Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Dongre, Vardhan"'
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
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
DeepFake Audio, unlike DeepFake images and videos, has been relatively less explored from detection perspective, and the solutions which exist for the synthetic speech classification either use complex networks or dont generalize to different varieti
Externí odkaz:
http://arxiv.org/abs/2210.11722