no code implementations • 21 Oct 2024 • Yiping Ma, Shiyu Hu, Xuchen Li, Yipei Wang, Shiqing Liu, Kang Hao Cheong
Specifically, we: (1) develop a theoretical framework for generating LVSA; (2) integrate human subjective evaluation metrics into GPT-4 assessments, demonstrating a strong correlation between human evaluators and GPT-4 in judging LVSA authenticity; and (3) validate that LLMs can generate human-like, personalized virtual student agents in educational contexts, laying a foundation for future applications in pre-service teacher training and multi-agent simulation environments.
no code implementations • 19 Jun 2024 • Yaochu Jin, Xueming Yan, Shiqing Liu, Xiangyu Wang
Graph neural networks (GNNs) have emerged as a powerful tool for solving combinatorial optimization problems (COPs), exhibiting state-of-the-art performance in both graph-structured and non-graph-structured domains.
no code implementations • 10 Oct 2023 • Shiqing Liu, Xueming Yan, Yaochu Jin
It has been shown that learning-based methods outperform traditional heuristics and mathematical solvers on the Traveling Salesman Problem (TSP) in terms of both performance and computational efficiency.
no code implementations • 27 Oct 2022 • Shiqing Liu, Xueming Yan, Yaochu Jin
The network outputs are then converted into the probability distribution of the Pareto set, from which a set of non-dominated solutions can be sampled non-autoregressively.
no code implementations • 3 Jun 2022 • Shiqing Liu, Haoyu Zhang, Yaochu Jin
Neural architecture search (NAS) has become increasingly popular in the deep learning community recently, mainly because it can provide an opportunity to allow interested users without rich expertise to benefit from the success of deep neural networks (DNNs).
no code implementations • 12 Jun 2021 • Hangyu Zhu, Jinjin Xu, Shiqing Liu, Yaochu Jin
Federated learning is an emerging distributed machine learning framework for privacy preservation.