Matthew Bennice

According to our database, Matthew Bennice authored at least 8 papers between 2022 and 2024.

Collaborative distances:

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

2024

VADER: Visual Affordance Detection and Error Recovery for Multi Robot Human Collaboration.

Michael Ahn, Montserrat Gonzalez Arenas, Matthew Bennice, Noah Brown, Christine Chan, Byron David, Anthony G. Francis, Gavin Gonzalez, Rainer Hessmer, Tomas Jackson, Nikhil J. Joshi, Daniel Lam, Tsang-Wei Edward Lee, Alex Luong, Sharath Maddineni, Harsh Patel, Jodilyn Peralta, Jornell Quiambao, Diego Reyes, Rosario Jauregui Ruano, Dorsa Sadigh, Pannag Sanketi, Leila Takayama, Pavel Vodenski, Fei Xia

CoRR, 2024

Interactive Multi-Robot Flocking with Gesture Responsiveness and Musical Accompaniment.

Catie Cuan, Kyle Jeffrey, Kim Kleiven, Adrian Li, Emre Fisher, Matt Harrison, Benjie Holson, Allison M. Okamura, Matthew Bennice

CoRR, 2024

Learning to Learn Faster from Human Feedback with Language Model Predictive Control.

Jacky Liang, Fei Xia, Wenhao Yu, Andy Zeng, Montserrat Gonzalez Arenas, Maria Attarian, Maria Bauzá, Matthew Bennice, Alex Bewley, Adil Dostmohamed, Chuyuan Kelly Fu, Nimrod Gileadi, Marissa Giustina, Keerthana Gopalakrishnan, Leonard Hasenclever, Jan Humplik, Jasmine Hsu, Nikhil J. Joshi, Ben Jyenis, J. Chase Kew, Sean Kirmani, Tsang-Wei Edward Lee, Kuang-Huei Lee, Assaf Hurwitz Michaely, Joss Moore, Ken Oslund, Dushyant Rao, Allen Z. Ren, Baruch Tabanpour, Quan Vuong, Ayzaan Wahid, Ted Xiao, Ying Xu, Vincent Zhuang, Peng Xu, Erik Frey, Ken Caluwaerts, Tingnan Zhang, Brian Ichter, Jonathan Tompson, Leila Takayama, Vincent Vanhoucke, Izhak Shafran, Maja J. Mataric, Dorsa Sadigh, Nicolas Heess, Kanishka Rao, Nik Stewart, Jie Tan, Carolina Parada

CoRR, 2024

2023

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators.

Alexander Herzog, Kanishka Rao, Karol Hausman, Yao Lu, Paul Wohlhart, Mengyuan Yan, Jessica Lin, Montserrat Gonzalez Arenas, Ted Xiao, Daniel Kappler, Daniel Ho, Jarek Rettinghouse, Yevgen Chebotar, Kuang-Huei Lee, Keerthana Gopalakrishnan, Ryan Julian, Adrian Li, Chuyuan Kelly Fu, Bob Wei, Sangeetha Ramesh, Khem Holden, Kim Kleiven, David Rendleman, Sean Kirmani, Jeff Bingham, Jonathan Weisz, Ying Xu, Wenlong Lu, Matthew Bennice, Cody Fong, David Do, Jessica Lam, Yunfei Bai, Benjie Holson, Michael Quinlan, Noah Brown, Mrinal Kalakrishnan, Julian Ibarz, Peter Pastor, Sergey Levine

CoRR, 2023

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators.

Alexander Herzog, Kanishka Rao, Karol Hausman, Yao Lu, Paul Wohlhart, Mengyuan Yan, Jessica Lin, Montserrat Gonzalez Arenas, Ted Xiao, Daniel Kappler, Daniel Ho, Jarek Rettinghouse, Yevgen Chebotar, Kuang-Huei Lee, Keerthana Gopalakrishnan, Ryan Julian, Adrian Li, Chuyuan Fu, Bob Wei, Sangeetha Ramesh, Khem Holden, Kim Kleiven, David J. Rendleman, Sean Kirmani, Jeffrey Bingham, Jonathan Weisz, Ying Xu, Wenlong Lu, Matthew Bennice, Cody Fong, David Do, Jessica Lam, Yunfei Bai, Benjie Holson, Michael Quinlan, Noah Brown, Mrinal Kalakrishnan, Julian Ibarz, Peter Pastor, Sergey Levine

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Practical Visual Deep Imitation Learning via Task-Level Domain Consistency.

Mohi Khansari, Daniel Ho, Yuqing Du, Armando Fuentes, Matthew Bennice, Nicolas Sievers, Sean Kirmani, Yunfei Bai, Eric Jang

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Jump-Start Reinforcement Learning.

Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman

Proceedings of the International Conference on Machine Learning, 2023

2022

Practical Imitation Learning in the Real World via Task Consistency Loss.

Mohi Khansari, Daniel Ho, Yuqing Du, Armando Fuentes, Matthew Bennice, Nicolas Sievers, Sean Kirmani, Yunfei Bai, Eric Jang

CoRR, 2022