1 code implementation • 2 Dec 2024 • Shuaijiang Zhao, Tingwei Guo, Bajian Xiang, Tongtang Wan, Qiang Niu, Wei Zou, Xiangang Li
The GPT-4o represents a significant milestone in enabling real-time interaction with large language models (LLMs) through speech, its remarkable low latency and high fluency not only capture attention but also stimulate research interest in the field.
1 code implementation • 2 Oct 2023 • Sen Li, Xu Yang, Anye Cao, Changbin Wang, Yaoqi Liu, Yapeng Liu, Qiang Niu
The most significant improvements, in comparison to existing models, are observed in phase-P picking, phase-S picking, and magnitude estimation, with gains of 1. 7%, 9. 5%, and 8. 0%, respectively.
2 code implementations • 16 Apr 2023 • Yunjie Ji, Yan Gong, Yong Deng, Yiping Peng, Qiang Niu, Baochang Ma, Xiangang Li
Recently, significant public efforts have been directed towards developing low-cost models with capabilities akin to ChatGPT, thereby fostering the growth of open-source conversational models.
1 code implementation • 26 Mar 2023 • Yunjie Ji, Yong Deng, Yan Gong, Yiping Peng, Qiang Niu, Lei Zhang, Baochang Ma, Xiangang Li
However current research rarely studies the impact of different amounts of instruction data on model performance, especially in the real-world use cases.
1 code implementation • 17 Aug 2022 • Binrui Shen, Qiang Niu, Shengxin Zhu
The advanced constraining operator enables a CSGO for large graph matching, which outperforms state-of-the-art methods in experiments.
no code implementations • 4 Jul 2022 • Di Zhang, Qiang Niu, Youzhou Zhou
2) If the variational inference(VI) is used for state estimation, it runs much faster than Monte Carlo(MC) methods since the calculation of the posterior uses only basic arithmetic operations.
no code implementations • 1 Apr 2021 • Zixun Lan, Limin Yu, Linglong Yuan, Zili Wu, Qiang Niu, Fei Ma
Comparing with the previous GNNs-based methods for subgraph matching task, our proposed Sub-GMN allows varying query and data graphes in the test/application stage, while most previous GNNs-based methods can only find a matched subgraph in the data graph during the test/application for the same query graph used in the training stage.
no code implementations • 16 Jan 2020 • Binrui Shen, Qiang Niu, Shengxin Zhu
Fabricating experimental pictures in research work is a serious academic misconduct, which should better be detected in the reviewing process.