1 code implementation • 30 Nov 2024 • Bytedance-Seed-Foundation-Code-Team, :, Yao Cheng, Jianfeng Chen, Jie Chen, Li Chen, Liyu Chen, Wentao Chen, Zhengyu Chen, Shijie Geng, Aoyan Li, Bo Li, Bowen Li, Linyi Li, Boyi Liu, Jerry Liu, Kaibo Liu, Qi Liu, Shukai Liu, Siyao Liu, Tianyi Liu, Tingkai Liu, Yongfei Liu, Rui Long, Jing Mai, Guanghan Ning, Z. Y. Peng, Kai Shen, Jiahao Su, Jing Su, Tao Sun, Yifan Sun, Yunzhe Tao, Guoyin Wang, Siwei Wang, Xuwu Wang, Yite Wang, Zihan Wang, Jinxiang Xia, Liang Xiang, Xia Xiao, Yongsheng Xiao, Chenguang Xi, Shulin Xin, Jingjing Xu, Shikun Xu, Hongxia Yang, Jack Yang, Yingxiang Yang, Jianbo Yuan, Jun Zhang, Yufeng Zhang, Yuyu Zhang, Shen Zheng, He Zhu, Ming Zhu
As the capabilities of code large language models (LLMs) continue to expand, their applications across diverse code intelligence domains are rapidly increasing.
no code implementations • 18 Nov 2024 • Pengjun Guo, He Zhu
This extensive dataset enables the evaluation of gene set enrichment across a wide range of phenotypes, facilitating the inference of associations between specified gene sets and phenotypic traits.
no code implementations • 4 Nov 2024 • Shukai Liu, Linzheng Chai, Jian Yang, Jiajun Shi, He Zhu, Liran Wang, Ke Jin, Wei zhang, Hualei Zhu, Shuyue Guo, Tao Sun, Jiaheng Liu, Yunlong Duan, Yu Hao, Liqun Yang, Guanglin Niu, Ge Zhang, Zhoujun Li
Code large language models (LLMs) have made significant progress in code debugging by directly generating the correct code based on the buggy code snippet.
1 code implementation • 3 Nov 2024 • Yuanlin Duan, Wensen Mao, He Zhu
Learning world models offers a promising avenue for goal-conditioned reinforcement learning with sparse rewards.
1 code implementation • 3 Nov 2024 • Yuanlin Duan, Guofeng Cui, He Zhu
Exploring unknown environments efficiently is a fundamental challenge in unsupervised goal-conditioned reinforcement learning.
no code implementations • 28 Oct 2024 • Jiaheng Liu, Ken Deng, Congnan Liu, Jian Yang, Shukai Liu, He Zhu, Peng Zhao, Linzheng Chai, Yanan Wu, Ke Jin, Ge Zhang, Zekun Wang, Guoan Zhang, Bangyu Xiang, Wenbo Su, Bo Zheng
Besides, the existing benchmarks usually report overall average scores of different languages, where the fine-grained abilities in different completion scenarios are ignored.
no code implementations • 23 Oct 2024 • He Zhu, Ren Togo, Takahiro Ogawa, Miki Haseyama
Conventional medical artificial intelligence (AI) models face barriers in clinical application and ethical issues owing to their inability to handle the privacy-sensitive characteristics of medical data.
Medical Visual Question Answering
Personalized Federated Learning
+2
no code implementations • 3 Oct 2024 • Ziyang Song, Qingcheng Lu, He Zhu, David Buckeridge, Yue Li
In many domains, such as healthcare, time-series data is often irregularly sampled with varying intervals between observations.
no code implementations • 2 Aug 2024 • He Zhu, Junyou Su, Tianle Lun, Yicheng Tao, Wenjia Zhang, Zipei Fan, Guanhua Chen
Instruction fine-tuning stands as a crucial advancement in leveraging large language models (LLMs) for enhanced task performance.
1 code implementation • 25 Jul 2024 • Yue Hou, Xueyuan Chen, He Zhu, Romei Liu, Bowen Shi, Jiaheng Liu, Junran Wu, Ke Xu
SWORD achieves this by employing a self-training strategy to learn new categories and preventing the forgetting of old categories through the joint use of feature prototypes and knowledge distillation.
