12 citations · 41 across the 15 of their papers we have counts for
16 papers
Personalized Federated Learning via Amortized Bayesian Meta-Learning
Shiyu Liu, Shaogao Lv, Dun Zeng +3
Federated learning is a decentralized and privacy-preserving technique that enables multiple clients to collaborate with a server to learn a global model without exposing their pri…
Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing
Jinglong Luo, Yehong Zhang, Jiaqi Zhang +4
Gaussian process regression (GPR) is a non-parametric model that has been used in many real-world applications that involve sensitive personal data (e.g., healthcare, finance, etc.…
FedNoisy: Federated Noisy Label Learning Benchmark
Siqi Liang, Jintao Huang, Junyuan Hong +3
Federated learning has gained popularity for distributed learning without aggregating sensitive data from clients. But meanwhile, the distributed and isolated nature of data isolat…
Enabling Intelligent Interactions between an Agent and an LLM: A Reinforcement Learning Approach
Bin Hu, Chenyang Zhao, Pu Zhang +4
Large language models (LLMs) encode a vast amount of world knowledge acquired from massive text datasets. Recent studies have demonstrated that LLMs can assist an embodied agent in…
BadCS: A Backdoor Attack Framework for Code search
Shiyi Qi, Yuanhang Yang, Shuzhzeng Gao +2
With the development of deep learning (DL), DL-based code search models have achieved state-of-the-art performance and have been widely used by developers during software developme…
Multi-task Transformer with Relation-attention and Type-attention for Named Entity Recognition
Ying Mo, Hongyin Tang, Jiahao Liu +5
Named entity recognition (NER) is an important research problem in natural language processing. There are three types of NER tasks, including flat, nested and discontinuous entity…
StoCFL: A Stochastically Clustered Federated Learning Framework for Non-IID Data with Dynamic Client Participation
Dun Zeng, Xiangjing Hu, Shiyu Liu +3
Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices. In real-world federated learning systems, these data…
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy
Yifei Zhang, Dun Zeng, Jinglong Luo +2
Trustworthy artificial intelligence (AI) technology has revolutionized daily life and greatly benefited human society. Among various AI technologies, Federated Learning (FL) stands…
MultiCoder: Multi-Programming-Lingual Pre-Training for Low-Resource Code Completion
Zi Gong, Yinpeng Guo, Pingyi Zhou +3
Code completion is a valuable topic in both academia and industry. Recently, large-scale mono-programming-lingual (MonoPL) pre-training models have been proposed to boost the perfo…
When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods
Zhuo Zhang, Yuanhang Yang, Yong Dai +2
With increasing privacy concerns on data, recent studies have made significant progress using federated learning (FL) on privacy-sensitive natural language processing (NLP) tasks.…
Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling
Yuanhang Yang, Shiyi Qi, Chuanyi Liu +3
Transformer-based models have achieved great success on sentence pair modeling tasks, such as answer selection and natural language inference (NLI). These models generally perform…
A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities
Yaoxian Li, Shiyi Qi, Cuiyun Gao +4
Transformer-based models have demonstrated state-of-the-art performance in many intelligent coding tasks such as code comment generation and code completion. Previous studies show…
Encoded Gradients Aggregation against Gradient Leakage in Federated Learning
Dun Zeng, Shiyu Liu, Siqi Liang +4
Federated learning enables isolated clients to train a shared model collaboratively by aggregating the locally-computed gradient updates. However, privacy information could be leak…
MarkBERT: Marking Word Boundaries Improves Chinese BERT
Linyang Li, Yong Dai, Duyu Tang +3
We present a Chinese BERT model dubbed MarkBERT that uses word information in this work. Existing word-based BERT models regard words as basic units, however, due to the vocabulary…
Source Code Summarization with Structural Relative Position Guided Transformer
Zi Gong, Cuiyun Gao, Yasheng Wang +3
Source code summarization aims at generating concise and clear natural language descriptions for programming languages. Well-written code summaries are beneficial for programmers t…
Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
Zonghang Li, Yihong He, Hongfang Yu +4
Nowadays, the industrial Internet of Things (IIoT) has played an integral role in Industry 4.0 and produced massive amounts of data for industrial intelligence. These data locate o…