Chaoyang He - RankMe

72 papers A* 9A 1B 1Misc 1Journal 54Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bridging the Safety Gap: A Guardrail Pipeline for Trustworthy LLM Inferences. CoRR Shanshan Han, Salman Avestimehr, Chaoyang He
2025	J	`jnl`	CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency. CoRR Jiacheng Guo, Suozhi Huang, Zixin Yao, Yifan Zhang, Yifu Lu, Jiashuo Liu, Zihao Li, Nicholas Deng, Qixin Xiao, Jia Tian, Kanghong Zhan, Tianyi Li, Xiaochen Liu, Jason Ge, Chaoyang He, Kaixuan Huang, Lin Yang, Wenhao Huang, Mengdi Wang
2025	J	`jnl`	Improving Single-round Active Adaptation: A Prediction Variability Perspective. Trans. Mach. Learn. Res. Xiaoyang Wang, Yibo Jacky Zhang, Olawale Elijah Salaudeen, Mingyuan Wu, Hongpeng Guo, Chaoyang He, Klara Nahrstedt, Sanmi Koyejo
2025	J	`jnl`	Toward Super Agent System with Hybrid AI Routers. CoRR Yuhang Yao, Haixin Wang, Yibo Chen, Jiawen Wang, Min Chang Jordan Ren, Bosheng Ding, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	Alopex: A Computational Framework for Enabling On-Device Function Calls with LLMs. CoRR Yide Ran, Zhaozhuo Xu, Yuhang Yao, Zijian Hu, Shanshan Han, Han Jin, Alay Dilipbhai Shah, Jipeng Zhang, Dimitris Stripelis, Tong Zhang, Salman Avestimehr, Chaoyang He
2024	A*	`conf`	FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs. KDD Shanshan Han, Baturalp Buyukates, Zijian Hu, Han Jin, Weizhao Jin, Lichao Sun, Xiaoyang Wang, Wenxuan Wu, Chulin Xie, Yuhang Yao, Kai Zhang, Qifan Zhang, Yuhui Zhang, Carlee Joe-Wong, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	Fox-1 Technical Report. CoRR Zijian Hu, Jipeng Zhang, Rui Pan, Zhaozhuo Xu, Shanshan Han, Han Jin, Alay Dilipbhai Shah, Dimitris Stripelis, Yuhang Yao, Salman Avestimehr, Chaoyang He, Tong Zhang
2024	J	`jnl`	LLM Multi-Agent Systems: Challenges and Open Problems. CoRR Shanshan Han, Qifan Zhang, Yuhang Yao, Weizhao Jin, Zhaozhuo Xu, Chaoyang He
2024	J	`jnl`	PolyRouter: A Multi-LLM Querying System. CoRR Dimitris Stripelis, Zijian Hu, Jipeng Zhang, Zhaozhuo Xu, Alay Dilipbhai Shah, Han Jin, Yuhang Yao, Salman Avestimehr, Chaoyang He
2024	—	`conf`	ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency. EMNLP (Industry Track) Yuhang Yao, Han Jin, Alay Dilipbhai Shah, Shanshan Han, Zijian Hu, Dimitris Stripelis, Yide Ran, Zhaozhuo Xu, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency. CoRR Yuhang Yao, Han Jin, Alay Dilipbhai Shah, Shanshan Han, Zijian Hu, Yide Ran, Dimitris Stripelis, Zhaozhuo Xu, Salman Avestimehr, Chaoyang He
2024	—	`conf`	TensorOpera Router: A Multi-Model Router for Efficient LLM Inference. EMNLP (Industry Track) Dimitris Stripelis, Zhaozhuo Xu, Zijian Hu, Alay Dilipbhai Shah, Han Jin, Yuhang Yao, Jipeng Zhang, Tong Zhang, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	TorchOpera: A Compound AI System for LLM Safety. CoRR Shanshan Han, Yuhang Yao, Zijian Hu, Dimitris Stripelis, Zhaozhuo Xu, Chaoyang He
2023	A*	`conf`	A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. NeurIPS Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
2023	J	`jnl`	A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. CoRR Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
2023	J	`jnl`	Accelerated Distributed Approximate Newton Method. IEEE Trans. Neural Networks Learn. Syst. Haishan Ye, Chaoyang He, Xiangyu Chang
2023	J	`jnl`	Achieving small-batch accuracy with large-batch scalability via Hessian-aware learning rate adjustment. Neural Networks Sunwoo Lee, Chaoyang He, Salman Avestimehr
2023	J	`jnl`	Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution. IEEE Trans. Circuits Syst. Video Technol. Han Huang, Li Shen, Chaoyang He, Weisheng Dong, Wei Liu
2023	J	`jnl`	Distributed Architecture Search Over Heterogeneous Distributions. Trans. Mach. Learn. Res. Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr
2023	J	`jnl`	Don't Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory. CoRR Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
2023	A*	`conf`	FairFed: Enabling Group Fairness in Federated Learning. AAAI Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Amir Salman Avestimehr
2023	J	`jnl`	FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training. CoRR Zhenheng Tang, Xiaowen Chu, Ryan Yide Ran, Sunwoo Lee, Shaohuai Shi, Yonggang Zhang, Yuxin Wang, Alex Qiaozhong Liang, Salman Avestimehr, Chaoyang He
