Zobrazeno 1 - 10
of 33 008
pro vyhledávání: '"Suraj, A."'
With the growing complexity and capability of large language models, a need to understand model reasoning has emerged, often motivated by an underlying goal of controlling and aligning models. While numerous interpretability and steering methods have
Externí odkaz:
http://arxiv.org/abs/2411.04430
Autor:
Li, Zexu, Prabhu, Suraj P., Popp, Zachary T., Jain, Shubhi S., Balakundi, Vijetha, Ang, Ting Fang Alvin, Au, Rhoda, Chen, Jinying
Biomedical research requires large, diverse samples to produce unbiased results. Automated methods for matching variables across datasets can accelerate this process. Research in this area has been limited, primarily focusing on lexical matching and
Externí odkaz:
http://arxiv.org/abs/2411.02730
Autor:
Black, Kevin, Brown, Noah, Driess, Danny, Esmail, Adnan, Equi, Michael, Finn, Chelsea, Fusai, Niccolo, Groom, Lachy, Hausman, Karol, Ichter, Brian, Jakubczak, Szymon, Jones, Tim, Ke, Liyiming, Levine, Sergey, Li-Bell, Adrian, Mothukuri, Mohith, Nair, Suraj, Pertsch, Karl, Shi, Lucy Xiaoyang, Tanner, James, Vuong, Quan, Walling, Anna, Wang, Haohuan, Zhilinsky, Ury
Robot learning holds tremendous promise to unlock the full potential of flexible, general, and dexterous robot systems, as well as to address some of the deepest questions in artificial intelligence. However, bringing robot learning to the level of g
Externí odkaz:
http://arxiv.org/abs/2410.24164
Autor:
Hatch, Kyle B., Balakrishna, Ashwin, Mees, Oier, Nair, Suraj, Park, Seohong, Wulfe, Blake, Itkina, Masha, Eysenbach, Benjamin, Levine, Sergey, Kollar, Thomas, Burchfiel, Benjamin
Image and video generative models that are pre-trained on Internet-scale data can greatly increase the generalization capacity of robot learning systems. These models can function as high-level planners, generating intermediate subgoals for low-level
Externí odkaz:
http://arxiv.org/abs/2410.20018
Quality-of-Service (QoS) prediction is a critical task in the service lifecycle, enabling precise and adaptive service recommendations by anticipating performance variations over time in response to evolving network uncertainties and user preferences
Externí odkaz:
http://arxiv.org/abs/2410.17762
Autor:
Kommuguri, Sneha Latha, Pratihary, Smrutishree, Singh, Thangjam Rishikanta, Sinha, Suraj Kumar
Unlike junctions in solid-state devices, a plasma-metal junction (pm-junction) is a junction of classical and quantum electrons. The plasma electrons are Maxwellain in nature, while metal electrons obey the Fermi-Dirac distribution. In this experimen
Externí odkaz:
http://arxiv.org/abs/2410.14306
Data Attribution (DA) methods quantify the influence of individual training data points on model outputs and have broad applications such as explainability, data selection, and noisy label identification. However, existing DA methods are often comput
Externí odkaz:
http://arxiv.org/abs/2410.09940
This paper presents a Discrete-Time Model Predictive Controller (MPC) for humanoid walking with online footstep adjustment. The proposed controller utilizes a hierarchical control approach. The high-level controller uses a low-dimensional Linear Inve
Externí odkaz:
http://arxiv.org/abs/2410.06790
The leakage of benchmark data into the training data has emerged as a significant challenge for evaluating the capabilities of large language models (LLMs). In this work, we use experimental evidence and theoretical estimates to challenge the common
Externí odkaz:
http://arxiv.org/abs/2410.03249
Autor:
Deshmukh, Neeraj, Yadav, Suraj
Given a smooth scheme X with an action by an affine algebraic group G, we give a formula to compute the Nisnevich sheaf of the motivic connected components of the quotient stack [X/G] in the case of an orbifold. We apply it to identify all the $\math
Externí odkaz:
http://arxiv.org/abs/2410.01525