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Sanjiv Kumar

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Metric-aware LLM inference

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Mar 07, 2024
Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar

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HiRE: High Recall Approximate Top-$k$ Estimation for Efficient LLM Inference

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Feb 14, 2024
Yashas Samaga B L, Varun Yerram, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli

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Tandem Transformers for Inference Efficient LLMs

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Feb 13, 2024
Aishwarya P S, Pranav Ajit Nair, Yashas Samaga, Toby Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli

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Efficient Stagewise Pretraining via Progressive Subnetworks

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Feb 08, 2024
Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank Reddi, Satyen Kale, Sanjiv Kumar

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SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection

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Jan 24, 2024
Ke Ye, Heinrich Jiang, Afshin Rostamizadeh, Ayan Chakrabarti, Giulia DeSalvo, Jean-François Kagy, Lazaros Karydas, Gui Citovsky, Sanjiv Kumar

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A Weighted K-Center Algorithm for Data Subset Selection

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Dec 17, 2023
Srikumar Ramalingam, Pranjal Awasthi, Sanjiv Kumar

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ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent

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Dec 15, 2023
Renat Aksitov, Sobhan Miryoosefi, Zonglin Li, Daliang Li, Sheila Babayan, Kavya Kopparapu, Zachary Fisher, Ruiqi Guo, Sushant Prakash, Pranesh Srinivasan, Manzil Zaheer, Felix Yu, Sanjiv Kumar

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It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models

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Oct 13, 2023
Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar

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DistillSpec: Improving Speculative Decoding via Knowledge Distillation

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Oct 12, 2023
Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal

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What do larger image classifiers memorise?

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Oct 09, 2023
Michal Lukasik, Vaishnavh Nagarajan, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar

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