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Related papers: World Models: The Safety Perspective

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The era of intelligent agents is upon us, driven by revolutionary advancements in large language models. Large Language Model (LLM) agents, with goal-driven behaviors and dynamic adaptation capabilities, potentially represent a critical…

World models are emerging as a transformative paradigm in artificial intelligence, enabling agents to construct internal representations of their environments for predictive reasoning, planning, and decision-making. By learning latent…

Artificial Intelligence · Computer Science 2025-06-03 Changyuan Zhao , Ruichen Zhang , Jiacheng Wang , Gaosheng Zhao , Dusit Niyato , Geng Sun , Shiwen Mao , Dong In Kim

Large Language Models (LLMs) can serve as world models to enhance agent decision-making in digital environments by simulating future states and predicting action outcomes, potentially eliminating costly trial-and-error exploration. However,…

Computation and Language · Computer Science 2026-03-10 Kai Mei , Jiang Guo , Shuaichen Chang , Mingwen Dong , Dongkyu Lee , Xing Niu , Jiarong Jiang

In the field of Artificial (General) Intelligence (AI), the several recent advancements in Natural language processing (NLP) activities relying on Large Language Models (LLMs) have come to encourage the adoption of LLMs as scientific models…

Computation and Language · Computer Science 2023-10-18 Evelina Leivada , Vittoria Dentella , Elliot Murphy

Large language models (LLMs) and LLM-based agents have been widely deployed in a wide range of applications in the real world, including healthcare diagnostics, financial analysis, customer support, robotics, and autonomous driving,…

Cryptography and Security · Computer Science 2025-05-20 Wenrui Xu , Keshab K. Parhi

World Models serve as tools for understanding the current state of the world and predicting its future dynamics, with broad application potential across numerous fields. As a key component of world knowledge, emotion significantly…

Computation and Language · Computer Science 2026-01-01 Changhao Song , Yazhou Zhang , Hui Gao , Chang Yang , Peng Zhang

Despite their tremendous success in many applications, large language models often fall short of consistent reasoning and planning in various (language, embodied, and social) scenarios, due to inherent limitations in their inference,…

Artificial Intelligence · Computer Science 2023-12-11 Zhiting Hu , Tianmin Shu

With the advent of Large Language Models (LLMs), medical artificial intelligence (AI) has experienced substantial technological progress and paradigm shifts, highlighting the potential of LLMs to streamline healthcare delivery and improve…

Computation and Language · Computer Science 2024-12-10 Lei Liu , Xiaoyan Yang , Junchi Lei , Yue Shen , Jian Wang , Peng Wei , Zhixuan Chu , Zhan Qin , Kui Ren

Agentic AI systems -- Large Language Models (LLMs) augmented with planning, tool use, memory, and long-horizon interactions -- can execute complex tasks autonomously, but their multi-step trajectories introduce new failure modes that…

Artificial Intelligence · Computer Science 2026-05-26 Jinhu Qi , Muzhi Li , Jiahong Liu , Yuqin Shu , Dianzhi Yu , Shicheng Ma , Wenqian Cui , Yiyang Zhao , Yiyi Chen , Ruoxi Jiang , Irwin King , Zenglin Xu

Large language model (LLM) based agents have recently attracted much attention from the research and industry communities. Compared with original LLMs, LLM-based agents are featured in their self-evolving capability, which is the basis for…

Artificial Intelligence · Computer Science 2024-04-23 Zeyu Zhang , Xiaohe Bo , Chen Ma , Rui Li , Xu Chen , Quanyu Dai , Jieming Zhu , Zhenhua Dong , Ji-Rong Wen

The rapid advancement of Large Language Models (LLMs) has driven novel applications across diverse domains, with LLM-based agents emerging as a crucial area of exploration. This survey presents a comprehensive analysis of LLM-based agents…

Artificial Intelligence · Computer Science 2025-11-25 Ke Chen , Peiran Wang , Yaoning Yu , Xianyang Zhan , Haohan Wang

As the strength of Large Language Models (LLMs) has grown over recent years, so too has interest in their use as the underlying models for autonomous agents. Although LLMs demonstrate emergent abilities and broad expertise across natural…

Artificial Intelligence · Computer Science 2024-12-06 Chris Sypherd , Vaishak Belle

Language agents increasingly require persistent worlds in which they can act, remember, and learn. Existing approaches sit at two extremes: conventional web frameworks provide reliable but fixed contexts backed by databases, while fully…

Artificial Intelligence · Computer Science 2025-12-30 Jichen Feng , Yifan Zhang , Chenggong Zhang , Yifu Lu , Shilong Liu , Mengdi Wang

Large language models (LLMs) have become increasingly sophisticated, leading to widespread deployment in sensitive applications where safety and reliability are paramount. However, LLMs have inherent risks accompanying them, including bias,…

Cryptography and Security · Computer Science 2024-06-21 Suriya Ganesh Ayyamperumal , Limin Ge

Autonomous agents are increasingly expected to operate in complex, dynamic, and uncertain environments, performing tasks such as manipulation, navigation, and decision-making. Achieving these capabilities requires agents to understand the…

Robotics · Computer Science 2025-11-11 Peng-Fei Zhang , Ying Cheng , Xiaofan Sun , Shijie Wang , Fengling Li , Lei Zhu , Heng Tao Shen

Large Language Models (LLMs) possess general world knowledge but often struggle to generate precise predictions in structured, domain-specific contexts such as simulations. These limitations arise from their inability to ground their broad,…

Artificial Intelligence · Computer Science 2026-01-30 Guillaume Levy , Cedric Colas , Pierre-Yves Oudeyer , Thomas Carta , Clement Romac

Large Language Model (LLMs) such as ChatGPT that exhibit generative AI capabilities are facing accelerated adoption and innovation. The increased presence of Generative AI (GAI) inevitably raises concerns about the risks and safety…

Computers and Society · Computer Science 2024-07-29 Jaymari Chua , Yun Li , Shiyi Yang , Chen Wang , Lina Yao

Recent advances in large language model (LLM) have empowered autonomous agents to perform multi-turn interactions with tools and environments. However, scaling such agent training is limited by the lack of diverse and reliable environments.…

Artificial Intelligence · Computer Science 2026-05-26 Zhaoyang Wang , Canwen Xu , Boyi Liu , Yite Wang , Siwei Han , Zhewei Yao , Huaxiu Yao , Yuxiong He

In the age of large language models (LLMs), autonomous agents have emerged as a powerful paradigm for achieving general intelligence. These agents dynamically leverage tools, memory, and reasoning capabilities to accomplish user-defined…

Artificial Intelligence · Computer Science 2025-08-05 Chaojia Yu , Zihan Cheng , Hanwen Cui , Yishuo Gao , Zexu Luo , Yijin Wang , Hangbin Zheng , Yong Zhao

The long-standing vision of intelligent cities is to create efficient, livable, and sustainable urban environments using big data and artificial intelligence technologies. Recently, the advent of Large Language Models (LLMs) has opened new…

Multiagent Systems · Computer Science 2025-07-02 Jindong Han , Yansong Ning , Zirui Yuan , Hang Ni , Fan Liu , Tengfei Lyu , Hao Liu