2023	J	`jnl`	FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System. CoRR Weizhao Jin, Yuhang Yao, Shanshan Han, Carlee Joe-Wong, Srivatsan Ravi, Salman Avestimehr, Chaoyang He
2023	J	`jnl`	FedMLSecurity: A Benchmark for Attacks and Defenses in Federated Learning and LLMs. CoRR Shanshan Han, Baturalp Buyukates, Zijian Hu, Han Jin, Weizhao Jin, Lichao Sun, Xiaoyang Wang, Chulin Xie, Kai Zhang, Qifan Zhang, Yuhui Zhang, Chaoyang He, Salman Avestimehr
2023	J	`jnl`	Federated Analytics: A survey. CoRR Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Shanshan Han, Shantanu Sharma, Chaoyang He, Sharad Mehrotra, Salman Avestimehr
2023	J	`jnl`	Kick Bad Guys Out! Zero-Knowledge-Proof-Based Anomaly Detection in Federated Learning. CoRR Shanshan Han, Wenxuan Wu, Baturalp Buyukates, Weizhao Jin, Yuhang Yao, Qifan Zhang, Salman Avestimehr, Chaoyang He
2023	J	`jnl`	L-BGNN: Layerwise Trained Bipartite Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Tian Xie, Chaoyang He, Xiang Ren, Cyrus Shahabi, C.-C. Jay Kuo
2023	J	`jnl`	Partial model averaging in Federated Learning: Performance guarantees and benefits. Neurocomputing Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr
2023	—	`conf`	Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain. DAPPS Baturalp Buyukates, Chaoyang He, Shanshan Han, Zhiyong Fang, Yupeng Zhang, Jieyi Long, Ali Farahanchi, Salman Avestimehr
2023	J	`jnl`	Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain. CoRR Baturalp Buyukates, Chaoyang He, Shanshan Han, Zhiyong Fang, Yupeng Zhang, Jieyi Long, Ali Farahanchi, Salman Avestimehr
2023	—	`conf`	PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. MLSys Shen Li, Pritam Damania, Luca Wehrstedt, Rohan Varma, Omkar Salpekar, Pavel Belevich, Howard Huang, Yanli Zhao, Lucas Hosseini, Wanchao Liang, Hongyi Jia, Shihao Xu, Satendra Gera, Alisson G. Azzolini, Guoqiang Jerry Chen, Zachary DeVito, Chaoyang He, Amir Ziashahabi, Alban Desmaison, Edward Z. Yang, Gregory Chanan, Brian Vaughan, Manoj Krishnan, Joseph S. Spisak, Salman Avestimehr, Soumith Chintala
2022	A*	`conf`	FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. NeurIPS Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux
2022	J	`jnl`	FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. CoRR Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux
2022	—	`conf`	FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks. NAACL-HLT (Findings) Bill Yuchen Lin, Chaoyang He, Zihang Ze, Hulin Wang, Yufen Hua, Christophe Dupuy, Rahul Gupta, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr
2022	J	`jnl`	Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities. IEEE Internet Things Mag. Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, Amir Salman Avestimehr
2022	J	`jnl`	Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits. CoRR Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr
2022	J	`jnl`	SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing. CoRR Chaoyang He, Shuai Zheng, Aston Zhang, George Karypis, Trishul Chilimbi, Mahdi Soltanolkotabi, Salman Avestimehr
2022	A*	`conf`	SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data. AAAI Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr
2022	A	`conf`	The 1st International Workshop on Federated Learning with Graph Data (FedGraph). CIKM Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr
2021	J	`jnl`	A Field Guide to Federated Optimization. CoRR Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
2021	J	`jnl`	Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
2021	J	`jnl`	AutoCTS: Automated Correlated Time Series Forecasting - Extended Version. CoRR Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, Christian S. Jensen
2021	J	`jnl`	AutoCTS: Automated Correlated Time Series Forecasting. Proc. VLDB Endow. Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, Christian S. Jensen
2021	J	`jnl`	FairFed: Enabling Group Fairness in Federated Learning. CoRR Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Salman Avestimehr
2021	J	`jnl`	FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks. CoRR Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang, Di Fan, Adarshan Naiynar Sivashunmugam, Keerti Bhogaraju, Mita Shimpi, Li Shen, Xiaowen Chu, Mahdi Soltanolkotabi, Salman Avestimehr