1 code implementation • 1 Jul 2024 • Zelong Li, Shuyuan Xu, Kai Mei, Wenyue Hua, Balaji Rama, Om Raheja, Hao Wang, He Zhu, Yongfeng Zhang
We believe that the automatic generation and interpretation of workflows in natural language represent a promising paradigm for solving complex tasks, particularly with the rapid development of LLMs.
no code implementations • 4 Jun 2024 • Yuzhou Ji, He Zhu, Junshu Tang, Wuyi Liu, Zhizhong Zhang, Xin Tan, Yuan Xie
The semantically interactive radiance field has always been an appealing task for its potential to facilitate user-friendly and automated real-world 3D scene understanding applications.
no code implementations • 3 Jun 2024 • Ken Deng, Jiaheng Liu, He Zhu, Congnan Liu, Jingxin Li, Jiakai Wang, Peng Zhao, Chenchen Zhang, Yanan Wu, Xueqiao Yin, Yuanxing Zhang, Wenbo Su, Bangyu Xiang, Tiezheng Ge, Bo Zheng
Code completion models have made significant progress in recent years.
1 code implementation • 26 Mar 2024 • He Zhu, Junran Wu, Ruomei Liu, Yue Hou, Ze Yuan, Shangzhe Li, YiCheng Pan, Ke Xu
Existing self-supervised methods in natural language processing (NLP), especially hierarchical text classification (HTC), mainly focus on self-supervised contrastive learning, extremely relying on human-designed augmentation rules to generate contrastive samples, which can potentially corrupt or distort the original information.
Ranked #1 on
Hierarchical Multi-label Classification
on WOS
no code implementations • 29 Feb 2024 • He Zhu, Wenjia Zhang, Nuoxian Huang, Boyang Li, Luyao Niu, Zipei Fan, Tianle Lun, Yicheng Tao, Junyou Su, Zhaoya Gong, Chenyu Fang, Xing Liu
In the field of urban planning, general-purpose large language models often struggle to meet the specific needs of planners.
no code implementations • 15 Feb 2024 • He Zhu, Ren Togo, Takahiro Ogawa, Miki Haseyama
We present a novel prompt-based personalized federated learning (pFL) method to address data heterogeneity and privacy concerns in traditional medical visual question answering (VQA) methods.
Medical Visual Question Answering
Personalized Federated Learning
+2
1 code implementation • 14 Feb 2024 • Ziyang Song, Qincheng Lu, He Zhu, David Buckeridge, Yue Li
Learning time-series representations for discriminative tasks, such as classification and regression, has been a long-standing challenge in the healthcare domain.
1 code implementation • 1 Feb 2024 • Zelong Li, Wenyue Hua, Hao Wang, He Zhu, Yongfeng Zhang
A stack-based LLM plan generation process is then conducted under the supervision of the automaton to ensure that the generated plan satisfies the constraints, making the planning process controllable.
no code implementations • 13 Dec 2023 • Haoyu Guo, He Zhu, Sida Peng, Yuang Wang, Yujun Shen, Ruizhen Hu, Xiaowei Zhou
Experimental results on the ScanNet, ScanNet++ and KITTI-360 datasets demonstrate that our method achieves robust segmentation performance and can generalize across different types of scenes.
no code implementations • 29 Nov 2023 • Ziyang Song, Qincheng Lu, Hao Xu, He Zhu, David L. Buckeridge, Yue Li
However, the development of PTMs on healthcare time-series data is lagging behind. This underscores the limitations of the existing transformer-based architectures, particularly their scalability to handle large-scale time series and ability to capture long-term temporal dependencies.
no code implementations • 27 May 2023 • Dianbo Liu, Samuele Bolotta, He Zhu, Yoshua Bengio, Guillaume Dumas
A strong prediction of this theory is that an agent can use its own AS to also infer the states of other agents' attention and consequently enhance coordination with other agents.
1 code implementation • 24 May 2023 • He Zhu, Chong Zhang, JunJie Huang, Junran Wu, Ke Xu
Hierarchical text classification (HTC) is a challenging subtask of multi-label classification as the labels form a complex hierarchical structure.
Ranked #2 on
Hierarchical Multi-label Classification
on WOS
Hierarchical Multi-label Classification
MUlTI-LABEL-ClASSIFICATION
+2
no code implementations • 5 Apr 2023 • Yuhan Zhang, He Zhu, Shan Yu
In computer vision, contrastive learning is the most advanced unsupervised learning framework.
no code implementations • 9 Mar 2023 • He Zhu, Xihua Li, Xuemin Zhao, Yunbo Cao, Shan Yu
Finally, supervised contrastive learning was conducted on relevance prediction-related downstream tasks, which helped the model to learn the representation of questions effectively.
no code implementations • 8 Mar 2023 • He Zhu, Ren Togo, Takahiro Ogawa, Miki Haseyama
We present a novel multimodal interpretable VQA model that can answer the question more accurately and generate diverse explanations.
