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Large Language Models with Controllable Working Memory


Nov 09, 2022
Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix Yu, Sanjiv Kumar


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Preserving In-Context Learning ability in Large Language Model Fine-tuning


Nov 01, 2022
Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit S Dhillon, Sanjiv Kumar


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Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers


Oct 12, 2022
Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix Chern, Felix Yu, Ruiqi Guo, Sanjiv Kumar


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FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning


Jul 20, 2022
Yuanhao Xiong, Ruochen Wang, Minhao Cheng, Felix Yu, Cho-Jui Hsieh


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Correlated quantization for distributed mean estimation and optimization


Mar 09, 2022
Ananda Theertha Suresh, Ziteng Sun, Jae Hun Ro, Felix Yu


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HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation


Oct 28, 2021
Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh, Felix Yu, Gang Wang


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InFillmore: Neural Frame Lexicalization for Narrative Text Infilling


Mar 08, 2021
Jiefu Ou, Nathaniel Weir, Anton Belyy, Felix Yu, Benjamin Van Durme


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Modifying Memories in Transformer Models


Dec 01, 2020
Chen Zhu, Ankit Singh Rawat, Manzil Zaheer, Srinadh Bhojanapalli, Daliang Li, Felix Yu, Sanjiv Kumar


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Semantic Label Smoothing for Sequence to Sequence Problems


Oct 15, 2020
Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix Yu, Sanjiv Kumar


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Learning discrete distributions: user vs item-level privacy


Jul 28, 2020
Yuhan Liu, Ananda Theertha Suresh, Felix Yu, Sanjiv Kumar, Michael Riley

* 36 pages 

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