Tootfinder

From Agentification to Self-Evolving Agentic AI for Wireless Networks: Concepts, Approaches, and Future Research Directions
Changyuan Zhao, Ruichen Zhang, Jiacheng Wang, Dusit Niyato, Geng Sun, Xianbin Wang, Shiwen Mao, Abbas Jamalipour
https://arxiv.org/abs/2510.05596

From Agentification to Self-Evolving Agentic AI for Wireless Networks: Concepts, Approaches, and Future Research Directions
Self-evolving agentic artificial intelligence (AI) offers a new paradigm for future wireless systems by enabling autonomous agents to continually adapt and improve without human intervention. Unlike static AI models, self-evolving agents embed an autonomous evolution cycle that updates models, tools, and workflows in response to environmental dynamics. This paper presents a comprehensive overview of self-evolving agentic AI, highlighting its layered architecture, life cycle, and key techniques,…

#AIForensics' study (07/2025) reveals how AI-generated content floods #TikTok & #Instagram, with platforms failing to adequately label synthetic material.
>

AI Generated Algorithmic Virality
This investigation systematically analyzes AI-generated content across TikTok and Instagram in three European countries. We found that 25% of TikTok's top search results contain synthetic AI imagery, with over 80% produced by "Agentic AI Accounts." Despite platforms' DSA commitments, only half of AI content receives proper labeling, creating significant risks for users.

Open Webinar IIP – 16 settembre 2025 – Come cambia il diritto dei dati con l’Agentic AI
https://www.istitutoitalianoprivacy.it/2025/09/08/open-webinar-iip-16-settembre-2025-come-cambia-il-diritto-dei-dati-co…

Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction
Sahar Salimpour, Lei Fu, Farhad Keramat, Leonardo Militano, Giovanni Toffetti, Harry Edelman, Jorge Pe\~na Queralta
https://arxiv.org/abs/2508.05294

Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction
Foundation models, including large language models (LLMs) and vision-language models (VLMs), have recently enabled novel approaches to robot autonomy and human-robot interfaces. In parallel, vision-language-action models (VLAs) or large behavior models (BLMs) are increasing the dexterity and capabilities of robotic systems. This survey paper focuses on those words advancing towards agentic applications and architectures. This includes initial efforts exploring GPT-style interfaces to tooling, a…

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
L\'eo Boisvert, Abhay Puri, Chandra Kiran Reddy Evuru, Nicolas Chapados, Quentin Cappart, Alexandre Lacoste, Krishnamurthy Dj Dvijotham, Alexandre Drouin
https://arxiv.org/abs/2510.05159

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
The practice of fine-tuning AI agents on data from their own interactions--such as web browsing or tool use--, while being a strong general recipe for improving agentic capabilities, also introduces a critical security vulnerability within the AI supply chain. In this work, we show that adversaries can easily poison the data collection pipeline to embed hard-to-detect backdoors that are triggerred by specific target phrases, such that when the agent encounters these triggers, it performs an uns…

Interesting and worrying article by Marcus and Hamiel going over recent work exploring the very serious security weaknesses of agentic AI:
https://garymarcus.substack.com/p/llms-coding-agents-security-nightmare

LLMs + Coding Agents = Security Nightmare
Things are about to get wild

Agentic DDQN-Based Scheduling for Licensed and Unlicensed Band Allocation in Sidelink Networks
Po-Heng Chou, Pin-Qi Fu, Walid Saad, Li-Chun Wang
https://arxiv.org/abs/2509.06775

Agentic DDQN-Based Scheduling for Licensed and Unlicensed Band Allocation in Sidelink Networks
This paper presents an agentic artificial intelligence (AI)-driven double deep Q-network (DDQN) scheduling framework for licensed and unlicensed band allocation in New Radio (NR) sidelink (SL) networks. SL must share licensed spectrum with cellular communications (CC) and unlicensed bands with Wi-Fi, posing significant challenges for coexistence. Unlike prior rule-based or threshold-based methods, the proposed agentic scheduler autonomously perceives queueing dynamics, channel conditions, and c…

Breakfast at my elegant London hotel, listening to the America business bro next to me harangue his captive audience. His company has a best of class agentic AI product at scale. It integrates fully with the Blockchain.

Q&A with Anthropic CEO Dario Amodei on Anthropic's growth to ~$5B in ARR, focusing on B2B, AI talent wars, open-source models, safety regulations, and more (John Collison/Cheeky Pint)
https://cheekypint.substack.com/p/a-cheeky-pint-with-anthropic-ceo

A Cheeky Pint with Anthropic CEO Dario Amodei
Dario Amodei joins John Collison to talk about Anthropic's growth to almost $5 billion in ARR, how AI models show capitalistic impulses, predictions for an agentic future, the economics of model businesses, and the 19th-century concept of vitalism.

A4FN: an Agentic AI Architecture for Autonomous Flying Networks
Andr\'e Coelho, Pedro Ribeiro, Helder Fontes, Rui Campos
https://arxiv.org/abs/2510.03829 https://

A4FN: an Agentic AI Architecture for Autonomous Flying Networks
This position paper presents A4FN, an Agentic Artificial Intelligence (AI) architecture for intent-driven automation in Flying Networks (FNs) using Unmanned Aerial Vehicles (UAVs) as access nodes. A4FN leverages Generative AI and Large Language Models (LLMs) to enable real-time, context-aware network control via a distributed agentic system. It comprises two components: the Perception Agent (PA), which semantically interprets multimodal input -- including imagery, audio, and telemetry data -- f…

FreshBrew: A Benchmark for Evaluating AI Agents on Java Code Migration
Victor May, Diganta Misra, Yanqi Luo, Anjali Sridhar, Justine Gehring, Silvio Soares Ribeiro Junior
https://arxiv.org/abs/2510.04852

FreshBrew: A Benchmark for Evaluating AI Agents on Java Code Migration
AI coding assistants are rapidly becoming integral to modern software development. A key challenge in this space is the continual need to migrate and modernize codebases in response to evolving software ecosystems. Traditionally, such migrations have relied on rule-based systems and human intervention. With the advent of powerful large language models (LLMs), AI-driven agentic frameworks offer a promising alternative-but their effectiveness has not been systematically evaluated. In this paper, …

Discovery of Disease Relationships via Transcriptomic Signature Analysis Powered by Agentic AI
Ke Chen, Haohan Wang
https://arxiv.org/abs/2508.04742 https://

Discovery of Disease Relationships via Transcriptomic Signature Analysis Powered by Agentic AI
Modern disease classification often overlooks molecular commonalities hidden beneath divergent clinical presentations. This study introduces a transcriptomics-driven framework for discovering disease relationships by analyzing over 1300 disease-condition pairs using GenoMAS, a fully automated agentic AI system. Beyond identifying robust gene-level overlaps, we develop a novel pathway-based similarity framework that integrates multi-database enrichment analysis to quantify functional convergence…

PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows
Renan Souza, Amal Gueroudji, Stephen DeWitt, Daniel Rosendo, Tirthankar Ghosal, Robert Ross, Prasanna Balaprakash, Rafael Ferreira da Silva
https://arxiv.org/abs/2508.02866

PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows
Foundation models, such as Large Language Models (LLMs), are increasingly used as core components of AI agents in complex, large-scale workflows across federated and heterogeneous environments. In agentic workflows, autonomous agents plan tasks, interact with humans and peers, and shape scientific outcomes. This makes transparency, traceability, reproducibility, and reliability essential. However, AI-based agents can hallucinate or reason incorrectly, and their decisions may propagate errors th…

VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
Mohammed Almutairi, Charles Chiang, Haoze Guo, Matthew Belcher, Nandini Banerjee, Maria Milkowski, Svitlana Volkova, Daniel Nguyen, Tim Weninger, Michael Yankoski, Trenton W. Ford, Diego Gomez-Zara
https://arxiv.org/abs/2508.04634

VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
Simulating how team members collaborate within complex environments using Agentic AI is a promising approach to explore hypotheses grounded in social science theories and study team behaviors. We introduce VirtLab, a user-friendly, customizable, multi-agent, and scalable team simulation system that enables testing teams with LLM-based agents in spatial and temporal settings. This system addresses the current frameworks' design and technical limitations that do not consider flexible simulation s…

PentestMCP: A Toolkit for Agentic Penetration Testing
Zachary Ezetta, Wu-chang Feng
https://arxiv.org/abs/2510.03610 https://arxiv.org/pdf/2510.03610

PentestMCP: A Toolkit for Agentic Penetration Testing
Agentic AI is transforming security by automating many tasks being performed manually. While initial agentic approaches employed a monolithic architecture, the Model-Context-Protocol has now enabled a remote-procedure call (RPC) paradigm to agentic applications, allowing for the flexible construction and composition of multi-function agents. This paper describes PentestMCP, a library of MCP server implementations that support agentic penetration testing. By supporting common penetration testing…

Artificially intelligent agents in the social and behavioral sciences: A history and outlook
Petter Holme, Milena Tsvetkova
https://arxiv.org/abs/2510.05743 https://

Artificially intelligent agents in the social and behavioral sciences: A history and outlook
We review the historical development and current trends of artificially intelligent agents (agentic AI) in the social and behavioral sciences: from the first programmable computers, and social simulations soon thereafter, to today's experiments with large language models. This overview emphasizes the role of AI in the scientific process and the changes brought about, both through technological advancements and the broader evolution of science from around 1950 to the present. Some of the specifi…

Is the client vendor now responsible for you getting scammed when their agent gives away your financial information to scam sites?
https://guard.io/labs/scamlexity-we-put-agentic-ai-browsers-to-the-test-they-clicked-they-paid-they-fa…

"Scamlexity": When Agentic AI Browsers Get Scammed
We Put Agentic AI Browsers to the Test - They Clicked, They Paid, They Failed

Speaking of AI, CrowdStrike came out with two big announcements today on its big shift to agentic AI.
My latest piece for CSO.
CrowdStrike bets big on agentic AI with new offerings after $290M Onum buy
https://www.csoonline.com/article/405…

CrowdStrike bets big on agentic AI with new offerings after $290M Onum buy
At its Fal.Con conference, the cybersecurity giant launched its Agentic Security Platform and Agentic Security Workforce, aiming to outpace AI-driven adversaries with real-time intelligence, automation, and a common language for defense.

ArgoLOOM: agentic AI for fundamental physics from quarks to cosmos
S. D. Bakshi, P. Barry, C. Bissolotti, I. Cloet, S. Corrodi, Z. Djurcic, S. Habib, K. Heitmann, T. J. Hobbs, W. Hopkins, S. Joosten, B. Kriesten, N. Ramachandra, A. Wells, M. Zurek
https://arxiv.org/abs/2510.02426

ArgoLOOM: agentic AI for fundamental physics from quarks to cosmos
Progress in modern physics has been supported by a steadily expanding corpus of numerical analyses and computational frameworks, which in turn form the basis for precision calculations and baseline predictions in experimental programs. These tools play a central role in navigating a complex landscape of theoretical models and current and potential observables to identify and understand fundamental interactions in physics. In addition, efforts to search for new fundamental interactions increasin…

"AI Generated Algorithmic Virality"
https://aiforensics.org/work/gen-ai-slop
A recent report by
@…
🔹 "25% of…

AI Generated Algorithmic Virality
This investigation systematically analyzes AI-generated content across TikTok and Instagram in three European countries. We found that 25% of TikTok's top search results contain synthetic AI imagery, with over 80% produced by "Agentic AI Accounts." Despite platforms' DSA commitments, only half of AI content receives proper labeling, creating significant risks for users.

AI Agent Smart Contract Exploit Generation
Arthur Gervais, Liyi Zhou
https://arxiv.org/abs/2507.05558 https://arxiv.org/pdf/2507.0555…

AI Agent Smart Contract Exploit Generation
We present A1, an agentic execution driven system that transforms any LLM into an end-to-end exploit generator. A1 has no hand-crafted heuristics and provides the agent with six domain-specific tools that enable autonomous vulnerability discovery. The agent can flexibly leverage these tools to understand smart contract behavior, generate exploit strategies, test them on blockchain states, and refine approaches based on execution feedback. All outputs are concretely validated to eliminate false …

Agentic AI in 6G Software Businesses: A Layered Maturity Model
Muhammad Zohaib, Muhammad Azeem Akbar, Sami Hyrynsalmi, Arif Ali Khan
https://arxiv.org/abs/2508.03393 https://

Agentic AI in 6G Software Businesses: A Layered Maturity Model
The emergence of agentic AI systems in 6G software businesses presents both strategic opportunities and significant challenges. While such systems promise increased autonomy, scalability, and intelligent decision-making across distributed environments, their adoption raises concerns regarding technical immaturity, integration complexity, organizational readiness, and performance-cost trade-offs. In this study, we conducted a preliminary thematic mapping to identify factors influencing the adopt…

Agentic large language models improve retrieval-based radiology question answering
Sebastian Wind, Jeta Sopa, Daniel Truhn, Mahshad Lotfinia, Tri-Thien Nguyen, Keno Bressem, Lisa Adams, Mirabela Rusu, Harald K\"ostler, Gerhard Wellein, Andreas Maier, Soroosh Tayebi Arasteh
https://arxiv.org/abs/2508.00743

Agentic large language models improve retrieval-based radiology question answering
Clinical decision-making in radiology increasingly benefits from artificial intelligence (AI), particularly through large language models (LLMs). However, traditional retrieval-augmented generation (RAG) systems for radiology question answering (QA) typically rely on single-step retrieval, limiting their ability to handle complex clinical reasoning tasks. Here we propose an agentic RAG framework enabling LLMs to autonomously decompose radiology questions, iteratively retrieve targeted clinical …

Orchestrating Human-AI Teams: The Manager Agent as a Unifying Research Challenge
Charlie Masters, Advaith Vellanki, Jiangbo Shangguan, Bart Kultys, Jonathan Gilmore, Alastair Moore, Stefano V. Albrecht
https://arxiv.org/abs/2510.02557

Orchestrating Human-AI Teams: The Manager Agent as a Unifying Research Challenge
While agentic AI has advanced in automating individual tasks, managing complex multi-agent workflows remains a challenging problem. This paper presents a research vision for autonomous agentic systems that orchestrate collaboration within dynamic human-AI teams. We propose the Autonomous Manager Agent as a core challenge: an agent that decomposes complex goals into task graphs, allocates tasks to human and AI workers, monitors progress, adapts to changing conditions, and maintains transparent s…

Leena AI, which develops an employee-facing agentic AI assistant, launches "AI colleagues" that it says can work and interact just like human employees (Kyt Dotson/SiliconANGLE)
https://siliconangle.com/2025/07/24/leena-ai-anno…

