Zobrazeno 1 - 10
of 47 323
pro vyhledávání: '"A A Jaya"'
Autor:
Xu, Maxwell A., Narain, Jaya, Darnell, Gregory, Hallgrimsson, Haraldur, Jeong, Hyewon, Forde, Darren, Fineman, Richard, Raghuram, Karthik J., Rehg, James M., Ren, Shirley
We present RelCon, a novel self-supervised \textit{Rel}ative \textit{Con}trastive learning approach that uses a learnable distance measure in combination with a softened contrastive loss for training an motion foundation model from wearable sensors.
Externí odkaz:
http://arxiv.org/abs/2411.18822
We show that flocking of microswimmers in a turbulent flow can enhance the efficacy of reinforcement-learning-based path-planning of microswimmers in turbulent flows. In particular, we develop a machine-learning strategy that incorporates Vicsek-mode
Externí odkaz:
http://arxiv.org/abs/2411.15902
Publikováno v:
EMNLP CustomNLP4U 2024
Although people are impressed by the content generation skills of large language models, the use of LLMs, such as ChatGPT, is limited by the domain grounding of the content. The correctness and groundedness of the generated content need to be based o
Externí odkaz:
http://arxiv.org/abs/2411.07870
Large language models (LLMs) could be valuable personal AI agents across various domains, provided they can precisely follow user instructions. However, recent studies have shown significant limitations in LLMs' instruction-following capabilities, ra
Externí odkaz:
http://arxiv.org/abs/2410.14582
Autor:
Heo, Juyeon, Heinze-Deml, Christina, Elachqar, Oussama, Ren, Shirley, Nallasamy, Udhay, Miller, Andy, Chan, Kwan Ho Ryan, Narain, Jaya
Instruction-following is crucial for building AI agents with large language models (LLMs), as these models must adhere strictly to user-provided constraints and guidelines. However, LLMs often fail to follow even simple and clear instructions. To imp
Externí odkaz:
http://arxiv.org/abs/2410.14516
Autor:
Agnihotri, Jaya, Bhoriya, Deepak, Kumar, Harish, Chandrashekhar, Praveen, Balsara, Dinshaw S.
Two-fluid plasma flow equations describe the flow of ions and electrons with different densities, velocities, and pressures. We consider the ideal plasma flow i.e. we ignore viscous, resistive, and collision effects. The resulting system of equations
Externí odkaz:
http://arxiv.org/abs/2409.16004
Neural network assisted electrostatic global gyrokinetic toroidal code using cylindrical coordinates
Gyrokinetic simulation codes are used to understand the microturbulence in the linear and nonlinear regimes of the tokamak and stellarator core. The codes that use flux coordinates to reduce computational complexities introduced by the anisotropy due
Externí odkaz:
http://arxiv.org/abs/2408.12851
Autor:
Kudyba, Paul, Mandapaka, Jaya Sravani, Wang, Weijie, McCorkendale, Logan, McCorkendale, Zachary, Kidane, Mathias, Sun, Haijian, Adams, Eric, Namuduri, Kamesh, Fund, Fraida, Sichitiu, Mihail, Ozdemir, Ozgur
As wireless researchers are tasked to enable wireless communication as infrastructure in more dynamic aerial settings, there is a growing need for large-scale experimental platforms that provide realistic, reproducible, and reliable experimental vali
Externí odkaz:
http://arxiv.org/abs/2407.12180
Autor:
Díaz-Aranda, Sergio, Ramírez, Juan Marcos, Daga, Mohit, Champati, Jaya Prakash, Aguilar, José, Lillo, Rosa Elvira, Anta, Antonio Fernández
Epidemiologists and social scientists have used the Network Scale-Up Method (NSUM) for over thirty years to estimate the size of a hidden sub-population within a social network. This method involves querying a subset of network nodes about the number
Externí odkaz:
http://arxiv.org/abs/2407.10640
Autor:
Clink, Dena J., Kim, Jinsung, Cross-Jaya, Hope, Ahmad, Abdul Hamid, Hong, Moeurk, Sala, Roeun, Birot, Hélène, Agger, Cain, Vu, Thinh Tien, Thi, Hoa Nguyen, Chi, Thanh Nguyen, Klinck, Holger
Automated detection of acoustic signals is crucial for effective monitoring of vocal animals and their habitats across ecologically-relevant spatial and temporal scales. Recent advances in deep learning have made these approaches more accessible. How
Externí odkaz:
http://arxiv.org/abs/2407.09976