Tootfinder

Anthropic details how it built its multi-agent Claude Research system, claiming significant improvements in internal evaluations over single-agent systems (Anthropic)
https://www.anthropic.com/engineering/built-multi-agent-research-system

How we built our multi-agent research system
On the the engineering challenges and lessons learned from building Claude's Research system

Russian agent caught 'red-handed' planting explosives in Rivne apartment building, Ukraine's SBU says: https://benborges.xyz/2025/07/15/russian-agent-caught-redhanded-planting.html

WR Bond no longer faces charges, agent says https://www.espn.com/nfl/story/_/id/45980953/ex-texas-wr-isaiah-bond-no-longer-faces-charges-agent-says

KI-Update kompakt: V-Jepa-2, Sicherheitslücke in KI-Agent, Hirnfäule, Nvidia
Das "KI-Update" liefert werktäglich eine Zusammenfassung der wichtigsten KI-Entwicklungen.
https:/…

Man accused of hurling sandwich at federal agent in D.C. gets hit with felony assault charge (NBC News)
https://www.nbcnews.com/politics/politics-news/man-accused-hurling-sandwich-federal-agent-dc-gets-hit-felony-assault-rcna224921
http://www.memeorandum.com/250814/p35#a250814p35

Raiders free agent idea adds 5-time Pro Bowl wide receiver instead of relying on rookies https://www.sportingnews.com/us/nfl/las-vegas-raiders/news/raiders-free-agent-idea-amari-cooper…

A look at 10 AI agent startups from YC's first-ever spring Demo Day; the batch included 144 companies, 70 of which focused on agentic AI (Samantha Stokes/Business Insider)
https://africa.businessinsider.com/new

The 10 most exciting AI agent startups at Y Combinator's Demo Day for its first-ever spring cohort
Christmas came early for Y Combinator

Exploring Design of Multi-Agent LLM Dialogues for Research Ideation
Keisuke Ueda, Wataru Hirota, Takuto Asakura, Takahiro Omi, Kosuke Takahashi, Kosuke Arima, Tatsuya Ishigaki
https://arxiv.org/abs/2507.08350

Exploring Design of Multi-Agent LLM Dialogues for Research Ideation
Large language models (LLMs) are increasingly used to support creative tasks such as research idea generation. While recent work has shown that structured dialogues between LLMs can improve the novelty and feasibility of generated ideas, the optimal design of such interactions remains unclear. In this study, we conduct a comprehensive analysis of multi-agent LLM dialogues for scientific ideation. We compare different configurations of agent roles, number of agents, and dialogue depth to underst…

Good explanation of MCP and A2A.
#ai

If MCP is the USB-C of AI agents, A2A is their Ethernet
: Tell me, Mr. Smith ... what good is an agent if it's unable to speak?

Building a Code-Editing #Agent in 400 Lines of #Go Code 🤖
➰
🔧 Complete agent implementation requires only #LLM integration, loop structure & sufficient token allocation
🧵 👇

RAGulating Compliance: A Multi-Agent Knowledge Graph for Regulatory QA
Bhavik Agarwal, Hemant Sunil Jomraj, Simone Kaplunov, Jack Krolick, Viktoria Rojkova
https://arxiv.org/abs/2508.09893

RAGulating Compliance: A Multi-Agent Knowledge Graph for Regulatory QA
Regulatory compliance question answering (QA) requires precise, verifiable information, and domain-specific expertise, posing challenges for Large Language Models (LLMs). In this work, we present a novel multi-agent framework that integrates a Knowledge Graph (KG) of Regulatory triplets with Retrieval-Augmented Generation (RAG) to address these demands. First, agents build and maintain an ontology-free KG by extracting subject--predicate--object (SPO) triplets from regulatory documents and syst…

Jury nullification has never had a better shot than this absolutely absurd felony charge
https://www.axios.com/2025/08/14/trump-dc-federal-agent-sandwich-assault-charge

D.C. man accused of throwing sandwich at federal agent faces felony charges
The incident is alleged to have occurred after President Trump ordered an increased federal law enforcement presence in the city.

CS-Agent: LLM-based Community Search via Dual-agent Collaboration
Jiahao Hua, Long Yuan, Qingshuai Feng, Qiang Fang, Shan Huang
https://arxiv.org/abs/2508.09549 https://

CS-Agent: LLM-based Community Search via Dual-agent Collaboration
Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, yet their application to graph structure analysis, particularly in community search, remains underexplored. Community search, a fundamental task in graph analysis, aims to identify groups of nodes with dense interconnections, which is crucial for understanding the macroscopic structure of graphs. In this paper, we propose GraphCS, a comprehensive benchmark designed to evaluate the perfor…

Sheriff: Death of Elway's ex-agent an accident https://www.espn.com/nfl/story/_/id/45736921/sheriff-death-john-elway-former-agent-tragic-accident

