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ORCIDAditya Kusupati
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- affiliation: University of Washington, Seattle, WA, USA
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2020 – today
- 2024
[i23]Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, Blair Chen, Daniel Cer, Jeremy R. Cole, Kai Hui, Michael Boratko, Rajvi Kapadia, Wen Ding, Yi Luan, Sai Meher Karthik Duddu, Gustavo Hernández Ábrego, Weiqiang Shi, Nithi Gupta, Aditya Kusupati, Prateek Jain, Siddhartha Reddy Jonnalagadda, Ming-Wei Chang, Iftekhar Naim:
Gecko: Versatile Text Embeddings Distilled from Large Language Models. CoRR abs/2403.20327 (2024)- [i22]Ethan Shen, Alan Fan, Sarah M. Pratt, Jae Sung Park, Matthew Wallingford, Sham M. Kakade, Ari Holtzman, Ranjay Krishna, Ali Farhadi, Aditya Kusupati:
Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass. CoRR abs/2405.18400 (2024) - [i21]Gagan Jain, Nidhi Hegde, Aditya Kusupati, Arsha Nagrani, Shyamal Buch, Prateek Jain, Anurag Arnab, Sujoy Paul:
Mixture of Nested Experts: Adaptive Processing of Visual Tokens. CoRR abs/2407.19985 (2024) - 2023
- [j2]Matthew Wallingford, Aditya Kusupati, Keivan Alizadeh-Vahid, Aaron Walsman, Aniruddha Kembhavi, Ali Farhadi:
FLUID: A Unified Evaluation Framework for Flexible Sequential Data. Trans. Mach. Learn. Res. 2023 (2023) - [c16]Mohammadreza Salehi, Sachin Mehta, Aditya Kusupati, Ali Farhadi, Hannaneh Hajishirzi:
SHARCS: Efficient Transformers Through Routing with Dynamic Width Sub-networks. EMNLP (Findings) 2023: 10519-10532 - [c15]Matthew Wallingford, Aditya Kusupati, Alex Fang, Vivek Ramanujan, Aniruddha Kembhavi, Roozbeh Mottaghi, Ali Farhadi:
Neural Radiance Field Codebooks. ICLR 2023 - [c14]Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, Eli VanderBilt, Aniruddha Kembhavi, Carl Vondrick, Georgia Gkioxari, Kiana Ehsani, Ludwig Schmidt, Ali Farhadi:
Objaverse-XL: A Universe of 10M+ 3D Objects. NeurIPS 2023 - [c13]Sneha Kudugunta, Isaac Caswell, Biao Zhang, Xavier Garcia, Derrick Xin, Aditya Kusupati, Romi Stella, Ankur Bapna, Orhan Firat:
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset. NeurIPS 2023 - [c12]Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao, Sham M. Kakade, Prateek Jain, Ali Farhadi:
AdANNS: A Framework for Adaptive Semantic Search. NeurIPS 2023 - [c11]Matthew Wallingford, Vivek Ramanujan, Alex Fang, Aditya Kusupati, Roozbeh Mottaghi, Aniruddha Kembhavi, Ludwig Schmidt, Ali Farhadi:
Neural Priming for Sample-Efficient Adaptation. NeurIPS 2023 - [i20]Matthew Wallingford, Aditya Kusupati, Alex Fang, Vivek Ramanujan, Aniruddha Kembhavi, Roozbeh Mottaghi, Ali Farhadi:
Neural Radiance Field Codebooks. CoRR abs/2301.04101 (2023) - [i19]Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao, Sham M. Kakade, Prateek Jain, Ali Farhadi:
AdANNS: A Framework for Adaptive Semantic Search. CoRR abs/2305.19435 (2023) - [i18]Matthew Wallingford, Vivek Ramanujan, Alex Fang, Aditya Kusupati, Roozbeh Mottaghi, Aniruddha Kembhavi, Ludwig Schmidt, Ali Farhadi:
Neural Priming for Sample-Efficient Adaptation. CoRR abs/2306.10191 (2023) - [i17]Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, Eli VanderBilt, Aniruddha Kembhavi, Carl Vondrick, Georgia Gkioxari, Kiana Ehsani, Ludwig Schmidt, Ali Farhadi:
Objaverse-XL: A Universe of 10M+ 3D Objects. CoRR abs/2307.05663 (2023) - [i16]Sneha Kudugunta, Isaac Caswell, Biao Zhang, Xavier Garcia, Christopher A. Choquette-Choo, Katherine Lee, Derrick Xin, Aditya Kusupati, Romi Stella, Ankur Bapna, Orhan Firat:
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset. CoRR abs/2309.04662 (2023) - [i15]Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S. Dhillon, Yulia Tsvetkov, Hannaneh Hajishirzi, Sham M. Kakade, Ali Farhadi, Prateek Jain:
MatFormer: Nested Transformer for Elastic Inference. CoRR abs/2310.07707 (2023) - [i14]Ramnath Kumar, Anshul Mittal, Nilesh Gupta, Aditya Kusupati, Inderjit S. Dhillon, Prateek Jain:
EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval. CoRR abs/2310.08891 (2023) - [i13]Mohammadreza Salehi, Sachin Mehta, Aditya Kusupati, Ali Farhadi, Hannaneh Hajishirzi:
SHARCS: Efficient Transformers through Routing with Dynamic Width Sub-networks. CoRR abs/2310.12126 (2023) - [i12]Ethan Shen, Ali Farhadi, Aditya Kusupati:
Are "Hierarchical" Visual Representations Hierarchical? CoRR abs/2311.05784 (2023) - 2022