Leena AI announces voice-enabled AI ‘colleagues’ who can work alongside you - SiliconANGLE
Leena AI announces voice-enabled AI ‘colleagues’ who can work alongside you - SiliconANGLE

Agentic-AI based Mathematical Framework for Commercialization of Energy Resilience in Electrical Distribution System Planning and Operation
Aniket Johri, Divyanshi Dwivedi, Mayukha Pal
https://arxiv.org/abs/2508.04170

Agentic-AI based Mathematical Framework for Commercialization of Energy Resilience in Electrical Distribution System Planning and Operation
The increasing vulnerability of electrical distribution systems to extreme weather events and cyber threats necessitates the development of economically viable frameworks for resilience enhancement. While existing approaches focus primarily on technical resilience metrics and enhancement strategies, there remains a significant gap in establishing market-driven mechanisms that can effectively commercialize resilience features while optimizing their deployment through intelligent decision-making.…

Agentic Workflow for Education: Concepts and Applications
Yuan-Hao Jiang, Yijie Lu, Ling Dai, Jiatong Wang, Ruijia Li, Bo Jiang
https://arxiv.org/abs/2509.01517 https://

Agentic Workflow for Education: Concepts and Applications
With the rapid advancement of Large Language Models (LLMs) and Artificial Intelligence (AI) agents, agentic workflows are showing transformative potential in education. This study introduces the Agentic Workflow for Education (AWE), a four-component model comprising self-reflection, tool invocation, task planning, and multi-agent collaboration. We distinguish AWE from traditional LLM-based linear interactions and propose a theoretical framework grounded in the von Neumann Multi-Agent System (MA…

Agentic AI meets Neural Architecture Search: Proactive Traffic Prediction for AI-RAN
Abdelaziz Salama, Mohammed M. H. Qazzaz, Zeinab Nezami, Maryam Hafeez, Syed Ali Raza Zaidi
https://arxiv.org/abs/2510.00851

Agentic AI meets Neural Architecture Search: Proactive Traffic Prediction for AI-RAN
Next-generation wireless networks require intelligent traffic prediction to enable autonomous resource management and handle diverse, dynamic service demands. The Open Radio Access Network (O-RAN) framework provides a promising foundation for embedding machine learning intelligence through its disaggregated architecture and programmable interfaces. This work applies a Neural Architecture Search (NAS)-based framework that dynamically selects and orchestrates efficient Long Short-Term Memory (LST…

A co-evolving agentic AI system for medical imaging analysis
Songhao Li, Jonathan Xu, Tiancheng Bao, Yuxuan Liu, Yuchen Liu, Yihang Liu, Lilin Wang, Wenhui Lei, Sheng Wang, Yinuo Xu, Yan Cui, Jialu Yao, Shunsuke Koga, Zhi Huang
https://arxiv.org/abs/2509.20279

A co-evolving agentic AI system for medical imaging analysis
Agentic AI is rapidly advancing in healthcare and biomedical research. However, in medical image analysis, their performance and adoption remain limited due to the lack of a robust ecosystem, insufficient toolsets, and the absence of real-time interactive expert feedback. Here we present "TissueLab", a co-evolving agentic AI system that allows researchers to ask direct questions, automatically plan and generate explainable workflows, and conduct real-time analyses where experts can visualize in…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[2/9]:
- From Semantic Web and MAS to Agentic AI: A Unified Narrative of the Web of Agents
Tatiana Petrova, Boris Bliznioukov, Aleksandr Puzikov, Radu State

Toward the Autonomous AI Doctor: Quantitative Benchmarking of an Autonomous Agentic AI Versus Board-Certified Clinicians in a Real World Setting
Hashim Hayat, Maksim Kudrautsau, Evgeniy Makarov, Vlad Melnichenko, Tim Tsykunou, Piotr Varaksin, Matt Pavelle, Adam Z. Oskowitz
https://arxiv.org/abs/2507.22902

Toward the Autonomous AI Doctor: Quantitative Benchmarking of an Autonomous Agentic AI Versus Board-Certified Clinicians in a Real World Setting
Background: Globally we face a projected shortage of 11 million healthcare practitioners by 2030, and administrative burden consumes 50% of clinical time. Artificial intelligence (AI) has the potential to help alleviate these problems. However, no end-to-end autonomous large language model (LLM)-based AI system has been rigorously evaluated in real-world clinical practice. In this study, we evaluated whether a multi-agent LLM-based AI framework can function autonomously as an AI doctor in a vir…

FlexNGIA 2.0: Redesigning the Internet with Agentic AI - Protocols, Services, and Traffic Engineering Designed, Deployed, and Managed by AI
Mohamed Faten Zhani, Younes Korbi, Yamen Mkadem
https://arxiv.org/abs/2509.02124

FlexNGIA 2.0: Redesigning the Internet with Agentic AI - Protocols, Services, and Traffic Engineering Designed, Deployed, and Managed by AI
The escalating demands of immersive communications, alongside advances in network softwarization and AI-driven cognition and generative reasoning, create a pivotal opportunity to rethink and reshape the future Internet. In this context, we introduce in this paper, FlexNGIA 2.0, an Agentic AI-driven Internet architecture that leverages LLM-based AI agents to autonomously orchestrate, configure, and evolve the network. These agents can, at runtime, perceive, reason, coordinate among themselves to…

AI use cases introduced by Rob Finn from EMBL-EBI, as pointed out in his #CORDI2025 keynote "Delivering life science data resources in a world of growing data and impacts from AI"
https://www.nfdi.de/cordi-2025/keynotes/

Agentic-AI Healthcare: Multilingual, Privacy-First Framework with MCP Agents
Mohammed A. Shehab
https://arxiv.org/abs/2510.02325 https://arxiv.org/pdf/2510…

Agentic-AI Healthcare: Multilingual, Privacy-First Framework with MCP Agents
This paper introduces Agentic-AI Healthcare, a privacy-aware, multilingual, and explainable research prototype developed as a single-investigator project. The system leverages the emerging Model Context Protocol (MCP) to orchestrate multiple intelligent agents for patient interaction, including symptom checking, medication suggestions, and appointment scheduling. The platform integrates a dedicated Privacy and Compliance Layer that applies role-based access control (RBAC), AES-GCM field-level e…

Every friggin' day on here. "hey my company is hiring!"
I look at the job posting and...

Guard [.] io says a new era of scam complexity is on the way because AI-powered browsers can interact with phishing pages and malicious prompts without human detection.
https://guard.io/labs/scamlexity-we-put-agentic-ai-browsers-to-t…

"Scamlexity": When Agentic AI Browsers Get Scammed
We Put Agentic AI Browsers to the Test - They Clicked, They Paid, They Failed

Maisa AI, which offers an enterprise agentic automation service that uses a proprietary system to limit hallucinations, raised $25M seed led by Creandum (Anna Heim/TechCrunch)
https://techcrunch.com/2025/08/27/maisa-ai-gets-25m-to-fix-enterprise-ais…

Maisa AI gets $25M to fix enterprise AI's 95% failure rate | TechCrunch
Maisa AI is built on the premise that enterprise automation requires accountable AI agents, not opaque black boxes.