2021	J	`jnl`	FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks. CoRR Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram, Salman Avestimehr
2021	J	`jnl`	FedNLP: A Research Platform for Federated Learning in Natural Language Processing. CoRR Bill Yuchen Lin, Chaoyang He, Zihang Zeng, Hulin Wang, Yufen Huang, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr
2021	Misc	`conf`	Federated Learning for Internet of Things. SenSys Tuo Zhang, Chaoyang He, Tianhao Ma, Lei Gao, Mark Ma, Salman Avestimehr
2021	J	`jnl`	Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection. CoRR Tuo Zhang, Chaoyang He, Tianhao Ma, Mark Ma, Salman Avestimehr
2021	J	`jnl`	Federated Learning for Internet of Things: Applications, Challenges, and Opportunities. CoRR Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, Salman Avestimehr
2021	J	`jnl`	Layer-wise Adaptive Model Aggregation for Scalable Federated Learning. CoRR Sunwoo Lee, Tuo Zhang, Chaoyang He, Salman Avestimehr
2021	J	`jnl`	LightSecAgg: Rethinking Secure Aggregation in Federated Learning. CoRR Chien-Sheng Yang, Jinhyun So, Chaoyang He, Songze Li, Qian Yu, Salman Avestimehr
2021	J	`jnl`	Lightweight Image Super-Resolution with Hierarchical and Differentiable Neural Architecture Search. CoRR Han Huang, Li Shen, Chaoyang He, Weisheng Dong, Haozhi Huang, Guangming Shi
2021	A*	`conf`	MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge. NeurIPS Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, Siyue Wang, Minghai Qin, Bin Ren, Yanzhi Wang, Sijia Liu, Xue Lin
2021	J	`jnl`	MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge. CoRR Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, Siyue Wang, Minghai Qin, Bin Ren, Yanzhi Wang, Sijia Liu, Xue Lin
2021	A*	`conf`	PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models. ICML Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
2021	J	`jnl`	PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers. CoRR Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
2021	J	`jnl`	SPIDER: Searching Personalized Neural Architecture for Federated Learning. CoRR Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr
2021	J	`jnl`	SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision. CoRR Chaoyang He, Zhengyu Yang, Erum Mushtaq, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr
2021	J	`jnl`	SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks. CoRR Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr
2020	J	`jnl`	FedML: A Research Library and Benchmark for Federated Machine Learning. CoRR Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr
2020	J	`jnl`	FedNAS: Federated Deep Learning via Neural Architecture Search. CoRR Chaoyang He, Murali Annavaram, Salman Avestimehr
2020	J	`jnl`	Group Knowledge Transfer: Collaborative Training of Large CNNs on the Edge. CoRR Chaoyang He, Murali Annavaram, Salman Avestimehr
2020	A*	`conf`	Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge. NeurIPS Chaoyang He, Murali Annavaram, Salman Avestimehr
2020	A*	`conf`	MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. CVPR Chaoyang He, Haishan Ye, Li Shen, Tong Zhang
2020	J	`jnl`	MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. CoRR Chaoyang He, Haishan Ye, Li Shen, Tong Zhang
2019	—	`conf`	ADMSv2: A Modern Architecture for Transportation Data Management and Analysis. ARIC@SIGSPATIAL Chrysovalantis Anastasiou, Jianfa Lin, Chaoyang He, Yao-Yi Chiang, Cyrus Shahabi
2019	J	`jnl`	Advances and Open Problems in Federated Learning. CoRR Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
2019	J	`jnl`	Adversarial Representation Learning on Large-Scale Bipartite Graphs. CoRR Chaoyang He, Tian Xie, Yu Rong, Wen-bing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi
2019	J	`jnl`	Central Server Free Federated Learning over Single-sided Trust Social Networks. CoRR Chaoyang He, Conghui Tan, Hanlin Tang, Shuang Qiu, Ji Liu
2019	B	`conf`	Collecting Indicators of Compromise from Unstructured Text of Cybersecurity Articles using Neural-Based Sequence Labelling. IJCNN Zi Long, Lianzhi Tan, Shengping Zhou, Chaoyang He, Xin Liu
2019	J	`jnl`	Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps. CoRR Chaoyang He, Ming Li