- [c10]Dhruv Jain, Khoa Huynh Anh Nguyen, Steven M. Goodman, Rachel Grossman-Kahn, Hung Ngo, Aditya Kusupati, Ruofei Du, Alex Olwal, Leah Findlater, Jon E. Froehlich
:
ProtoSound: A Personalized and Scalable Sound Recognition System for Deaf and Hard-of-Hearing Users. CHI 2022: 305:1-305:16 - [c9]Rowan Zellers, Jiasen Lu, Ximing Lu, Youngjae Yu, Yanpeng Zhao, Mohammadreza Salehi, Aditya Kusupati, Jack Hessel, Ali Farhadi, Yejin Choi:
MERLOT RESERVE: Neural Script Knowledge through Vision and Language and Sound. CVPR 2022: 16354-16366 - [c8]Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham M. Kakade, Prateek Jain, Ali Farhadi:
Matryoshka Representation Learning. NeurIPS 2022 - [i11]Rowan Zellers, Jiasen Lu, Ximing Lu, Youngjae Yu, Yanpeng Zhao, Mohammadreza Salehi, Aditya Kusupati, Jack Hessel, Ali Farhadi, Yejin Choi:
MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound. CoRR abs/2201.02639 (2022) - [i10]Dhruv Jain, Khoa Huynh Anh Nguyen, Steven Goodman, Rachel Grossman-Kahn, Hung Ngo, Aditya Kusupati, Ruofei Du, Alex Olwal, Leah Findlater, Jon E. Froehlich:
ProtoSound: A Personalized and Scalable Sound Recognition System for Deaf and Hard-of-Hearing Users. CoRR abs/2202.11134 (2022) - [i9]Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham M. Kakade, Prateek Jain, Ali Farhadi:
Matryoshka Representations for Adaptive Deployment. CoRR abs/2205.13147 (2022) - 2021
- [j1]Dhrubojyoti Roy, Sangeeta Srivastava, Aditya Kusupati, Pranshu Jain, Manik Varma, Anish Arora:
One Size Does Not Fit All: Multi-scale, Cascaded RNNs for Radar Classification. ACM Trans. Sens. Networks 17(2): 12:1-12:27 (2021) - [c7]Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi:
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. NeurIPS 2021: 23900-23913 - [i8]Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi:
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. CoRR abs/2106.01487 (2021) - [i7]Ivan Evtimov, Ian Covert, Aditya Kusupati, Tadayoshi Kohno:
Disrupting Model Training with Adversarial Shortcuts. CoRR abs/2106.06654 (2021) - 2020
- [c6]Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi:
Soft Threshold Weight Reparameterization for Learnable Sparsity. ICML 2020: 5544-5555 - [c5]Oindrila Saha, Aditya Kusupati, Harsha Vardhan Simhadri, Manik Varma, Prateek Jain:
RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference. NeurIPS 2020 - [c4]Yashoteja Prabhu, Aditya Kusupati, Nilesh Gupta, Manik Varma:
Extreme Regression for Dynamic Search Advertising. WSDM 2020: 456-464 - [i6]Yashoteja Prabhu, Aditya Kusupati, Nilesh Gupta, Manik Varma:
Extreme Regression for Dynamic Search Advertising. CoRR abs/2001.05228 (2020) - [i5]Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi:
Soft Threshold Weight Reparameterization for Learnable Sparsity. CoRR abs/2002.03231 (2020) - [i4]Oindrila Saha, Aditya Kusupati, Harsha Vardhan Simhadri, Manik Varma, Prateek Jain:
RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference. CoRR abs/2002.11921 (2020) - [i3]Matthew Wallingford, Aditya Kusupati, Keivan Alizadeh-Vahid, Aaron Walsman, Aniruddha Kembhavi, Ali Farhadi:
In the Wild: From ML Models to Pragmatic ML Systems. CoRR abs/2007.02519 (2020)
2010 – 2019
- 2019
- [c3]Dhrubojyoti Roy, Sangeeta Srivastava, Aditya Kusupati, Pranshu Jain, Manik Varma, Anish Arora:
One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification. BuildSys@SenSys 2019: 1-10 - [c2]Dhrubojyoti Roy, Sangeeta Srivastava, Pranshu Jain, Aditya Kusupati, Manik Varma, Anish Arora:
Lightweight, Deep RNNs for Radar Classification. BuildSys@SenSys 2019: 360-361 - [i2]Aditya Kusupati, Manish Singh, Kush Bhatia, Ashish Kumar, Prateek Jain, Manik Varma:
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network. CoRR abs/1901.02358 (2019) - [i1]Dhrubojyoti Roy, Sangeeta Srivastava, Aditya Kusupati, Pranshu Jain, Manik Varma, Anish Arora:
One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification. CoRR abs/1909.03082 (2019) - 2018
- [c1]Aditya Kusupati, Manish Singh, Kush Bhatia, Ashish Kumar, Prateek Jain, Manik Varma:
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network. NeurIPS 2018: 9031-9042
Coauthor Index
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last updated on 2024-08-25 19:11 CEST by the dblp team
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