7 code implementations • 5 Oct 2022 • Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.
1 code implementation • 23 Aug 2022 • Hanxiong Chen, Yunqi Li, He Zhu, Yongfeng Zhang
Experiments on different datasets show that the adaptive architecture assembled by MANAS outperforms static global architectures.
1 code implementation • 14 Jun 2022 • Zikang Xiong, Joe Eappen, He Zhu, Suresh Jagannathan
We focus our attention on well-trained deterministic and stochastic neural network policies in the context of continuous control benchmarks subject to four well-studied observation space adversarial attacks.
1 code implementation • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2022 • Junwei Liang, He Zhu, Enwei Zhang, Jun Zhang
Distracted driver actions can be dangerous and cause severe accidents.
no code implementations • 27 Dec 2021 • Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu, Yongfeng Zhang
Graphs can represent relational information among entities and graph structures are widely used in many intelligent tasks such as search, recommendation, and question answering.
no code implementations • NeurIPS 2021 • Guofeng Cui, He Zhu
Differentiable programs have recently attracted much interest due to their interpretability, compositionality, and their efficiency to leverage differentiable training.
1 code implementation • 22 Oct 2021 • Ziheng Chen, Fabrizio Silvestri, Jia Wang, He Zhu, Hongshik Ahn, Gabriele Tolomei
However, existing CF generation methods either exploit the internals of specific models or depend on each sample's neighborhood, thus they are hard to generalize for complex models and inefficient for large datasets.
2 code implementations • COLING 2022 • Chong Zhang, He Zhu, Xingyu Peng, Junran Wu, Ke Xu
Inspired by the structural entropy, we construct the coding tree of the graph by minimizing the structural entropy and propose HINT, which aims to make full use of the hierarchical information contained in the text for the task of text classification.
no code implementations • ICLR 2022 • Wenjie Qiu, He Zhu
Our first contribution is a programmatically interpretable RL framework that conducts program architecture search on top of a continuous relaxation of the architecture space defined by programming language grammar rules.
no code implementations • 12 Apr 2021 • He Zhu, Shan Yu
To address this issue, we propose a loss function with intra-class uncertainty following Gaussian distribution.
no code implementations • 31 Dec 2020 • Yichi Zhang, Qingcheng Liao, Lin Yuan, He Zhu, Jiezhen Xing, Jicong Zhang
In this paper, we propose a novel relation-driven collaborative learning model to exploit shared knowledge from non-COVID lesions for annotation-efficient COVID-19 CT lung infection segmentation.
no code implementations • 1 Dec 2020 • Leyu Dai, He Zhu, Dianbo Liu
Patient similarity analysis is important in health care applications.
no code implementations • 23 Nov 2020 • He Zhu, Dianbo Liu
The concept of disinformation is to use fake messages to confuse people in order to protect the real information.
no code implementations • 11 Jun 2020 • Zikang Xiong, Joe Eappen, He Zhu, Suresh Jagannathan
We consider shield-based defenses as a means to improve controller robustness in the face of such perturbations.
no code implementations • 25 Dec 2019 • Jianfei Cui, He Zhu, Hao Deng, Ziwei Chen, Dianbo Liu
Sometimes electrical medical records are restricted and difficult to centralize for machine learning, which could only be trained in distributed manner that involved many institutions in the process.
1 code implementation • 17 Jul 2019 • Xuankang Lin, He Zhu, Roopsha Samanta, Suresh Jagannathan
Our key insight is that we can integrate an optimization-based abstraction refinement loop into the learning process and operate over dynamically constructed partitions of the input space that considers accuracy and safety objectives synergistically.
no code implementations • 16 Jul 2019 • He Zhu, Zikang Xiong, Stephen Magill, Suresh Jagannathan
Rather than enforcing safety by examining and altering the structure of a complex neural network implementation, our technique uses blackbox methods to synthesizes deterministic programs, simpler, more interpretable, approximations of the network that can nonetheless guarantee desired safety properties are preserved, even when the network is deployed in unanticipated or previously unobserved environments.
no code implementations • 15 Mar 2018 • Jiayu Zhou, Fengyi Tang, He Zhu, Ning Nan, Ziheng Zhou
However, one key challenge in distributed data vending is the trade-off dilemma between the effectiveness of data retrieval, and the leakage risk from indexing the data.