Zobrazeno 1 - 10
of 1 361
pro vyhledávání: '"DONGRE, P."'
Autor:
Dongre, Vardhan, Yang, Xiaocheng, Acikgoz, Emre Can, Dey, Suvodip, Tur, Gokhan, Hakkani-Tür, Dilek
Large language model (LLM)-based agents have been increasingly used to interact with external environments (e.g., games, APIs, etc.) and solve tasks. However, current frameworks do not enable these agents to work with users and interact with them to
Externí odkaz:
http://arxiv.org/abs/2411.00927
Publikováno v:
NeurIPS 2024 Workshop on Open-World Agents
Recent advancements in Large Language Model (LLM)-based frameworks have extended their capabilities to complex real-world applications, such as interactive web navigation. These systems, driven by user commands, navigate web browsers to complete task
Externí odkaz:
http://arxiv.org/abs/2410.23555
Publikováno v:
NeurIPS 2024 Workshop on Open-World Agents
Embodied agents designed to assist users with tasks must engage in natural language interactions, interpret instructions, execute actions, and communicate effectively to resolve issues. However, collecting large-scale, diverse datasets of situated hu
Externí odkaz:
http://arxiv.org/abs/2410.23535
We analyze the performance of a quantum battery in terms of energy storage and energy extraction, assisted by nonlinearities in a charger-battery system utilizing an open-system approach. In particular, we consider two types of nonlinearities in the
Externí odkaz:
http://arxiv.org/abs/2410.00618
In modern healthcare, addressing the complexities of accurate disease prediction and personalized recommendations is both crucial and challenging. This research introduces MLtoGAI, which integrates Semantic Web technology with Machine Learning (ML) t
Externí odkaz:
http://arxiv.org/abs/2407.20284
Publikováno v:
IEEE Access 2024
This systematic literature review paper explores the use of extended reality {(XR)} technology for smart built environments and particularly for smart lighting systems design. Smart lighting is a novel concept that has emerged over a decade now and i
Externí odkaz:
http://arxiv.org/abs/2405.06928
This paper explores enhancing empathy in Large Language Models (LLMs) by integrating them with physiological data. We propose a physiological computing approach that includes developing deep learning models that use physiological data for recognizing
Externí odkaz:
http://arxiv.org/abs/2404.15351
Autor:
Deng, Bingchen, Ahn, Heonsu, Wang, Jue, Moon, Gunho, Dongre, Ninad, Lei, Chao, Scuri, Giovanni, Sung, Jiho, Brutschea, Elise, Watanabe, Kenji, Taniguchi, Takashi, Zhang, Fan, Jo, Moon-Ho, Park, Hongkun
A mirror twin boundary (MTB) in a transition metal dichalcogenide (TMD) monolayer can host one-dimensional electron liquid of a topological nature with tunable interactions. Unfortunately, the electrical characterization of such boundaries has been c
Externí odkaz:
http://arxiv.org/abs/2403.13956
Autor:
Dongre, Vardhan, Hora, Gurpreet Singh
The accessibility of spatially distributed data, enabled by affordable sensors, field, and numerical experiments, has facilitated the development of data-driven solutions for scientific problems, including climate change, weather prediction, and urba
Externí odkaz:
http://arxiv.org/abs/2311.04457
Autor:
Sneha A. Dongre, Gauri A. Kulkarni, Akshay Mishra, Rutuja B. Deshmane, Nameeta Sonar, Kanica Yashi, Damodar Thapa, Nikhil Ghade, Sachin M. Kadoo, Archana R. Krishnan, Sanjay M. Sonar
Publikováno v:
Research in Pharmaceutical Sciences, Vol 19, Iss 5, Pp 489-499 (2024)
Background and purpose: To compare the efficacy, safety, and immunogenicity of recombinant insulin aspart 100 U/mL manufactured by BioGenomics Limited (BGL-ASP) with innovator NovoRapid® in type 2 diabetes mellitus patients (T2 DM). Experimental app
Externí odkaz:
https://doaj.org/article/a78f8accec534f4ca3603b5aecde987a
