no code implementations • 26 Apr 2024 • Yichuan Li, Kaize Ding, Jianling Wang, Kyumin Lee
With the capabilities of understanding and executing natural language instructions, Large language models (LLMs) can potentially act as a powerful tool for textual data augmentation.
1 code implementation • 11 Mar 2024 • Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee, Xiaohu Liu, Chenlei Guo
Large Language models (LLMs) have demonstrated impressive in-context learning (ICL) capabilities, where a LLM makes predictions for a given test input together with a few input-output pairs (demonstrations).
1 code implementation • 23 Oct 2023 • Yichuan Li, Kaize Ding, Kyumin Lee
Self-supervised representation learning on text-attributed graphs, which aims to create expressive and generalizable representations for various downstream tasks, has received increasing research attention lately.
no code implementations • 2 May 2023 • Yichuan Li, Jialong Han, Kyumin Lee, Chengyuan Ma, Benjamin Yao, Derek Liu
In recent years, Pre-trained Language Models (PLMs) have shown their superiority by pre-training on unstructured text corpus and then fine-tuning on downstream tasks.
no code implementations • 14 Apr 2022 • Kai Chen, Rui Cao, Stephen James, Yichuan Li, Yun-hui Liu, Pieter Abbeel, Qi Dou
To continuously improve the quality of pseudo labels, we iterate the above steps by taking the trained student model as a new teacher and re-label real data using the refined teacher model.
no code implementations • 7 Apr 2022 • Yonghai Gong, Yichuan Li, Nikolaos M. Freris
Federated Learning (FL) is an emerging framework for distributed processing of large data volumes by edge devices subject to limited communication bandwidths, heterogeneity in data distributions and computational resources, as well as privacy considerations.
no code implementations • 27 Nov 2021 • Yichuan Li, Salman Ghafoor, Mohammed El-Hajjar
Hence, in this article, we propose an analogue radio over fiber (A-RoF) aided multi-service network architecture for high-speed trains, in order to enhance the quality of service as well as reduce the cost of the radio access network (RAN).
no code implementations • 27 Nov 2021 • Yichuan Li, Qijie Xie, Mohammed El-Hajjar, Lajos Hanzo
The radio access network (RAN) connects the users to the core networks, where typically digitised radio over fiber (D-RoF) links are employed.
1 code implementation • 8 Dec 2020 • Kai Shu, Yichuan Li, Kaize Ding, Huan Liu
The existing text generation methods either afford limited supplementary information or lose consistency between the input and output which makes the synthetic news less trustworthy.
2 code implementations • 8 Nov 2020 • Yichuan Li, Bohan Jiang, Kai Shu, Huan Liu
The COVID-19 epidemic is considered as the global health crisis of the whole society and the greatest challenge mankind faced since World War Two.
Social and Information Networks Computers and Society
no code implementations • 3 Apr 2020 • Kai Shu, Guoqing Zheng, Yichuan Li, Subhabrata Mukherjee, Ahmed Hassan Awadallah, Scott Ruston, Huan Liu
Social media has greatly enabled people to participate in online activities at an unprecedented rate.
no code implementations • 19 Aug 2019 • Kaize Ding, Yichuan Li, Jundong Li, Chenghao Liu, Huan Liu
Inspired by the immense success of deep learning, graph neural networks (GNNs) are widely used to learn powerful node representations and have demonstrated promising performance on different graph learning tasks.