ReqInOne: A Large Language Model-Based Agent for Software Requirements Specification Generation
Taohong Zhu, Lucas C. Cordeiro, Youcheng Sun
https://arxiv.org/abs/2508.09648 htt…

ReqInOne: A Large Language Model-Based Agent for Software Requirements Specification Generation
Software Requirements Specification (SRS) is one of the most important documents in software projects, but writing it manually is time-consuming and often leads to ambiguity. Existing automated methods rely heavily on manual analysis, while recent Large Language Model (LLM)-based approaches suffer from hallucinations and limited controllability. In this paper, we propose ReqInOne, an LLM-based agent that follows the common steps taken by human requirements engineers when writing an SRS to conve…

The Gestapo's most feared department: die Village People-Einheit

DatasetAgent: A Novel Multi-Agent System for Auto-Constructing Datasets from Real-World Images
Haoran Sun, Haoyu Bian, Shaoning Zeng, Yunbo Rao, Xu Xu, Lin Mei, Jianping Gou
https://arxiv.org/abs/2507.08648

DatasetAgent: A Novel Multi-Agent System for Auto-Constructing Datasets from Real-World Images
Common knowledge indicates that the process of constructing image datasets usually depends on the time-intensive and inefficient method of manual collection and annotation. Large models offer a solution via data generation. Nonetheless, real-world data are obviously more valuable comparing to artificially intelligence generated data, particularly in constructing image datasets. For this reason, we propose a novel method for auto-constructing datasets from real-world images by a multiagent colla…

Cowpox: Towards the Immunity of VLM-based Multi-Agent Systems
Yutong Wu, Jie Zhang, Yiming Li, Chao Zhang, Qing Guo, Nils Lukas, Tianwei Zhang
https://arxiv.org/abs/2508.09230 h…

Cowpox: Towards the Immunity of VLM-based Multi-Agent Systems
Vision Language Model (VLM)-based agents are stateful, autonomous entities capable of perceiving and interacting with their environments through vision and language. Multi-agent systems comprise specialized agents who collaborate to solve a (complex) task. A core security property is robustness, stating that the system should maintain its integrity under adversarial attacks. However, the design of existing multi-agent systems lacks the robustness consideration, as a successful exploit against o…

DC man charged with felony assault after hitting federal agent with Subway sandwich (Steven Nelson/New York Post)
https://nypost.com/2025/08/13/us-news/dc-man-sean-charles-dunn-charged-with-felony-assault-after-hitting-federal-agent-with-subway-sandwich/
http://www.memeorandum.com/250814/p76#a250814p76

Buyer's Agent Networks Podcast
Great Australian Pods Podcast Directory: #GreatAusPods

CRADLE: Conversational RTL Design Space Exploration with LLM-based Multi-Agent Systems
Lukas Krupp, Maximilian Sch\"offel, Elias Biehl, Norbert Wehn
https://arxiv.org/abs/2508.08709

CRADLE: Conversational RTL Design Space Exploration with LLM-based Multi-Agent Systems
This paper presents CRADLE, a conversational framework for design space exploration of RTL designs using LLM-based multi-agent systems. Unlike existing rigid approaches, CRADLE enables user-guided flows with internal self-verification, correction, and optimization. We demonstrate the framework with a generator-critic agent system targeting FPGA resource minimization using state-of-the-art LLMs. Experimental results on the RTLLM benchmark show that CRADLE achieves significant reductions in resou…

FROGENT: An End-to-End Full-process Drug Design Agent
Qihua Pan, Dong Xu, Jenna Xinyi Yao, Lijia Ma, Zexuan Zhu, Junkai Ji
https://arxiv.org/abs/2508.10760 https://

FROGENT: An End-to-End Full-process Drug Design Agent
Powerful AI tools for drug discovery reside in isolated web apps, desktop programs, and code libraries. Such fragmentation forces scientists to manage incompatible interfaces and specialized scripts, which can be a cumbersome and repetitive process. To address this issue, a Full-pROcess druG dEsign ageNT, named FROGENT, has been proposed. Specifically, FROGENT utilizes a Large Language Model and the Model Context Protocol to integrate multiple dynamic biochemical databases, extensible tool libr…

AWorld: Dynamic Multi-Agent System with Stable Maneuvering for Robust GAIA Problem Solving
Zhitian Xie, Qintong Wu, Chengyue Yu, Chenyi Zhuang, Jinjie Gu
https://arxiv.org/abs/2508.09889

AWorld: Dynamic Multi-Agent System with Stable Maneuvering for Robust GAIA Problem Solving
The rapid advancement of large language models (LLMs) has empowered intelligent agents to leverage diverse external tools for solving complex real-world problems. However, as agents increasingly depend on multiple tools, they encounter new challenges: extended contexts from disparate sources and noisy or irrelevant tool outputs can undermine system reliability and accuracy. These challenges underscore the necessity for enhanced stability in agent-based systems. To address this, we introduce dyn…

