation • 14 Feb 2024 • Xiongye Xiao, Chenyu Zhou, Heng Ping, Defu Cao, Yaxing Li, Yizhuo Zhou, Shixuan Li, Paul Bogdan

Prior studies on the emergence in large models have primarily focused on how the functional capabilities of large language models (LLMs) scale with model size.

Leveraging Reinforcement Learning and Large Language Models for Code Optimization

no code implementations • 9 Dec 2023 • Shukai Duan, Nikos Kanakaris, Xiongye Xiao, Heng Ping, Chenyu Zhou, Nesreen K. Ahmed, Guixiang Ma, Mihai Capota, Theodore L. Willke, Shahin Nazarian, Paul Bogdan

We compare our framework with existing state-of-the-art models and show that it is more efficient with respect to speed and computational usage, as a result of the decrement in training steps and its applicability to models with fewer parameters.

Language Modelling reinforcement-learning +1

On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation

1 code implementation • 15 Jun 2023 • Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han

Although powerful graph neural networks (GNNs) have boosted numerous real-world applications, the potential privacy risk is still underexplored.

Graph Reconstruction Reconstruction Attack