no code implementations • 27 Feb 2024 • Le Cheng, Peican Zhu, Keke Tang, Chao GAO, Zhen Wang
In this paper, we address a more challenging task, rumor source detection with incomplete user data, and propose a novel framework, i. e., Source Detection in Graphs with Incomplete Nodes via Positional Encoding and Attentive Fusion (GIN-SD), to tackle this challenge.
no code implementations • 14 Feb 2024 • Yining Huang, Keke Tang, Meilian Chen
Our results indicate that a strategic mix of distilled and original data markedly elevates the NER capabilities of BERT.
no code implementations • 13 Jan 2024 • Jie Tian, Jixin Hou, Zihao Wu, Peng Shu, Zhengliang Liu, Yujie Xiang, Beikang Gu, Nicholas Filla, Yiwei Li, Ning Liu, Xianyan Chen, Keke Tang, Tianming Liu, Xianqiao Wang
This study is a pioneering endeavor to investigate the capabilities of Large Language Models (LLMs) in addressing conceptual questions within the domain of mechanical engineering with a focus on mechanics.
no code implementations • 3 Aug 2022 • Xiao Zhang, Hao Tan, Xuan Huang, Denghui Zhang, Keke Tang, Zhaoquan Gu
With the development of hardware and algorithms, ASR(Automatic Speech Recognition) systems evolve a lot.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 31 Jan 2022 • Peican Zhu, Xin Hou, Keke Tang, Zhen Wang, Feiping Nie
For feature engineering, feature selection seems to be an important research content in which is anticipated to select "excellent" features from candidate ones.
no code implementations • 29 Aug 2021 • Yining Huang, Shaoze Lin, Yijun Wei, Keke Tang
We propose a knowledge engine called Sinoledge mainly for doctors, physicians, and researchers in medical field to organize thoughts, manage reasoning process, test and deploy to production environments effortlessly.
no code implementations • ICCV 2021 • Keke Tang, Dingruibo Miao, Weilong Peng, Jianpeng Wu, Yawen Shi, Zhaoquan Gu, Zhihong Tian, Wenping Wang
Overconfident predictions on out-of-distribution (OOD) samples is a thorny issue for deep neural networks.
Generative Adversarial Network Out of Distribution (OOD) Detection
no code implementations • 14 Jun 2021 • Yining Huang, Meilian Chen, Keke Tang
We introduce a framework for AI-based medical consultation system with knowledge graph embedding and reinforcement learning components and its implement.
no code implementations • 1 Jan 2021 • Keke Tang, Guodong Wei, Jie Zhu, Yuexin Ma, Runnan Chen, Zhaoquan Gu, Wenping Wang
Deep neural networks have achieved great success in computer vision, thanks to their ability in extracting category-relevant semantic features.
no code implementations • 2 Nov 2020 • Nan Lin, YuXuan Li, Yujun Zhu, Ruolin Wang, Xiayu Zhang, Jianmin Ji, Keke Tang, Xiaoping Chen, Xinming Zhang
Our meta policy tries to manipulate the next optimal state and actual action is produced by the inverse dynamics model.
no code implementations • 27 Nov 2019 • Keke Tang, Peng Song, Yuexin Ma, Zhaoquan Gu, Yu Su, Zhihong Tian, Wenping Wang
High-level (e. g., semantic) features encoded in the latter layers of convolutional neural networks are extensively exploited for image classification, leaving low-level (e. g., color) features in the early layers underexplored.
no code implementations • 17 Dec 2018 • Keke Tang, Guodong Wei, Runnan Chen, Jie Zhu, Zhaoquan Gu, Wenping Wang
In this paper, we propose a general framework for image classification using the attention mechanism and global context, which could incorporate with various network architectures to improve their performance.
no code implementations • 26 Dec 2016 • Keke Tang, Peng Song, Xiaoping Chen
Depth scans acquired from different views may contain nuisances such as noise, occlusion, and varying point density.