Kevin Stone

According to our database, Kevin Stone authored at least 10 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Llama 2: Open Foundation and Fine-Tuned Chat Models.

Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurélien Rodriguez, Robert Stojnic, Sergey Edunov, Thomas Scialom

CoRR, 2023

Modeling Scattering Coefficients using Self-Attentive Complex Polynomials with Image-based Representation.

Andrew Cohen, Weiping Dou, Jiang Zhu, Slawomir Koziel, Peter Renner, Jan-Ove Mattsson, Xiaomeng Yang, Beidi Chen, Kevin Stone, Yuandong Tian

CoRR, 2023

Masked Trajectory Models for Prediction, Representation, and Control.

Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran

Proceedings of the International Conference on Machine Learning, 2023

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction.

Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh James Leather, Yuandong Tian

Proceedings of the International Conference on Machine Learning, 2023

2022

Learned Stereo.

Jeremy Ma, Krishna Shankar, Mark Tjersland, Kevin Stone, Max Bajracharya

Dataset, May, 2022

A Learned Stereo Depth System for Robotic Manipulation in Homes.

Krishna Shankar, Mark Tjersland, Jeremy Ma, Kevin Stone, Max Bajracharya

IEEE Robotics Autom. Lett., 2022

CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation.

Muhammad Zubair Irshad, Thomas Kollar, Michael Laskey, Kevin Stone, Zsolt Kira

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo.

Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan, Mark Tjersland

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data.

Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Michael Laskey, Kevin Stone, Joseph E. Gonzalez, Ken Goldberg

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

A Mobile Manipulation System for One-Shot Teaching of Complex Tasks in Homes.

Max Bajracharya, James Borders, Daniel M. Helmick, Thomas Kollar, Michael Laskey, John Leichty, Jeremy Ma, Umashankar Nagarajan, Akiyoshi Ochiai, Josh Petersen, Krishna Shankar, Kevin Stone, Yutaka Takaoka

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020