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Related papers: Agentic Insight Generation in VSM Simulations

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Agentic Retrieval-Augmented Generation (RAG) empowers large language models to autonomously plan and retrieve information for complex problem-solving. However, the development of robust agents is hindered by the scarcity of high-quality…

Computation and Language · Computer Science 2026-01-14 Zhengwei Tao , Bo Li , Jialong Wu , Guochen Yan , Huanyao Zhang , Jiahao Xu , Haitao Mi , Wentao Zhang

Foundation models have reshaped AI by unifying fragmented architectures into scalable backbones with multimodal reasoning and contextual adaptation. In parallel, the long-standing notion of AI agents, defined by the sensing-decision-action…

Machine Learning · Computer Science 2025-10-02 Sicong Liu , Weiye Wu , Xiangrui Xu , Teng Li , Bowen Pang , Bin Guo , Zhiwen Yu

The emergence of multi-agent systems powered by large language models (LLMs) has unlocked new frontiers in complex task-solving, enabling diverse agents to integrate unique expertise, collaborate flexibly, and address challenges…

Artificial Intelligence · Computer Science 2025-11-05 Jingbo Wang , Sendong Zhao , Haochun Wang , Yuzheng Fan , Lizhe Zhang , Yan Liu , Ting Liu

Accurate visual understanding is imperative for advancing autonomous systems and intelligent robots. Despite the powerful capabilities of vision-language models (VLMs) in processing complex visual scenes, precisely recognizing obscured or…

Computer Vision and Pattern Recognition · Computer Science 2024-06-03 Huaxiang Zhang , Yaojia Mu , Guo-Niu Zhu , Zhongxue Gan

Powerful autonomous systems, which reason, plan, and converse using and between numerous tools and agents, are made possible by Large Language Models (LLMs), Vision-Language Models (VLMs), and new agentic AI systems, like LangChain and…

Cryptography and Security · Computer Science 2025-12-30 Toqeer Ali Syed , Mishal Ateeq Almutairi , Mahmoud Abdel Moaty

Existing unstructured data analytics systems rely on experts to write code and manage complex analysis workflows, making them both expensive and time-consuming. To address these challenges, we introduce AgenticData, an innovative agentic…

Databases · Computer Science 2025-08-08 Ji Sun , Guoliang Li , Peiyao Zhou , Yihui Ma , Jingzhe Xu , Yuan Li

This paper introduces a methodology based on agentic workflows for economic research that leverages Large Language Models (LLMs) and multimodal AI to enhance research efficiency and reproducibility. Our approach features autonomous and…

General Economics · Economics 2025-04-15 Herbert Dawid , Philipp Harting , Hankui Wang , Zhongli Wang , Jiachen Yi

This study explores integrating large language models (LLMs) with situational awareness-based planning (SAP) to enhance the decision-making capabilities of AI agents in dynamic and uncertain environments. We employ a multi-agent reasoning…

Artificial Intelligence · Computer Science 2024-06-18 Liman Wang , Hanyang Zhong

This technical brief introduces Deep Agent, an advanced autonomous AI system designed to manage complex multi-phase tasks through a novel hierarchical task management architecture. The system's foundation is built on our Hierarchical Task…

Artificial Intelligence · Computer Science 2025-02-12 Amy Yu , Erik Lebedev , Lincoln Everett , Xiaoxin Chen , Terry Chen

Vision-Language Models (VLMs) show promise for autonomous driving, yet their struggle with hallucinations, inefficient reasoning, and limited real-world validation hinders accurate perception and robust step-by-step reasoning. To overcome…

Agentic Artificial Intelligence (AI) constitutes a transformative paradigm in the evolution of intelligent agents and decision-support systems, redefining smart environments by enhancing operational efficiency, optimizing resource…

The rapid evolution of agentic AI marks a new phase in artificial intelligence, where Large Language Models (LLMs) no longer merely respond but act, reason, and adapt. This survey traces the paradigm shift in building agentic AI: from…

Artificial Intelligence · Computer Science 2025-10-28 Jitao Sang , Jinlin Xiao , Jiarun Han , Jilin Chen , Xiaoyi Chen , Shuyu Wei , Yongjie Sun , Yuhang Wang

When used in high-stakes settings, AI systems are expected to produce decisions that are transparent, interpretable and auditable, a requirement increasingly expected by regulations. Decision trees such as CART provide clear and verifiable…

Machine Learning · Computer Science 2026-04-07 Vincent Grari , Tim Arni , Thibault Laugel , Sylvain Lamprier , James Zou , Marcin Detyniecki

Large language models (LLMs) have gained significant interest in industry due to their impressive capabilities across a wide range of tasks. However, the widespread adoption of LLMs presents several challenges, such as integration into…

Artificial Intelligence · Computer Science 2025-04-14 Eser Kandogan , Nikita Bhutani , Dan Zhang , Rafael Li Chen , Sairam Gurajada , Estevam Hruschka

Orchestrated multi-agent systems represent the next stage in the evolution of artificial intelligence, where autonomous agents collaborate through structured coordination and communication to achieve complex, shared objectives. This paper…

Multiagent Systems · Computer Science 2026-01-21 Apoorva Adimulam , Rajesh Gupta , Sumit Kumar

Large language models (LLMs) are increasingly deployed in agentic frameworks, in which prompts trigger complex tool-based analysis in pursuit of a goal. While these frameworks have shown promise across multiple domains including in finance,…

Statistical Finance · Quantitative Finance 2025-07-14 Dimitrios Emmanoulopoulos , Ollie Olby , Justin Lyon , Namid R. Stillman

Retrieval-Augmented Generation (RAG) systems have emerged as a pivotal methodology for enhancing Large Language Models (LLMs) through the dynamic integration of external knowledge. To further improve RAG's flexibility, Agentic RAG…

Information Retrieval · Computer Science 2026-05-19 Hao Sun , Zile Qiao , Bo Wang , Guoxin Chen , Yingyan Hou , Yong Jiang , Pengjun Xie , Fei Huang , Yan Zhang

Generating deep research reports requires large-scale information acquisition and the synthesis of insight-driven analysis, posing a significant challenge for current language models. Most existing approaches follow a plan-then-write…

Large language models (LLMs) and agent techniques have brought a fundamental shift in the functionality and development paradigm of data analysis tasks (a.k.a LLM/Agent-as-Data-Analyst), demonstrating substantial impact across both academia…

While individual components of agentic architectures have been studied in isolation, there remains limited empirical understanding of how different design dimensions interact within complex multi-agent systems. This study aims to address…

Artificial Intelligence · Computer Science 2026-01-07 Tara Bogavelli , Roshnee Sharma , Hari Subramani