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OPEx: A Component-Wise Analysis of LLM-Centric Agents in Embodied Instruction Following
Embodied Instruction Following (EIF) is a crucial task in embodied learning, requiring agents to interact with their environment through egocentric observations to fulfill natural language instructions.
Deciphering Digital Detectives: Understanding LLM Behaviors and Capabilities in Multi-Agent Mystery Games
In this study, we explore the application of Large Language Models (LLMs) in \textit{Jubensha}, a Chinese detective role-playing game and a novel area in Artificial Intelligence (AI) driven gaming.
Augmented smartphone bilirubinometer enabled by a mobile app that turns smartphone into multispectral imager
This study highlights the potential of SpeCamX to improve the prediction of bio-chromophores, and its ability to transform an ordinary smartphone into a powerful medical tool without the need for additional investments or expertise.
Bulk Photovoltaic Effect Driven by Collective Excitations in a Correlated Insulator
We investigate the bulk photovoltaic effect, which rectifies light into electric current, in a collective quantum state with correlation driven electronic ferroelectricity.
Strongly Correlated Electrons Mesoscale and Nanoscale Physics
