Zobrazeno 1 - 10
of 198 427
pro vyhledávání: '"Ajay, A"'
Publikováno v:
2024 Conference on Robot Learning (CoRL)
Imitation learning from human demonstrations is an effective paradigm for robot manipulation, but acquiring large datasets is costly and resource-intensive, especially for long-horizon tasks. To address this issue, we propose SkillMimicGen (SkillGen)
Externí odkaz:
http://arxiv.org/abs/2410.18907
Robot learning has proven to be a general and effective technique for programming manipulators. Imitation learning is able to teach robots solely from human demonstrations but is bottlenecked by the capabilities of the demonstrations. Reinforcement l
Externí odkaz:
http://arxiv.org/abs/2410.18065
Autor:
Tian, Felix, Byadgi, Ajay, Kim, Daniel, Zha, Daochen, White, Matt, Xiao, Kairong, Yanglet, Xiao-Yang Liu
Publikováno v:
5th ACM International Conference on AI in Finance, 2024
Current large language models (LLMs) have proven useful for analyzing financial data, but most existing models, such as BloombergGPT and FinGPT, lack customization for specific user needs. In this paper, we address this gap by developing FinGPT Searc
Externí odkaz:
http://arxiv.org/abs/2410.15284
Presence of a hot corona above the accretion disc can have important consequences for the evolution of magnetic fields and the Shakura-Sunyaev (SS) viscosity parameter $\alpha$ in such a strongly coupled system. In this work, we have performed three-
Externí odkaz:
http://arxiv.org/abs/2410.14497
Autor:
Lodha, Chetan, Rai, Ajay Kumar
We investigate the mass spectra and decay properties of pions and all light tetraquarks using both semi-relativistic and non-relativistic frameworks. By applying a Cornell-like potential and a spin-dependent potential, we generate the mass spectra. T
Externí odkaz:
http://arxiv.org/abs/2410.14246
Autor:
Patel, Ajay, Zhu, Jiacheng, Qiu, Justin, Horvitz, Zachary, Apidianaki, Marianna, McKeown, Kathleen, Callison-Burch, Chris
Style representations aim to embed texts with similar writing styles closely and texts with different styles far apart, regardless of content. However, the contrastive triplets often used for training these representations may vary in both style and
Externí odkaz:
http://arxiv.org/abs/2410.12757
Autor:
Ye, Seonghyeon, Jang, Joel, Jeon, Byeongguk, Joo, Sejune, Yang, Jianwei, Peng, Baolin, Mandlekar, Ajay, Tan, Reuben, Chao, Yu-Wei, Lin, Bill Yuchen, Liden, Lars, Lee, Kimin, Gao, Jianfeng, Zettlemoyer, Luke, Fox, Dieter, Seo, Minjoon
We introduce Latent Action Pretraining for general Action models (LAPA), an unsupervised method for pretraining Vision-Language-Action (VLA) models without ground-truth robot action labels. Existing Vision-Language-Action models require action labels
Externí odkaz:
http://arxiv.org/abs/2410.11758
The long-term variability study over a range of black hole (BH) mass systems from the microquasars of stellar-mass black holes to the Active Galactic Nuclei (AGNs) of supermassive black holes, in $\gamma$-rays offers new insights into the physics of
Externí odkaz:
http://arxiv.org/abs/2410.06653
Autor:
Bandari, Abhinav, Yin, Lu, Hsieh, Cheng-Yu, Jaiswal, Ajay Kumar, Chen, Tianlong, Shen, Li, Krishna, Ranjay, Liu, Shiwei
Network pruning has emerged as a potential solution to make LLMs cheaper to deploy. However, existing LLM pruning approaches universally rely on the C4 dataset as the calibration data for calculating pruning scores, leaving its optimality unexplored.
Externí odkaz:
http://arxiv.org/abs/2410.07461
Autor:
yadav, Ajay Kumar, Sahoo, Suchismita
Recent results from the LHCb experiment have confirmed that lepton flavor universality is upheld in flavor-changing neutral current processes, such as $B \to K^{(*)} l^+ l^-$. However, discrepancies remain in the charged current sector, raising quest
Externí odkaz:
http://arxiv.org/abs/2410.06100