RAG has revolutionised AI by merging search and generation. Agentic behaviour takes this search to the next level by enabling LLMs to make decisions and call tools. At Berlin Buzzwords 2025, Bilge Yücel discussed how agentic behaviour enhances pipelines, what it means for a system to act as an 'agent', and core concepts such as routing, tool calling and reasoning, along with a live demo.
Watch the full session: #bbuzz returns on 7-9 June 2026: https://tickets.plainschwarz.com/bbuzz26/c/uIWaci8Cm/

heise | heise Update vom 19. September 2025: Lesetipps fürs Wochenende
Der wöchentliche Newsletter von heise dieses Mal zu PC-Hardwareprobleme lösen, iOS 26 & macOS 26, Bluetooth-Tracker, Agentic AI und den neuen Bildgeneratoren.

ACT: Agentic Classification Tree
Vincent Grari, Tim Arni, Thibault Laugel, Sylvain Lamprier, James Zou, Marcin Detyniecki
https://arxiv.org/abs/2509.26433 https://

ACT: Agentic Classification Tree
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 rules, but they are restricted to structured tabular data and cannot operate directly on unstructured inputs such as text. In practice, large language models (LLMs) are widely used for such data, yet prompting strategies such as chain-of-thought or prompt op…

BioinfoMCP: A Unified Platform Enabling MCP Interfaces in Agentic Bioinformatics
Florensia Widjaja, Zhangtianyi Chen, Juexiao Zhou
https://arxiv.org/abs/2510.02139 https://

BioinfoMCP: A Unified Platform Enabling MCP Interfaces in Agentic Bioinformatics
Bioinformatics tools are essential for complex computational biology tasks, yet their integration with emerging AI-agent frameworks is hindered by incompatible interfaces, heterogeneous input-output formats, and inconsistent parameter conventions. The Model Context Protocol (MCP) provides a standardized framework for tool-AI communication, but manually converting hundreds of existing and rapidly growing specialized bioinformatics tools into MCP-compliant servers is labor-intensive and unsustain…

Agentic AI Empowered Multi-UAV Trajectory Optimization in Low-Altitude Economy Networks
Feibo Jiang, Li Dong, Xitao Pan, Kezhi Wang, Cunhua Pan
https://arxiv.org/abs/2508.16379 …

Agentic AI Empowered Multi-UAV Trajectory Optimization in Low-Altitude Economy Networks
This paper proposes a novel Agentic Retrieval-augmented generation with Mamba-Attention Integrated Transformer (ARMAIT) framework for multi-Unmanned Aerial Vehicle (UAV) trajectory optimization. The framework is built upon Large Language Models (LLMs), incorporating Retrieval-Augmented Generation (RAG) empowered by Agentic AI and integrated with a UAV-specific knowledge base. Through the Agentic RAG, the LLM autonomously interprets high-level task requirements and identifies the key components …

🤦‍♂️ https://brave.com/blog/comet-prompt-injection/

Agentic Browser Security: Indirect Prompt Injection in Perplexity Comet | Brave
The attack we developed shows that traditional Web security assumptions don't hold for agentic AI, and that we need new security and privacy architectures for agentic browsing.

Crosslisted article(s) found for astro-ph.CO. https://arxiv.org/list/astro-ph.CO/new
[1/1]:
- ArgoLOOM: agentic AI for fundamental physics from quarks to cosmos
S. D. Bakshi, et al.

🚀 Welcome GLM-4.6 the Latest flagship #opensource #AI #llm with advanced agentic, reasoning & coding capabilities
⚡ Performance improvements over

from my link log —
Cracking the Vault: flaws in authentication, identity, and authorization in HashiCorp Vault.
https://cyata.ai/blog/cracking-the-vault-how-we-found-zero-day-flaws-in-authe…

Cracking the Vault: how we found zero-day flaws in authentication, identity, and authorization in HashiCorp Vault - Cyata | The Control Plane for Agentic Identity
Introduction: when the trust model can’t be trusted Secrets vaults are the backbone of digital infrastructure. They store the credentials, tokens, and certificates that govern access to systems, services, APIs, and data. They’re not just a part of the trust model, they are the trust model. In other words, if your vault is compromised, your […]

The latest large opensource AI model from China.
Kimi-K2
#AI #china #KimiK2

InstaLILY, whose industry-specific AI agents called InstaWorkers integrate with legacy systems, raised $25M from Insight Partners (Mike Wheatley/SiliconANGLE)
https://siliconangle.com/2025/08/27/instalily-gets-25m-accelerate-industr…

InstaLILY gets $25M to accelerate industry automation with agentic AI teammates - SiliconANGLE
InstaLILY gets $25M to accelerate industry automation with agentic AI teammates - SiliconANGLE

LLM Agent Meets Agentic AI: Can LLM Agents Simulate Customers to Evaluate Agentic-AI-based Shopping Assistants?
Lu Sun, Shihan Fu, Bingsheng Yao, Yuxuan Lu, Wenbo Li, Hansu Gu, Jiri Gesi, Jing Huang, Chen Luo, Dakuo Wang
https://arxiv.org/abs/2509.21501

LLM Agent Meets Agentic AI: Can LLM Agents Simulate Customers to Evaluate Agentic-AI-based Shopping Assistants?
Agentic AI is emerging, capable of executing tasks through natural language, such as Copilot for coding or Amazon Rufus for shopping. Evaluating these systems is challenging, as their rapid evolution outpaces traditional human evaluation. Researchers have proposed LLM Agents to simulate participants as digital twins, but it remains unclear to what extent a digital twin can represent a specific customer in multi-turn interaction with an agentic AI system. In this paper, we recruited 40 human par…

Agentic AI promises a swift revolution for cybersecurity defenders, with one expert calling it a "Cambrian explosion" and another likening it to "the fastest train ever made."
But it's a technology still in its infancy, and other experts caution CISOs to take it slow until the kinks can be worked out.
Check out my latest CSO piece on agentic AI for more details. Thanks to Jimmy Mesta of RAD Security, Andres Riancho and Hillai Ben-Sasson of Wiz, Ben Seri of…

Agentic AI promises a cybersecurity revolution — with asterisks
Experts say agentic AI will rapidly change cybersecurity, freeing up talent to focus on more dynamic work. But with AI agents still in their infancy, they also urge CISOs to ask a lot of questions before committing to this new security paradigm.

Microsoft Edge adds Copilot Mode, an experimental feature that tries to make browsing an agentic AI experience, even anticipating links to click, free for now (Zac Bowden/Windows Central)
https://www.windowscentral.com/microsoft/micros…

Microsoft revolutionizes Edge as an AI-powered web browser with new experimental 'Copilot Mode' — but it won't be free forever
Copilot Mode in Microsoft Edge is a new experimental feature that transforms the browser into an agentic AI experience, but it's only free for a limited time.

