1 code implementation • EMNLP 2020 • Qiongkai Xu, Lizhen Qu, Zeyu Gao, Gholamreza Haffari
In this work, we propose to protect personal information by warning users of detected suspicious sentences generated by conversational assistants.
1 code implementation • 26 Feb 2024 • Hao Wang, Zeyu Gao, Chao Zhang, Zihan Sha, Mingyang Sun, Yuchen Zhou, Wenyu Zhu, Wenju Sun, Han Qiu, Xi Xiao
At the core, our approach boosts superior transfer learning capabilities by effectively aligning binary code with their semantics explanations (in natural language), resulting a model able to generate better embeddings for binary code.
no code implementations • 24 Nov 2023 • William McGough, Thomas Buddenkotte, Stephan Ursprung, Zeyu Gao, Grant Stewart, Mireia Crispin-Ortuzar
In the development of our pipeline, we test three detections models: a shape model, a 2D-, and a 3D axial-sample model.
1 code implementation • 21 Nov 2023 • Zeyu Gao, Hao Wang, Yuchen Zhou, Wenyu Zhu, Chao Zhang
Given the significant successes of large language models (LLMs) in various tasks, there is growing anticipation of their efficacy in vulnerability detection.
1 code implementation • 24 Aug 2023 • Wenyu Zhu, Hao Wang, Yuchen Zhou, JiaMing Wang, Zihan Sha, Zeyu Gao, Chao Zhang
By feeding explicit knowledge as additional inputs to the Transformer, and fusing implicit knowledge with a novel pre-training task, kTrans provides a new perspective to incorporating domain knowledge into a Transformer framework.
no code implementations • 21 Jun 2023 • Jinye Qu, Zeyu Gao, Tielin Zhang, YanFeng Lu, Huajin Tang, Hong Qiao
We also present a SNN-based ultra-low latency and high accurate object detection model (SUHD) that achieves state-of-the-art performance on nontrivial datasets like PASCAL VOC and MS COCO, with about remarkable 750x fewer timesteps and 30% mean average precision (mAP) improvement, compared to the Spiking-YOLO on MS COCO datasets.
no code implementations • 8 Oct 2022 • Zeyu Gao, Yao Mu, Ruoyan Shen, Chen Chen, Yangang Ren, Jianyu Chen, Shengbo Eben Li, Ping Luo, YanFeng Lu
End-to-end autonomous driving provides a feasible way to automatically maximize overall driving system performance by directly mapping the raw pixels from a front-facing camera to control signals.
no code implementations • 24 Nov 2021 • Jiangbo Shi, Chang Jia, Zeyu Gao, Tieliang Gong, Chunbao Wang, Chen Li
However, the development of such an automated method requires a large amount of data with precisely annotated masks which is hard to obtain.
no code implementations • 9 Nov 2021 • Jialun Wu, Anyu Mao, Xinrui Bao, Haichuan Zhang, Zeyu Gao, Chunbao Wang, Tieliang Gong, Chen Li
However, there is still a lack of an open and universal digital pathology platform to assist doctors in the management and analysis of digital pathological sections, as well as the management and structured description of relevant patient information.
no code implementations • 26 Oct 2021 • Jialun Wu, Zeyu Gao, Haichuan Zhang, Ruonan Zhang, Tieliang Gong, Chunbao Wang, Chen Li
In this study, we propose a framework that combines pathological images and medical reports to generate a personalized diagnosis result for individual patient.
no code implementations • 26 Oct 2021 • Jialun Wu, Yang Liu, Zeyu Gao, Tieliang Gong, Chunbao Wang, Chen Li
To address this issue, we propose Biomedical Information Extraction, a hybrid neural network to extract relations from biomedical text and unstructured medical reports.
no code implementations • 26 Oct 2021 • Anyu Mao, Jialun Wu, Xinrui Bao, Zeyu Gao, Tieliang Gong, Chen Li
In order to take advantage of segmentation methods based on point annotation, further alleviate the manual workload, and make cancer diagnosis more efficient and accurate, it is necessary to develop an automatic nucleus detection algorithm, which can automatically and efficiently locate the position of the nucleus in the pathological image and extract valuable information for pathologists.
no code implementations • 26 Oct 2021 • Jialun Wu, Haichuan Zhang, Zeyu Gao, Xinrui Bao, Tieliang Gong, Chunbao Wang, Chen Li
Tumor region detection, subtype and grade classification are the fundamental diagnostic indicators for renal cell carcinoma (RCC) in whole-slide images (WSIs).
1 code implementation • 23 Jun 2021 • Zeyu Gao, Bangyang Hong, Xianli Zhang, Yang Li, Chang Jia, Jialun Wu, Chunbao Wang, Deyu Meng, Chen Li
Histological subtype of papillary (p) renal cell carcinoma (RCC), type 1 vs. type 2, is an essential prognostic factor.
1 code implementation • 20 Jun 2021 • Zeyu Gao, Jiangbo Shi, Xianli Zhang, Yang Li, Haichuan Zhang, Jialun Wu, Chunbao Wang, Deyu Meng, Chen Li
In this paper, we propose a Composite High-Resolution Network for ccRCC nuclei grading.
1 code implementation • 12 Aug 2020 • Zeyu Gao, Pargorn Puttapirat, Jiangbo Shi, Chen Li
Semi-supervised learning (SSL) is an effective way to utilize unlabeled data and alleviate the need for labeled data.
no code implementations • 15 Jan 2020 • Pargorn Puttapirat, Haichuan Zhang, Jingyi Deng, Yuxin Dong, Jiangbo Shi, Hongyu He, Zeyu Gao, Chunbao Wang, Xiangrong Zhang, Chen Li
Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine.
no code implementations • 14 Jan 2020 • Jiangbo Shi, Zeyu Gao, Haichuan Zhang, Pargorn Puttapirat, Chunbao Wang, Xiangrong Zhang, Chen Li
In classification, state-of-the-art deep learning-based classifiers perform better when trained by pixel-wise annotation dataset.