Zobrazeno 1 - 10
of 2 285
pro vyhledávání: '"P, Szot"'
Autor:
Szot, Andrew, Mazoure, Bogdan, Attia, Omar, Timofeev, Aleksei, Agrawal, Harsh, Hjelm, Devon, Gan, Zhe, Kira, Zsolt, Toshev, Alexander
We examine the capability of Multimodal Large Language Models (MLLMs) to tackle diverse domains that extend beyond the traditional language and vision tasks these models are typically trained on. Specifically, our focus lies in areas such as Embodied
Externí odkaz:
http://arxiv.org/abs/2412.08442
Autor:
Elawady, Ahmad, Chhablani, Gunjan, Ramrakhya, Ram, Yadav, Karmesh, Batra, Dhruv, Kira, Zsolt, Szot, Andrew
Intelligent embodied agents need to quickly adapt to new scenarios by integrating long histories of experience into decision-making. For instance, a robot in an unfamiliar house initially wouldn't know the locations of objects needed for tasks and mi
Externí odkaz:
http://arxiv.org/abs/2410.02751
Autor:
Yenamandra, Sriram, Ramachandran, Arun, Khanna, Mukul, Yadav, Karmesh, Vakil, Jay, Melnik, Andrew, Büttner, Michael, Harz, Leon, Brown, Lyon, Nandi, Gora Chand, PS, Arjun, Yadav, Gaurav Kumar, Kala, Rahul, Haschke, Robert, Luo, Yang, Zhu, Jinxin, Han, Yansen, Lu, Bingyi, Gu, Xuan, Liu, Qinyuan, Zhao, Yaping, Ye, Qiting, Dou, Chenxiao, Chua, Yansong, Kuzma, Volodymyr, Humennyy, Vladyslav, Partsey, Ruslan, Francis, Jonathan, Chaplot, Devendra Singh, Chhablani, Gunjan, Clegg, Alexander, Gervet, Theophile, Jain, Vidhi, Ramrakhya, Ram, Szot, Andrew, Wang, Austin, Yang, Tsung-Yen, Edsinger, Aaron, Kemp, Charlie, Shah, Binit, Kira, Zsolt, Batra, Dhruv, Mottaghi, Roozbeh, Bisk, Yonatan, Paxton, Chris
In order to develop robots that can effectively serve as versatile and capable home assistants, it is crucial for them to reliably perceive and interact with a wide variety of objects across diverse environments. To this end, we proposed Open Vocabul
Externí odkaz:
http://arxiv.org/abs/2407.06939
We present Reinforcement Learning via Auxiliary Task Distillation (AuxDistill), a new method that enables reinforcement learning (RL) to perform long-horizon robot control problems by distilling behaviors from auxiliary RL tasks. AuxDistill achieves
Externí odkaz:
http://arxiv.org/abs/2406.17168
Multimodal Large Language Models (MLLMs) have demonstrated a wide range of capabilities across many domains, including Embodied AI. In this work, we study how to best ground a MLLM into different embodiments and their associated action spaces, with t
Externí odkaz:
http://arxiv.org/abs/2406.07904
Autor:
Lysak, A., Przeździecka, E., Wierzbicka, A., Jakiela, R., Khosravizadeh, Z., Szot, M., Adhikari, A., Kozanecki, A.
Publikováno v:
Thin Solid Films. 781, 139982 (2023)
In situ Eu-doped {ZnCdO/ZnO}30 multilayer systems were grown on p-type Si-substrates and on quartz substrates by plasma-assisted molecular beam epitaxy. Various Eu concentrations in the samples were achieved by controlling temperature of the europium
Externí odkaz:
http://arxiv.org/abs/2402.10650
Autor:
Szot, Andrew, Schwarzer, Max, Agrawal, Harsh, Mazoure, Bogdan, Talbott, Walter, Metcalf, Katherine, Mackraz, Natalie, Hjelm, Devon, Toshev, Alexander
We show that large language models (LLMs) can be adapted to be generalizable policies for embodied visual tasks. Our approach, called Large LAnguage model Reinforcement Learning Policy (LLaRP), adapts a pre-trained frozen LLM to take as input text in
Externí odkaz:
http://arxiv.org/abs/2310.17722
Autor:
Maslowska, Aneta, Kochanowska, Dominika M., Sulich, Adrian, Domagala, Jaroslaw Z., Dopierala, Marcin, Kochanski, Michal, Szot, Michal, Chrominski, Witold, Mycielski, Andrzej
Publikováno v:
Sensors 24 (2024) 345
This study explores the suitability of semi-insulating compounds, specifically (Cd,Mn)Te and (Cd,Mn)(Te,Se), as materials for room temperature X-ray and gamma-ray detectors. These compounds were grown using the Bridgman method, known for its efficien
Externí odkaz:
http://arxiv.org/abs/2310.17231
Autor:
Puig, Xavier, Undersander, Eric, Szot, Andrew, Cote, Mikael Dallaire, Yang, Tsung-Yen, Partsey, Ruslan, Desai, Ruta, Clegg, Alexander William, Hlavac, Michal, Min, So Yeon, Vondruš, Vladimír, Gervet, Theophile, Berges, Vincent-Pierre, Turner, John M., Maksymets, Oleksandr, Kira, Zsolt, Kalakrishnan, Mrinal, Malik, Jitendra, Chaplot, Devendra Singh, Jain, Unnat, Batra, Dhruv, Rai, Akshara, Mottaghi, Roozbeh
We present Habitat 3.0: a simulation platform for studying collaborative human-robot tasks in home environments. Habitat 3.0 offers contributions across three dimensions: (1) Accurate humanoid simulation: addressing challenges in modeling complex def
Externí odkaz:
http://arxiv.org/abs/2310.13724
Autor:
Wojciech Piątek
Publikováno v:
Ruch Prawniczy, Ekonomiczny i Socjologiczny, Vol 80, Iss 3 (2018)
Externí odkaz:
https://doaj.org/article/ccefdd64a8d24f90baebc80f32f3f59b