PANDA: Towards Generalist Video Anomaly Detection via Agentic AI Engineer
Zhiwei Yang, Chen Gao, Mike Zheng Shou
https://arxiv.org/abs/2509.26386 https://a…

PANDA: Towards Generalist Video Anomaly Detection via Agentic AI Engineer
Video anomaly detection (VAD) is a critical yet challenging task due to the complex and diverse nature of real-world scenarios. Previous methods typically rely on domain-specific training data and manual adjustments when applying to new scenarios and unseen anomaly types, suffering from high labor costs and limited generalization. Therefore, we aim to achieve generalist VAD, i.e., automatically handle any scene and any anomaly types without training data or human involvement. In this work, we p…

DIRF: A Framework for Digital Identity Protection and Clone Governance in Agentic AI Systems
Hammad Atta, Muhammad Zeeshan Baig, Yasir Mehmood, Nadeem Shahzad, Ken Huang, Muhammad Aziz Ul Haq, Muhammad Awais, Kamal Ahmed, Anthony Green
https://arxiv.org/abs/2508.01997

DIRF: A Framework for Digital Identity Protection and Clone Governance in Agentic AI Systems
The rapid advancement and widespread adoption of generative artificial intelligence (AI) pose significant threats to the integrity of personal identity, including digital cloning, sophisticated impersonation, and the unauthorized monetization of identity-related data. Mitigating these risks necessitates the development of robust AI-generated content detection systems, enhanced legal frameworks, and ethical guidelines. This paper introduces the Digital Identity Rights Framework (DIRF), a structu…

Israeli customer service automation company Nice acquires Cognigy, which develops a conversational and agentic AI platform, for $955M, set to close in Q4 2025 (Shiri Habib-Valdhorn/Globes)
https://en.globes.co.il/en/article-nice-acquires-ai-co-cognigy-…

Nice acquires AI co Cognigy for $955m
The acquisition combines Nice's purpose built customer service AI platform with Cognigy's conversational and agentic platform, which will enable organizations to accelerate AI adoption in customer experience.

Imagining Design Workflows in Agentic AI Futures
Samangi Wadinambiarachchi, Jenny Waycott, Yvonne Rogers, Greg Wadley
https://arxiv.org/abs/2509.20731 https://

Imagining Design Workflows in Agentic AI Futures
As designers become familiar with Generative AI, a new concept is emerging: Agentic AI. While generative AI produces output in response to prompts, agentic AI systems promise to perform mundane tasks autonomously, potentially freeing designers to focus on what they love: being creative. But how do designers feel about integrating agentic AI systems into their workflows? Through design fiction, we investigated how designers want to interact with a collaborative agentic AI platform. Ten professio…

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN
Abdelaziz Salama, Zeinab Nezami, Mohammed M. H. Qazzaz, Maryam Hafeez, Syed Ali Raza Zaidi
https://arxiv.org/abs/2507.21696

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN
The deployment of AI agents within legacy Radio Access Network (RAN) infrastructure poses significant safety and reliability challenges for future 6G networks. This paper presents a novel Edge AI framework for autonomous network optimisation in Open RAN environments, addressing these challenges through three core innovations: (1) a persona-based multi-tools architecture enabling distributed, context-aware decision-making; (2) proactive anomaly detection agent powered by traffic predictive tool;…

FaMA: LLM-Empowered Agentic Assistant for Consumer-to-Consumer Marketplace
Yineng Yan, Xidong Wang, Jin Seng Cheng, Ran Hu, Wentao Guan, Nahid Farahmand, Hengte Lin, Yue Li
https://arxiv.org/abs/2509.03890

FaMA: LLM-Empowered Agentic Assistant for Consumer-to-Consumer Marketplace
The emergence of agentic AI, powered by Large Language Models (LLMs), marks a paradigm shift from reactive generative systems to proactive, goal-oriented autonomous agents capable of sophisticated planning, memory, and tool use. This evolution presents a novel opportunity to address long-standing challenges in complex digital environments. Core tasks on Consumer-to-Consumer (C2C) e-commerce platforms often require users to navigate complex Graphical User Interfaces (GUIs), making the experience…

Building Information Models to Robot-Ready Site Digital Twins (BIM2RDT): An Agentic AI Safety-First Framework
Reza Akhavian, Mani Amani, Johannes Mootz, Robert Ashe, Behrad Beheshti
https://arxiv.org/abs/2509.20705

Building Information Models to Robot-Ready Site Digital Twins (BIM2RDT): An Agentic AI Safety-First Framework
The adoption of cyber-physical systems and jobsite intelligence that connects design models, real-time site sensing, and autonomous field operations can dramatically enhance digital management in the construction industry. This paper introduces BIM2RDT (Building Information Models to Robot-Ready Site Digital Twins), an agentic artificial intelligence (AI) framework designed to transform static Building Information Modeling (BIM) into dynamic, robot-ready digital twins (DTs) that prioritize safe…

FalseCrashReducer: Mitigating False Positive Crashes in OSS-Fuzz-Gen Using Agentic AI
Paschal C. Amusuo, Dongge Liu, Ricardo Andres Calvo Mendez, Jonathan Metzman, Oliver Chang, James C. Davis
https://arxiv.org/abs/2510.02185

FalseCrashReducer: Mitigating False Positive Crashes in OSS-Fuzz-Gen Using Agentic AI
Fuzz testing has become a cornerstone technique for identifying software bugs and security vulnerabilities, with broad adoption in both industry and open-source communities. Directly fuzzing a function requires fuzz drivers, which translate random fuzzer inputs into valid arguments for the target function. Given the cost and expertise required to manually develop fuzz drivers, methods exist that leverage program analysis and Large Language Models to automatically generate these drivers. However…

Policy Design in Zero-Trust Distributed Networks: Challenges and Solutions
Fannya R. Sandjaja, Ayesha A. Majeed, Abdullah Abdullah, Gyan Wickremasinghe, Karen Rafferty, Vishal Sharma
https://arxiv.org/abs/2508.04526

Policy Design in Zero-Trust Distributed Networks: Challenges and Solutions
Traditional security architectures are becoming more vulnerable to distributed attacks due to significant dependence on trust. This will further escalate when implementing agentic AI within the systems, as more components must be secured over a similar distributed space. These scenarios can be observed in consumer technologies, such as the dense Internet of things (IoT). Here, zero-trust architecture (ZTA) can be seen as a potential solution, which relies on a key principle of not giving users …

Adaptive Monitoring and Real-World Evaluation of Agentic AI Systems
Manish Shukla
https://arxiv.org/abs/2509.00115 https://arxiv.org/pdf/2509.00115

Adaptive Monitoring and Real-World Evaluation of Agentic AI Systems
Agentic artificial intelligence (AI) -- multi-agent systems that combine large language models with external tools and autonomous planning -- are rapidly transitioning from research laboratories into high-stakes domains. Our earlier "Basic" paper introduced a five-axis framework and proposed preliminary metrics such as goal drift and harm reduction but did not provide an algorithmic instantiation or empirical evidence. This "Advanced" sequel fills that gap. First, we revisit recent benchmarks a…

AppZen, which builds AI-powered tools to automate finance functions, raised a $180M Series D led by Riverwood Capital, bringing its total funding to $290M (Mary Ann Azevedo/Crunchbase News)
https://news.crunchbase.com/fintech/agentic-ai-startup-appzen-seriesd/…

With Amazon And Salesforce As Customers, Agentic AI Startup AppZen Lands $180M To ‘Transform’ Finance...
AppZen, which has built an agentic AI platform for finance teams, has raised $180 million in a Series D round, the company told Crunchbase News. Riverwood Capital led the growth financing round.

