Zobrazeno 1 - 10
of 2 491
pro vyhledávání: '"Bastani, P."'
Autor:
Ma, Yecheng Jason, Hejna, Joey, Wahid, Ayzaan, Fu, Chuyuan, Shah, Dhruv, Liang, Jacky, Xu, Zhuo, Kirmani, Sean, Xu, Peng, Driess, Danny, Xiao, Ted, Tompson, Jonathan, Bastani, Osbert, Jayaraman, Dinesh, Yu, Wenhao, Zhang, Tingnan, Sadigh, Dorsa, Xia, Fei
Predicting temporal progress from visual trajectories is important for intelligent robots that can learn, adapt, and improve. However, learning such progress estimator, or temporal value function, across different tasks and domains requires both a la
Externí odkaz:
http://arxiv.org/abs/2411.04549
Autor:
Liang, William, Wang, Sam, Wang, Hung-Ju, Bastani, Osbert, Jayaraman, Dinesh, Ma, Yecheng Jason
Recent work has demonstrated that a promising strategy for teaching robots a wide range of complex skills is by training them on a curriculum of progressively more challenging environments. However, developing an effective curriculum of environment d
Externí odkaz:
http://arxiv.org/abs/2411.01775
Conformal prediction has recently emerged as a promising strategy for quantifying the uncertainty of a predictive model; these algorithms modify the model to output sets of labels that are guaranteed to contain the true label with high probability. H
Externí odkaz:
http://arxiv.org/abs/2410.06296
Autor:
Karger, Ezra, Bastani, Houtan, Yueh-Han, Chen, Jacobs, Zachary, Halawi, Danny, Zhang, Fred, Tetlock, Philip E.
Forecasts of future events are essential inputs into informed decision-making. Machine learning (ML) systems have the potential to deliver forecasts at scale, but there is no framework for evaluating the accuracy of ML systems on a standardized set o
Externí odkaz:
http://arxiv.org/abs/2409.19839
Autor:
Yao, Michael S., Chae, Allison, Kahn Jr., Charles E., Witschey, Walter R., Gee, James C., Sagreiya, Hersh, Bastani, Osbert
Diagnostic imaging studies are an increasingly important component of the workup and management of acutely presenting patients. However, ordering appropriate imaging studies according to evidence-based medical guidelines is a challenging task with a
Externí odkaz:
http://arxiv.org/abs/2409.19177
Autor:
Deitke, Matt, Clark, Christopher, Lee, Sangho, Tripathi, Rohun, Yang, Yue, Park, Jae Sung, Salehi, Mohammadreza, Muennighoff, Niklas, Lo, Kyle, Soldaini, Luca, Lu, Jiasen, Anderson, Taira, Bransom, Erin, Ehsani, Kiana, Ngo, Huong, Chen, YenSung, Patel, Ajay, Yatskar, Mark, Callison-Burch, Chris, Head, Andrew, Hendrix, Rose, Bastani, Favyen, VanderBilt, Eli, Lambert, Nathan, Chou, Yvonne, Chheda, Arnavi, Sparks, Jenna, Skjonsberg, Sam, Schmitz, Michael, Sarnat, Aaron, Bischoff, Byron, Walsh, Pete, Newell, Chris, Wolters, Piper, Gupta, Tanmay, Zeng, Kuo-Hao, Borchardt, Jon, Groeneveld, Dirk, Dumas, Jen, Nam, Crystal, Lebrecht, Sophie, Wittlif, Caitlin, Schoenick, Carissa, Michel, Oscar, Krishna, Ranjay, Weihs, Luca, Smith, Noah A., Hajishirzi, Hannaneh, Girshick, Ross, Farhadi, Ali, Kembhavi, Aniruddha
Today's most advanced multimodal models remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good performance, effectively distilling these closed models into open ones. As a result, the
Externí odkaz:
http://arxiv.org/abs/2409.17146
Autor:
Chang, Yi-Chia, Stewart, Adam J., Bastani, Favyen, Wolters, Piper, Kannan, Shreya, Huber, George R., Wang, Jingtong, Banerjee, Arindam
Foundation models pre-trained using self-supervised and weakly-supervised learning have shown powerful transfer learning capabilities on various downstream tasks, including language understanding, text generation, and image recognition. Recently, the
Externí odkaz:
http://arxiv.org/abs/2409.09451
The capability to generate diverse text is a key challenge facing large language models (LLMs). Thus far, diversity has been studied via metrics such as $n$-gram diversity or diversity of BERT embeddings. However, for these kinds of diversity, the us
Externí odkaz:
http://arxiv.org/abs/2408.06186
Autor:
Bastani, Osbert
We prove convergence guarantees for generalized low-rank matrix sensing -- i.e., where matrix sensing where the observations may be passed through some nonlinear link function. We focus on local convergence of the optimal estimator, ignoring question
Externí odkaz:
http://arxiv.org/abs/2407.10238
We consider access control for IoT systems that involves shared accesses to the IoT devices as well as their data. Since IoT devices are dispersed all over the edge of the Internet, traditional centralized access control has problems. Blockchain base
Externí odkaz:
http://arxiv.org/abs/2407.05506