Zobrazeno 1 - 10
of 763 957
pro vyhledávání: '"Jack, A. A."'
Autor:
Fourney, Adam, Bansal, Gagan, Mozannar, Hussein, Tan, Cheng, Salinas, Eduardo, Erkang, Zhu, Niedtner, Friederike, Proebsting, Grace, Bassman, Griffin, Gerrits, Jack, Alber, Jacob, Chang, Peter, Loynd, Ricky, West, Robert, Dibia, Victor, Awadallah, Ahmed, Kamar, Ece, Hosn, Rafah, Amershi, Saleema
Modern AI agents, driven by advances in large foundation models, promise to enhance our productivity and transform our lives by augmenting our knowledge and capabilities. To achieve this vision, AI agents must effectively plan, perform multi-step rea
Externí odkaz:
http://arxiv.org/abs/2411.04468
This work examines the fairness of generative mobility models, addressing the often overlooked dimension of equity in model performance across geographic regions. Predictive models built on crowd flow data are instrumental in understanding urban stru
Externí odkaz:
http://arxiv.org/abs/2411.04453
Autor:
Gegenberg, Jack, Kunstatter, Gabor
We consider a Yang-Mills type gauge theory of gravity based on the conformal group SO(4,2) coupled to a conformally invariant real scalar field. The goal is to generate fundamental dimensional constants via spontaneous breakdown of the conformal symm
Externí odkaz:
http://arxiv.org/abs/2411.04851
We propose a novel, highly efficient, second-order accurate, long-time unconditionally stable numerical scheme for a class of finite-dimensional nonlinear models that are of importance in geophysical fluid dynamics. The scheme is highly efficient in
Externí odkaz:
http://arxiv.org/abs/2411.03689
This paper presents a methodology for training a transformer-based model to classify lexical and morphosyntactic features of Skolt Sami, an endangered Uralic language characterized by complex morphology. The goal of our approach is to create an effec
Externí odkaz:
http://arxiv.org/abs/2411.02556
Autor:
Pearson Jr., Donny R., Prabhu, Ashwith, Tobar, Selvin, D'Amelio, Jack, Tram, Amy, Riedel, Zachary W., Shoemaker, Daniel P., Goldschmidt, Elizabeth A.
Rare-earth emitters in solids are well-suited for implementing efficient, long-lived quantum memory coupled to integrated photonics for scalable quantum technologies. They are typically introduced as dopants in a solid-state host, but this introduces
Externí odkaz:
http://arxiv.org/abs/2411.02683
Autor:
Leng, Xinyi, Liang, Jason, Mauro, Jack, Wang, Xu, Bertozzi, Andrea L., Chapman, James, Lin, Junyuan, Chen, Bohan, Ye, Chenchen, Daniel, Temple, Brantingham, P. Jeffrey
Narrative data spans all disciplines and provides a coherent model of the world to the reader or viewer. Recent advancement in machine learning and Large Language Models (LLMs) have enable great strides in analyzing natural language. However, Large l
Externí odkaz:
http://arxiv.org/abs/2411.02435
Autor:
Wu, Heng, Lu, Haoran, Peng, Wanyue, Xu, Ziqiao, Chu, Yanbang, Sun, Jiacheng, Zhou, Falong, Wu, Jack, Zhang, Lijie, Bu, Weihai, Kang, Jin, Li, Ming, Lin, Yibo, Wang, Runsheng, Zhang, Xin, Huang, Ru
Publikováno v:
Proc. of EDTM 2025
In this work, we proposed a new 3D integration technology: the Flip 3D integration (F3D), consisting of the 3D transistor stacking, the 3D dual-sided interconnects, the 3D die-to-die stacking and the dual-sided Monolithic 3D (M3D). Based on a 32-bit
Externí odkaz:
http://arxiv.org/abs/2411.00309
Autor:
Meyer, Maxwell, Spruyt, Jack
Transformers and their derivatives have achieved state-of-the-art performance across text, vision, and speech recognition tasks. However, minimal effort has been made to train transformers capable of evaluating the output quality of other models. Thi
Externí odkaz:
http://arxiv.org/abs/2411.00252
This chapter provides an overview of research works that present approaches with some degree of cross-fertilisation between Computational Argumentation and Machine Learning. Our review of the literature identified two broad themes representing the pu
Externí odkaz:
http://arxiv.org/abs/2410.23724