Agentic Privacy-Preserving Machine Learning
Mengyu Zhang, Zhuotao Liu, Jingwen Huang, Xuanqi Liu
https://arxiv.org/abs/2508.02836 https://arxiv.org/pdf/250…

Agentic Privacy-Preserving Machine Learning
Privacy-preserving machine learning (PPML) is critical to ensure data privacy in AI. Over the past few years, the community has proposed a wide range of provably secure PPML schemes that rely on various cryptography primitives. However, when it comes to large language models (LLMs) with billions of parameters, the efficiency of PPML is everything but acceptable. For instance, the state-of-the-art solution for confidential LLM inference represents at least 10,000-fold slower performance compared…

Google rolls out AI Mode to 180 countries and territories in English, after testing in the US, UK, and India, and plans to add more languages and regions "soon" (Abner Li/9to5Google)
https://9to5google.com/2025/08/21/google-ai-mode-countries-agentic/

Google AI Mode expanding to 180 countries, getting agentic restaurant finder, more
Google is now bringing AI Mode to many more countries around the world, while AI Ultra subscribers will get to use an agentic capability.

Learning to Lead Themselves: Agentic AI in MAS using MARL
Ansh Kamthan
https://arxiv.org/abs/2510.00022 https://arxiv.org/pdf/2510.00022

Learning to Lead Themselves: Agentic AI in MAS using MARL
As autonomous systems move from prototypes to real deployments, the ability of multiple agents to make decentralized, cooperative decisions becomes a core requirement. This paper examines how agentic artificial intelligence, agents that act independently, adaptively and proactively can improve task allocation and coordination in multi-agent systems, with primary emphasis on drone delivery and secondary relevance to warehouse automation. We formulate the problem in a cooperative multi-agent rein…

How to stop AI agents going rogue
https://www.bbc.com/news/articles/cq87e0dwj25o?at_medium=RSS&at_campaign=rss

How to stop AI agents going rogue
Agentic AI is taking decisions and acting on behalf of users, but how to stop that going wrong?

How can AI agents support journalists' work? An experiment with designing an LLM-driven intelligent reporting system
Vasileios Maltezos, Roman Kyrychenko, Aleksi Knuutila
https://arxiv.org/abs/2510.01193

How can AI agents support journalists' work? An experiment with designing an LLM-driven intelligent reporting system
The integration of artificial intelligence into journalistic practices represents a transformative shift in how news is gathered, analyzed, and disseminated. Large language models (LLMs), particularly those with agentic capabilities, offer unprecedented opportunities for enhancing journalistic workflows while simultaneously presenting complex challenges for newsroom integration. This research explores how agentic LLMs can support journalists' workflows, based on insights from journalist intervi…

EvoluteIQ, which offers a low-code AI platform for companies to design, deploy, and scale business processes, raised $53M led by Baird Capital (Tamara Djurickovic/Tech.eu)
https://tech.eu/2025/09/17/evoluteiq-raises-53m-led-by-baird-capi…

EvoluteIQ raises $53M led by Baird Capital to scale its agentic AI platform
EvoluteIQ, a native AI platform, secured $53 million in minority growth capital from Baird Capital to accelerate global expansion and strengthen its leadership in enterprise-grade agentic AI automation. Baird Capital’s Daina Spedding and Mark Donnelly will join the EvoluteIQ Board of Directors.Founded in 2019, EvoluteIQ develops the EIQ platform for automating complex business processes. Built on its Agentic Mesh Architecture (aMa) and an AI Workbench, EIQ orchestrates end-to-end workflo…

"Your AI, My Shell": Demystifying Prompt Injection Attacks on Agentic AI Coding Editors
Yue Liu, Yanjie Zhao, Yunbo Lyu, Ting Zhang, Haoyu Wang, David Lo
https://arxiv.org/abs/2509.22040

"Your AI, My Shell": Demystifying Prompt Injection Attacks on Agentic AI Coding Editors
Agentic AI coding editors driven by large language models have recently become more popular due to their ability to improve developer productivity during software development. Modern editors such as Cursor are designed not just for code completion, but also with more system privileges for complex coding tasks (e.g., run commands in the terminal, access development environments, and interact with external systems). While this brings us closer to the "fully automated programming" dream, it also r…

ToolBrain: A Flexible Reinforcement Learning Framework for Agentic Tools
Quy Minh Le, Minh Sao Khue Luu, Khanh-Tung Tran, Duc-Hai Nguyen, Hoang-Quoc-Viet Pham, Quan Le, Hoang Thanh Lam, Hoang D. Nguyen
https://arxiv.org/abs/2510.00023

ToolBrain: A Flexible Reinforcement Learning Framework for Agentic Tools
Effective tool use is essential for agentic AI, yet training agents to utilize tools remains challenging due to manually designed rewards, limited training data, and poor multi-tool selection, resulting in slow adaptation, wasted computational resources, and suboptimal performance. We introduce ToolBrain, a lightweight and user-friendly framework for coaching tool use in agentic models with flexible reinforcement learning (RL), easing the barriers for researchers and practitioners to adapt LLM-…

Agentic AI for Software: thoughts from Software Engineering community
Abhik Roychoudhury
https://arxiv.org/abs/2508.17343 https://arxiv.org/pdf/2508.17343

Agentic AI for Software: thoughts from Software Engineering community
AI agents have recently shown significant promise in software engineering. Much public attention has been transfixed on the topic of code generation from Large Language Models (LLMs) via a prompt. However, software engineering is much more than programming, and AI agents go far beyond instructions given by a prompt. At the code level, common software tasks include code generation, testing, and program repair. Design level software tasks may include architecture exploration, requirements under…

Circuit & Chisel, whose ATXP protocol enables AI agents to make autonomous payments, raised a $19.2M seed led by Primary Venture Partners and ParaFi (Leo Schwartz/Fortune)
https://fortune.com/2025/09/22/stripe-crypto-alum-agentic-ai-payments-cir…

Stripe crypto alum raise $19.2 million to power agentic payments through ATXP protocol
ATXP wants to create the first useful generation of AI agents through its HTTP-like protocol.

The Basic B*** Effect: The Use of LLM-based Agents Reduces the Distinctiveness and Diversity of People's Choices
Sandra C. Matz, C. Blaine Horton, Sofie Goethals
https://arxiv.org/abs/2509.02910

The Basic B*** Effect: The Use of LLM-based Agents Reduces the Distinctiveness and Diversity of People's Choices
Large language models (LLMs) increasingly act on people's behalf: they write emails, buy groceries, and book restaurants. While the outsourcing of human decision-making to AI can be both efficient and effective, it raises a fundamental question: how does delegating identity-defining choices to AI reshape who people become? We study the impact of agentic LLMs on two identity-relevant outcomes: interpersonal distinctiveness - how unique a person's choices are relative to others - and intrapersona…

AutoCodeSherpa: Symbolic Explanations in AI Coding Agents
Sungmin Kang, Haifeng Ruan, Abhik Roychoudhury
https://arxiv.org/abs/2507.22414 https://arxiv.org…

AutoCodeSherpa: Symbolic Explanations in AI Coding Agents
Large Language Model (LLM) agents autonomously use external tools on top of one or more LLMs to accomplish specific tasks. Lately LLM agents for software engineering tasks have become popular. These agents can benefit from the use of program analysis tools working on program representations. This is demonstrated by existing agentic AI solutions such as AutoCodeRover or SpecRover which perform automated program repair. Specifically the goal of these works is to use program analysis to improve th…

Claude Code, Gemini CLI, and CLI Codex, terminal-based AI tools launched since February, have surprisingly gained ground on AI code editors with traditional UIs (Russell Brandom/TechCrunch)
https://techcrunch.com/2025/07/15/ai-coding-tools-a…

