Peer review is fundamental to the integrity and advancement of scientific publication.
Traditional methods of peer review analyses often rely on exploration and statistics of …

General-purposed embodied agents are designed to understand the users' natural
instructions or intentions and act precisely to complete universal tasks. Recently, methods …

Recent years have witnessed the rapid development of Neuro-Symbolic (NeSy) AI systems,
which integrate symbolic reasoning into deep neural networks. However, most of the …

Healthcare systems worldwide face persistent challenges in efficiency, accessibility, and
personalization. Powered by modern AI technologies such as multimodal large language …

Unthinking execution of human instructions in robotic manipulation can lead to severe safety
risks, such as poisonings, fires, and even explosions. In this paper, we present responsible …

We investigate factors contributing to LLM agents' success in competitive multi-agent
environments, using auctions as a testbed where agents bid to maximize profit. The agents …

LLMs have immense potential for generating plans, transforming an initial world state into a
desired goal state. A large body of research has explored the use of LLMs for various …

Large language models (LLMs) based agent systems have made great strides in real-world
applications beyond traditional NLP tasks. This paper proposes a new LLM-powered Multi …

Healthcare systems worldwide face persistent challenges in efficiency, accessibility, and
personalization. Modern artificial intelligence (AI) has shown promise in addressing these …

Large Language Models have been shown to fail to create executable and verifiable plans
in grounded environments. An emerging line of work shows success in using LLM as a …