no code implementations • 7 Sep 2023 • Xiaocheng Yang, Yik-Cheung Tam
Consequently, we employ chain-of-thought to fine-tune LLaMA7B as a baseline model and develop other fine-tuned LLaMA7B models for the generation of Prolog code, Prolog code + chain-of-thought, and chain-of-thought + Prolog code, respectively.
2 code implementations • 6 Jul 2022 • Xiaocheng Yang, Mingyu Yan, Shirui Pan, Xiaochun Ye, Dongrui Fan
Heterogeneous graph neural networks (HGNNs) have powerful capability to embed rich structural and semantic information of a heterogeneous graph into node representations.
Ranked #8 on Node Property Prediction on ogbn-mag
no code implementations • 18 Apr 2022 • Haiyang Lin, Mingyu Yan, Xiaocheng Yang, Mo Zou, WenMing Li, Xiaochun Ye, Dongrui Fan
Graph neural network (GNN) has been demonstrated to be a powerful model in many domains for its effectiveness in learning over graphs.
no code implementations • 9 Aug 2021 • Mingfeng Jiang, Minghao Zhi, Liying Wei, Xiaocheng Yang, Jucheng Zhang, Yongming Li, Pin Wang, Jiahao Huang, Guang Yang
High-resolution magnetic resonance images can provide fine-grained anatomical information, but acquiring such data requires a long scanning time.