AI coding tools are shifting to a surprising place: the terminal | TechCrunch
For years, code-editing tools like Cursor, Windsurf, and GitHub’s Copilot have been the standard for AI-powered software development. But as agentic AI grows more powerful and vibe-coding takes off, a subtle shift has changed how AI systems are interacting with software. Instead of working on code, they’re increasingly interacting directly with the shell of whatever system they’re installed in. It’s a significant change in how AI-powered software development happens – and despite the …

AWorld: Orchestrating the Training Recipe for Agentic AI
Chengyue Yu, Siyuan Lu, Chenyi Zhuang, Dong Wang, Qintong Wu, Zongyue Li, Runsheng Gan, Chunfeng Wang, Siqi Hou, Gaochi Huang, Wenlong Yan, Lifeng Hong, Aohui Xue, Yanfeng Wang, Jinjie Gu, David Tsai, Tao Lin
https://arxiv.org/abs/2508.20404 …

AWorld: Orchestrating the Training Recipe for Agentic AI
The learning from practice paradigm is crucial for developing capable Agentic AI systems, yet it is severely hampered by inefficient experience generation, a bottleneck especially pronounced in complex benchmarks like GAIA. To address this, we introduce AWorld, an open-source system engineered for large-scale agent-environment interaction. By distributing tasks across a cluster, AWorld accelerates experience collection by 14.6x compared to standard single-node, sequential execution. This critic…

From Passive Tool to Socio-cognitive Teammate: A Conceptual Framework for Agentic AI in Human-AI Collaborative Learning
Lixiang Yan
https://arxiv.org/abs/2508.14825 https://

From Passive Tool to Socio-cognitive Teammate: A Conceptual Framework for Agentic AI in Human-AI Collaborative Learning
The role of Artificial Intelligence (AI) in education is undergoing a rapid transformation, moving beyond its historical function as an instructional tool towards a new potential as an active participant in the learning process. This shift is driven by the emergence of agentic AI, autonomous systems capable of proactive, goal-directed action. However, the field lacks a robust conceptual framework to understand, design, and evaluate this new paradigm of human-AI interaction in learning. This pap…

An Empirical Study of Testing Practices in Open Source AI Agent Frameworks and Agentic Applications
Mohammed Mehedi Hasan, Hao Li, Emad Fallahzadeh, Gopi Krishnan Rajbahadur, Bram Adams, Ahmed E. Hassan
https://arxiv.org/abs/2509.19185

AI Agentic Vulnerability Injection And Transformation with Optimized Reasoning
Amine Lbath, Massih-Reza Amini, Aurelien Delaitre, Vadim Okun
https://arxiv.org/abs/2508.20866 htt…

AI Agentic Vulnerability Injection And Transformation with Optimized Reasoning
The increasing complexity of software systems and the sophistication of cyber-attacks have underscored the critical need for effective automated vulnerability detection and repair systems. Traditional methods, such as static program analysis, face significant challenges related to scalability, adaptability, and high false-positive and false-negative rates. AI-driven approaches, particularly those using machine learning and deep learning models, show promise but are heavily reliant on the qualit…

SafeEvalAgent: Toward Agentic and Self-Evolving Safety Evaluation of LLMs
Yixu Wang, Xin Wang, Yang Yao, Xinyuan Li, Yan Teng, Xingjun Ma, Yingchun Wang
https://arxiv.org/abs/2509.26100

SafeEvalAgent: Toward Agentic and Self-Evolving Safety Evaluation of LLMs
The rapid integration of Large Language Models (LLMs) into high-stakes domains necessitates reliable safety and compliance evaluation. However, existing static benchmarks are ill-equipped to address the dynamic nature of AI risks and evolving regulations, creating a critical safety gap. This paper introduces a new paradigm of agentic safety evaluation, reframing evaluation as a continuous and self-evolving process rather than a one-time audit. We then propose a novel multi-agent framework SafeE…

Researchers detail an indirect prompt injection flaw in Perplexity's Comet AI browser, letting attackers manipulate it into performing unauthorized actions (Brave)
https://brave.com/blog/comet-prompt-injection/

Agentic Browser Security: Indirect Prompt Injection in Perplexity Comet | Brave
The attack we developed shows that traditional Web security assumptions don't hold for agentic AI, and that we need new security and privacy architectures for agentic browsing.

OpenAI is open sourcing the Agentic Commerce Protocol, a standard for AI commerce that powers its Instant Checkout feature and was co-developed with Stripe (Sabrina Ortiz/ZDNET)
https://www.zdnet.com/article/chatgpt-just

ChatGPT can buy stuff for you now - forever changing online shopping
Transactions between AI agents are on the rise. Here's how to try ChatGPT's new Instant Checkout feature.

MobiLLM: An Agentic AI Framework for Closed-Loop Threat Mitigation in 6G Open RANs
Prakhar Sharma, Haohuang Wen, Vinod Yegneswaran, Ashish Gehani, Phillip Porras, Zhiqiang Lin
https://arxiv.org/abs/2509.21634

MobiLLM: An Agentic AI Framework for Closed-Loop Threat Mitigation in 6G Open RANs
The evolution toward 6G networks is being accelerated by the Open Radio Access Network (O-RAN) paradigm -- an open, interoperable architecture that enables intelligent, modular applications across public telecom and private enterprise domains. While this openness creates unprecedented opportunities for innovation, it also expands the attack surface, demanding resilient, low-cost, and autonomous security solutions. Legacy defenses remain largely reactive, labor-intensive, and inadequate for the …

EvoEmo: Towards Evolved Emotional Policies for LLM Agents in Multi-Turn Negotiation
Yunbo Long, Liming Xu, Lukas Beckenbauer, Yuhan Liu, Alexandra Brintrup
https://arxiv.org/abs/2509.04310

EvoEmo: Towards Evolved Emotional Policies for LLM Agents in Multi-Turn Negotiation
Recent research on Chain-of-Thought (CoT) reasoning in Large Language Models (LLMs) has demonstrated that agents can engage in \textit{complex}, \textit{multi-turn} negotiations, opening new avenues for agentic AI. However, existing LLM agents largely overlook the functional role of emotions in such negotiations, instead generating passive, preference-driven emotional responses that make them vulnerable to manipulation and strategic exploitation by adversarial counterparts. To address this gap,…

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/7]:
- AT-CXR: Uncertainty-Aware Agentic Triage for Chest X-rays
Xueyang Li, Mingze Jiang, Gelei Xu, Jun Xia, Mengzhao Jia, Danny Chen, Yiyu Shi

Securing Agentic AI: Threat Modeling and Risk Analysis for Network Monitoring Agentic AI System
Pallavi Zambare, Venkata Nikhil Thanikella, Ying Liu
https://arxiv.org/abs/2508.10043

Securing Agentic AI: Threat Modeling and Risk Analysis for Network Monitoring Agentic AI System
When combining Large Language Models (LLMs) with autonomous agents, used in network monitoring and decision-making systems, this will create serious security issues. In this research, the MAESTRO framework consisting of the seven layers threat modeling architecture in the system was used to expose, evaluate, and eliminate vulnerabilities of agentic AI. The prototype agent system was constructed and implemented, using Python, LangChain, and telemetry in WebSockets, and deployed with inference, m…

MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems
Sri Ram Macharla, Sridhar Murthy J, Anjaneyulu Pasala
https://arxiv.org/abs/2508.21307

MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems
MultiFluxAI is an innovative AI platform developed to address the challenges of managing and integrating vast, disparate data sources in product engineering across application domains. It addresses both current and new service related queries that enhance user engagement in the digital ecosystem. This platform leverages advanced AI techniques, such as Generative AI, vectorization, and agentic orchestration to provide dynamic and context-aware responses to complex user queries.

