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OpenAI, Hurst, Aaron, Lerer, Adam, Goucher, Adam P., Perelman, Adam, Ramesh, Aditya, Clark, Aidan, Ostrow, AJ, Welihinda, Akila, Hayes, Alan, Radford, Alec, Mądry, Aleksander, Baker-Whitcomb, Alex, Beutel, Alex, Borzunov, Alex, Carney, Alex, Chow, Alex, Kirillov, Alex, Nichol, Alex, Paino, Alex, Renzin, Alex, Passos, Alex Tachard, Kirillov, Alexander, Christakis, Alexi, Conneau, Alexis, Kamali, Ali, Jabri, Allan, Moyer, Allison, Tam, Allison, Crookes, Amadou, Tootoochian, Amin, Tootoonchian, Amin, Kumar, Ananya, Vallone, Andrea, Karpathy, Andrej, Braunstein, Andrew, Cann, Andrew, Codispoti, Andrew, Galu, Andrew, Kondrich, Andrew, Tulloch, Andrew, Mishchenko, Andrey, Baek, Angela, Jiang, Angela, Pelisse, Antoine, Woodford, Antonia, Gosalia, Anuj, Dhar, Arka, Pantuliano, Ashley, Nayak, Avi, Oliver, Avital, Zoph, Barret, Ghorbani, Behrooz, Leimberger, Ben, Rossen, Ben, Sokolowsky, Ben, Wang, Ben, Zweig, Benjamin, Hoover, Beth, Samic, Blake, McGrew, Bob, Spero, Bobby, Giertler, Bogo, 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GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's trained end-to-end across text, vision, and audio, meaning all inputs
Externí odkaz:
http://arxiv.org/abs/2410.21276
V. Matache (J. Operator Theory 73(1):243--264, 2015) raised an open problem about characterizing composition operators $C_{\phi}$ on the Hardy space $H^2$ and nonzero singular measures $\mu_1$, $\mu_2$ on the unit circle such that $C_{\phi}({S_{\mu_1
Externí odkaz:
http://arxiv.org/abs/2408.09759
Autor:
Liu, Mira M., Dyke, Jonathan, Gladytz, Thomas, Jasse, Jonas, Bolger, Ian, Calle, Sergio, Pavaluri, Swathi, Crews, Tanner, Seshan, Surya, Salvatore, Steven, Stillman, Isaac, Muthukumar, Thangamani, Taouli, Bachir, Farouk, Samira, Lewis, Sara, Bane, Octavia
Purpose: Estimation of multi-compartment intravoxel flow in fD in ml/100g/min with multi-b-value diffusion weighted imaging and a multi-Gaussian model in the kidneys. Theory and Methods: A multi-Gaussian model of intravoxel flow using water transport
Externí odkaz:
http://arxiv.org/abs/2408.06427
Modern machine learning models are prone to over-reliance on spurious correlations, which can often lead to poor performance on minority groups. In this paper, we identify surprising and nuanced behavior of finetuned models on worst-group accuracy vi
Externí odkaz:
http://arxiv.org/abs/2407.13957
Autor:
Wang, Di, Hu, Chengsong, Xie, Shuangyu, Johnson, Joe, Ji, Hojun, Jiang, Yingtao, Bagavathiannan, Muthukumar, Song, Dezhen
Robotic weed flaming is a new and environmentally friendly approach to weed removal in the agricultural field. Using a mobile manipulator equipped with a flamethrower, we design a new system and algorithm to enable effective weed flaming, which requi
Externí odkaz:
http://arxiv.org/abs/2407.04929
Classifying 3D MRI images for early detection of Alzheimer's disease is a critical task in medical imaging. Traditional approaches using Convolutional Neural Networks (CNNs) and Transformers face significant challenges in this domain. CNNs, while eff
Externí odkaz:
http://arxiv.org/abs/2406.05757
The classical iteratively reweighted least-squares (IRLS) algorithm aims to recover an unknown signal from linear measurements by performing a sequence of weighted least squares problems, where the weights are recursively updated at each step. Variet
Externí odkaz:
http://arxiv.org/abs/2406.02769
We study the role of active coupling on the transport properties of homogeneously charged macromolecules in an infinitely dilute solution. An enzyme becomes actively bound to a segment of the macromolecule, exerting an electrostatic force on it. Even
Externí odkaz:
http://arxiv.org/abs/2405.13963
Autor:
Priyanka, M., Muthukumar, P.
The reduction in coral reef densities, characterized by the proliferation of macroalgae, has emerged as a global threat. In this paper, we present a discrete-time coral reef dynamical model that incorporates macroalgae. We explore all ecologically po
Externí odkaz:
http://arxiv.org/abs/2405.07491
Autor:
Lai, Kuo-Wei, Muthukumar, Vidya
Overparameterized models that achieve zero training error are observed to generalize well on average, but degrade in performance when faced with data that is under-represented in the training sample. In this work, we study an overparameterized Gaussi
Externí odkaz:
http://arxiv.org/abs/2405.06546