Zobrazeno 1 - 10
of 2 422
pro vyhledávání: '"P. Karnik"'
Autor:
Karnik, Sathwik, Hong, Zhang-Wei, Abhangi, Nishant, Lin, Yen-Chen, Wang, Tsun-Hsuan, Agrawal, Pulkit
Language-conditioned robot models (i.e., robotic foundation models) enable robots to perform a wide range of tasks based on natural language instructions. Despite strong performance on existing benchmarks, evaluating the safety and effectiveness of t
Externí odkaz:
http://arxiv.org/abs/2411.18676
We provide a rigorous analysis of implicit regularization in an overparametrized tensor factorization problem beyond the lazy training regime. For matrix factorization problems, this phenomenon has been studied in a number of works. A particular chal
Externí odkaz:
http://arxiv.org/abs/2410.16247
Autor:
Idnay, Betina, Xu, Zihan, Adams, William G., Adibuzzaman, Mohammad, Anderson, Nicholas R., Bahroos, Neil, Bell, Douglas S., Bumgardner, Cody, Campion, Thomas, Castro, Mario, Cimino, James J., Cohen, I. Glenn, Dorr, David, Elkin, Peter L, Fan, Jungwei W., Ferris, Todd, Foran, David J., Hanauer, David, Hogarth, Mike, Huang, Kun, Kalpathy-Cramer, Jayashree, Kandpal, Manoj, Karnik, Niranjan S., Katoch, Avnish, Lai, Albert M., Lambert, Christophe G., Li, Lang, Lindsell, Christopher, Liu, Jinze, Lu, Zhiyong, Luo, Yuan, McGarvey, Peter, Mendonca, Eneida A., Mirhaji, Parsa, Murphy, Shawn, Osborne, John D., Paschalidis, Ioannis C., Harris, Paul A., Prior, Fred, Shaheen, Nicholas J., Shara, Nawar, Sim, Ida, Tachinardi, Umberto, Waitman, Lemuel R., Wright, Rosalind J., Zai, Adrian H., Zheng, Kai, Lee, Sandra Soo-Jin, Malin, Bradley A., Natarajan, Karthik, Price II, W. Nicholson, Zhang, Rui, Zhang, Yiye, Xu, Hua, Bian, Jiang, Weng, Chunhua, Peng, Yifan
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the Clinical and Translational Science Award (CTSA) P
Externí odkaz:
http://arxiv.org/abs/2410.12793
This document presents the Center for Robot Assisted Search And Rescue - Uncrewed Aerial Systems - Disaster Response Overhead Inspection Dataset (CRASAR-U-DROIDs) for building damage assessment and spatial alignment collected from small uncrewed aeri
Externí odkaz:
http://arxiv.org/abs/2407.17673
Autor:
Cai, Ziqiang, Zhang, Xianzhe, Karnik, Tushar Sanjay, Xu, Yihao, Kim, Tae Yoon, Hu, Juejun, Liu, Yongmin
Metasurfaces have become one of the most prominent research topics in the field of optics owing to their unprecedented properties and novel applications on an ultrathin platform. By combining graphene with metasurfaces, electrical tunable functions c
Externí odkaz:
http://arxiv.org/abs/2407.07343
Autor:
Schumacher, Dan, Haji, Fatemeh, Grey, Tara, Bandlamudi, Niharika, Karnik, Nupoor, Kumar, Gagana Uday, Chiang, Jason Cho-Yu, Rad, Paul, Vishwamitra, Nishant, Rios, Anthony
Large language models (LLMs) often struggle with temporal reasoning, crucial for tasks like historical event analysis and time-sensitive information retrieval. Despite advancements, state-of-the-art models falter in handling temporal information, esp
Externí odkaz:
http://arxiv.org/abs/2406.19538
Various pose estimation and tracking problems in robotics can be decomposed into a correspondence estimation problem (often computed using a deep network) followed by a weighted least squares optimization problem to solve for the poses. Recent work h
Externí odkaz:
http://arxiv.org/abs/2406.07785
Autor:
Manzini, Thomas, Perali, Priyankari, Karnik, Raisa, Godbole, Mihir, Abdullah, Hasnat, Murphy, Robin
This work presents the first quantitative study of alignment errors between small uncrewed aerial systems (sUAS) geospatial imagery and a priori building polygons and finds that alignment errors are non-uniform and irregular. The work also introduces
Externí odkaz:
http://arxiv.org/abs/2405.06593
As factories continue to evolve into collaborative spaces with multiple robots working together with human supervisors in the loop, ensuring safety for all actors involved becomes critical. Currently, laser-based light curtain sensors are widely used
Externí odkaz:
http://arxiv.org/abs/2404.03556
We propose two provably accurate methods for low CP-rank tensor completion - one using adaptive sampling and one using nonadaptive sampling. Both of our algorithms combine matrix completion techniques for a small number of slices along with Jennrich'
Externí odkaz:
http://arxiv.org/abs/2403.09932