ServiceNow reports Q2 revenue up 22.5% YoY to $3.22B, vs. $3.12B est., and net income up 47% YoY to $385M, fueled by AI growth; NOW jumps 7% after hours (Samantha Subin/CNBC)
https://www.cnbc.com/2025/07/23/servicenow-now-q2-earnings-2025.html

ServiceNow lifts guidance on AI growth
"Every business process in every industry is being refactored for agentic AI," said ServiceNow chair and CEO Bill McDermott in a release.

Magentic-UI: Towards Human-in-the-loop Agentic Systems
Hussein Mozannar, Gagan Bansal, Cheng Tan, Adam Fourney, Victor Dibia, Jingya Chen, Jack Gerrits, Tyler Payne, Matheus Kunzler Maldaner, Madeleine Grunde-McLaughlin, Eric Zhu, Griffin Bassman, Jacob Alber, Peter Chang, Ricky Loynd, Friederike Niedtner, Ece Kamar, Maya Murad, Rafah Hosn, Saleema Amershi
http…

Magentic-UI: Towards Human-in-the-loop Agentic Systems
AI agents powered by large language models are increasingly capable of autonomously completing complex, multi-step tasks using external tools. Yet, they still fall short of human-level performance in most domains including computer use, software development, and research. Their growing autonomy and ability to interact with the outside world, also introduces safety and security risks including potentially misaligned actions and adversarial manipulation. We argue that human-in-the-loop agentic sy…

Goldman Sachs CTO Marco Argenti says the bank is "going to start augmenting our workforce with Devin", Cognition's AI coding assistant, as Wall Street adopts AI (Hugh Son/CNBC)
https://www.cnbc.com/2025/07/11/goldman-sachs-auto…

Goldman Sachs is piloting its first autonomous coder in major AI milestone for Wall Street
The arrival of agentic AI at Goldman Sachs, in which programs don't just help with tasks but execute complex jobs, signals a shift on Wall Street.

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[2/5]:
- Compliance Brain Assistant: Conversational Agentic AI for Assisting Compliance Tasks in Enterpris...
Zhu, Fang, Larson, Pochareddy, Rao, Zeng, Peng, Summer, Goncalves, Pudota, Robert

Agentic AI framework for End-to-End Medical Data Inference
Soorya Ram Shimgekar, Shayan Vassef, Abhay Goyal, Navin Kumar, Koustuv Saha
https://arxiv.org/abs/2507.18115 https://

Agentic AI framework for End-to-End Medical Data Inference
Building and deploying machine learning solutions in healthcare remains expensive and labor-intensive due to fragmented preprocessing workflows, model compatibility issues, and stringent data privacy constraints. In this work, we introduce an Agentic AI framework that automates the entire clinical data pipeline, from ingestion to inference, through a system of modular, task-specific agents. These agents handle both structured and unstructured data, enabling automatic feature selection, model se…

Microsoft Windows head Pavan Davuluri says the next Windows version will be more ambient, pervasive and multi-modal, with voice becoming more important (Zac Bowden/Windows Central)
https://www.windowscentral.com/microsoft/w

Microsoft's Windows lead says the next version of Windows will be "more ambient, pervasive, and multi-modal" as AI redefines the desktop interface
In a new video, Microsoft CVP and Windows boss Pavan Davuluri has teased that the future of Windows will consist of a truly ambient and multi-modal experience made possible by AI that will redefine our usage of computers.

AI-SearchPlanner: Modular Agentic Search via Pareto-Optimal Multi-Objective Reinforcement Learning
Lang Mei, Zhihan Yang, Chong Chen
https://arxiv.org/abs/2508.20368 https://

AI-SearchPlanner: Modular Agentic Search via Pareto-Optimal Multi-Objective Reinforcement Learning
Recent studies have explored integrating Large Language Models (LLMs) with search engines to leverage both the LLMs' internal pre-trained knowledge and external information. Specially, reinforcement learning (RL) has emerged as a promising paradigm for enhancing LLM reasoning through multi-turn interactions with search engines. However, existing RL-based search agents rely on a single LLM to handle both search planning and question-answering (QA) tasks in an end-to-end manner, which limits thei…

Moonshot's Kimi K2 uses a 1T-parameter MoE architecture with 32B active parameters and outperforms models like GPT-4.1 and DeepSeek-V3 on key benchmarks (Michael Nuñez/VentureBeat)
https://venturebeat.com/ai/moonshot-ais-kimi-k2-outperfor…

Moonshot AI’s Kimi K2 outperforms GPT-4 in key benchmarks — and it’s free
Chinese AI startup Moonshot releases open-source Kimi K2 model that outperforms OpenAI and Anthropic on coding tasks with breakthrough agentic capabilities and competitive pricing.

LLMZ : Contextual Prompt Whitelist Principles for Agentic LLMs
Tom Pawelek, Raj Patel, Charlotte Crowell, Noorbakhsh Amiri, Sudip Mittal, Shahram Rahimi, Andy Perkins
https://arxiv.org/abs/2509.18557

LLMZ+: Contextual Prompt Whitelist Principles for Agentic LLMs
Compared to traditional models, agentic AI represents a highly valuable target for potential attackers as they possess privileged access to data sources and API tools, which are traditionally not incorporated into classical agents. Unlike a typical software application residing in a Demilitarized Zone (DMZ), agentic LLMs consciously rely on nondeterministic behavior of the AI (only defining a final goal, leaving the path selection to LLM). This characteristic introduces substantial security ris…

Lumana, which integrates vision-language models and agentic AI into its video surveillance system, raised a $40M Series A led by Wing Venture Capital (Mike Wheatley/SiliconANGLE)
https://siliconangle.com/2025/07/29/lumana-gets-40m-build-intel…

Lumana gets $40M to build more intelligent video surveillance systems - SiliconANGLE
Lumana gets $40M to build more intelligent video surveillance systems - SiliconANGLE

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments
Nitish Jaipuria, Lorenzo Gatto, Zijun Kan, Shankey Poddar, Bill Cheung, Diksha Bansal, Ramanan Balakrishnan, Aviral Suri, Jose Estevez
https://arxiv.org/abs/2508.19932

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments
The proliferation of digital payment platforms has transformed commerce, offering unmatched convenience and accessibility globally. However, this growth has also attracted malicious actors, leading to a corresponding increase in sophisticated social engineering scams. These scams are often initiated and orchestrated on multiple surfaces outside the payment platform, making user and transaction-based signals insufficient for a complete understanding of the scam's methodology and underlying patte…

Agentic AI for Financial Crime Compliance
Henrik Axelsen, Valdemar Licht, Jan Damsgaard
https://arxiv.org/abs/2509.13137 https://arxiv.org/pdf/2509.13137…

Agentic AI for Financial Crime Compliance
The cost and complexity of financial crime compliance (FCC) continue to rise, often without measurable improvements in effectiveness. While AI offers potential, most solutions remain opaque and poorly aligned with regulatory expectations. This paper presents the design and deployment of an agentic AI system for FCC in digitally native financial platforms. Developed through an Action Design Research (ADR) process with a fintech firm and regulatory stakeholders, the system automates onboarding, m…