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Binhang Yuan
Researcher at Rice University
Publications - 43
Citations - 481
Binhang Yuan is an academic researcher from Rice University. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 7, co-authored 31 publications receiving 128 citations. Previous affiliations of Binhang Yuan include Fudan University.
Papers
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Journal ArticleDOI
Holistic Evaluation of Language Models
Percy Liang,Rishi Bommasani,Tony Lee,Dimitris Tsipras,Dilara Soylu,Michihiro Yasunaga,Yian Zhang,Deepak Narayanan,Yuhuai Wu,Ananya Kumar,Benjamin Newman,Binhang Yuan,Bobby Yan,Ce Zhang,Christian Cosgrove,Christopher D. Manning,Christopher R'e,Diana Acosta-Navas,Drew A. Hudson,Eric Zelikman,Esin Durmus,Faisal Ladhak,Frieda Rong,Hongyu Ren,Huaxiu Yao,Jue Wang,Keshav Santhanam,Laurel Orr,Lucia Zheng,Byron Rogers,Mirac M. Suzgun,Nathan S. Kim,Neel Guha,Niladri S. Chatterji,Peter Henderson,Qian Huang,Ryan Chi,Michael Xie,Shibani Santurkar,Surya Ganguli,Tatsunori Hashimoto,Thomas Icard,Tianyi Zhang,Vishrav Chaudhary,William Wang,Xuechen Li,Yifan Mai,Yuhui Zhang,Yuta Koreeda +48 more
TL;DR: The Holistic Evaluation of Language Models (HELM) as mentioned in this paper ) is a popular benchmark for language models, with 30 models evaluated on 16 core scenarios and 7 metrics, exposing important trade-offs.
Journal ArticleDOI
Declarative recursive computation on an RDBMS: or, why you should use a database for distributed machine learning
TL;DR: In this article, the authors make a small set of changes to a modern relational database management system (RDBMS) to make it suitable for distributed learning computations, such as adding better support for recursion, and optimization and execution of very large compute plans.
Posted Content
A Federated Learning Framework for Healthcare IoT devices.
Binhang Yuan,Song Ge,Wenhui Xing +2 more
TL;DR: This work proposes an advanced federated learning framework to train deep neural networks, where the network is partitioned and allocated to IoT devices and a centralized server, where most of the training computation is handled by the powerful server.
Proceedings ArticleDOI
Decentralized Training of Foundation Models in Heterogeneous Environments
Binhang Yuan,Yongjun He,Jared Davis,Tianyi Zhang,Tri Dao,Bei Chen,Percy Liang,Christopher Ré,Ce Zhang +8 more
TL;DR: This paper presents the first study of training large foundation models with model parallelism in a decentralized regime over a heterogeneous network, and provides a formal cost model and an efficient evolutionary algorithm to find the optimal allocation strategy.
Posted Content
WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection.
TL;DR: This paper proposes a novel classification-based anomaly detection system for icing detection of the wind turbine blades that effectively combines the deep neural networks and wavelet transformation to identify such failures sequentially across the time.