Kairos: Low-latency Multi-Agent Serving with Shared LLMs and Excessive Loads in the Public Cloud
Jinyuan Chen, Jiuchen Shi, Quan Chen, Minyi Guo
https://arxiv.org/abs/2508.06948

Kairos: Low-latency Multi-Agent Serving with Shared LLMs and Excessive Loads in the Public Cloud
Multi-agent applications utilize the advanced capabilities of large language models (LLMs) for intricate task completion through agent collaboration in a workflow. Under this situation, requests from different agents usually access the same shared LLM to perform different kinds of tasks, forcing the shared LLM to suffer excessive loads. However, existing works have low serving performance for these multi-agent applications, mainly due to the ignorance of inter-agent latency and resource differe…

Finding Common Ground: Using Large Language Models to Detect Agreement in Multi-Agent Decision Conferences
Selina Heller, Mohamed Ibrahim, David Antony Selby, Sebastian Vollmer
https://arxiv.org/abs/2507.08440

Finding Common Ground: Using Large Language Models to Detect Agreement in Multi-Agent Decision Conferences
Decision conferences are structured, collaborative meetings that bring together experts from various fields to address complex issues and reach a consensus on recommendations for future actions or policies. These conferences often rely on facilitated discussions to ensure productive dialogue and collective agreement. Recently, Large Language Models (LLMs) have shown significant promise in simulating real-world scenarios, particularly through collaborative multi-agent systems that mimic group in…

AURA: A Multi-Agent Intelligence Framework for Knowledge-Enhanced Cyber Threat Attribution
Nanda Rani, Sandeep Kumar Shukla
https://arxiv.org/abs/2506.10175

AURA: A Multi-Agent Intelligence Framework for Knowledge-Enhanced Cyber Threat Attribution
Effective attribution of Advanced Persistent Threats (APTs) increasingly hinges on the ability to correlate behavioral patterns and reason over complex, varied threat intelligence artifacts. We present AURA (Attribution Using Retrieval-Augmented Agents), a multi-agent, knowledge-enhanced framework for automated and interpretable APT attribution. AURA ingests diverse threat data including Tactics, Techniques, and Procedures (TTPs), Indicators of Compromise (IoCs), malware details, adversarial to…

Cowboys $3 Million Free Agent RB Predicted for ‘Career Year’ After Struggles https://heavy.com/sports/nfl/dallas-cowboys/running-back-javonte-williams-breakout-season/?adt_ei=[email]

This AI phone agent is playing an audible sound effect of a clackety mechanical keyboard as if someone is listening and typing.
I understand what they are trying to do, but it has the complete opposite effect on me. Whatever goon middle manager opted for this? I want them to suffer.
And the amount of typing that it pretends is ludicrously longer than the information provided. It's like an amplifier for my irritation.

webMCP: Efficient AI-Native Client-Side Interaction for Agent-Ready Web Design
D. Perera
https://arxiv.org/abs/2508.09171 https://arxiv.org/pdf/2508.09171

webMCP: Efficient AI-Native Client-Side Interaction for Agent-Ready Web Design
Current AI agents create significant barriers for users by requiring extensive processing to understand web pages, making AI-assisted web interaction slow and expensive. This paper introduces webMCP (Web Machine Context & Procedure), a client-side standard that embeds structured interaction metadata directly into web pages, enabling more efficient human-AI collaboration on existing websites. webMCP transforms how AI agents understand web interfaces by providing explicit mappings between page el…

Expert Incentives under Partially Contractible States
Zizhe Xia
https://arxiv.org/abs/2508.10170 https://arxiv.org/pdf/2508.10170

Expert Incentives under Partially Contractible States
I study whether and which expert incentives can be provided at what cost when the states of the world become non-contractible, but there is some noisy observation about the states that can be contracted upon. A principal hires an agent to acquire costly information about the states, but it is not possible to pay the agent based on the realized states. Instead, the principal has access to a noisy (Blackwell) experiment about the states, and can pay bonuses based on its realization. The agent is …

ChatGPT on the Road: Leveraging Large Language Model-Powered In-vehicle Conversational Agents for Safer and More Enjoyable Driving Experience
Yeana Lee Bond (Computer Science, Virginia Tech, Blacksburg, Virginia, USA), Mungyeong Choe (Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia, USA), Baker Kasim Hasan (Computer Science, Virginia Tech, Blacksburg, Virginia, USA), Arsh Siddiqui (Computer Science, Virginia Tech, Blacksburg, Virginia, USA), Myounghoon Jeon (Com…

ChatGPT on the Road: Leveraging Large Language Model-Powered In-vehicle Conversational Agents for Safer and More Enjoyable Driving Experience
Studies on in-vehicle conversational agents have traditionally relied on pre-scripted prompts or limited voice commands, constraining natural driver-agent interaction. To resolve this issue, the present study explored the potential of a ChatGPT-based in-vehicle agent capable of carrying continuous, multi-turn dialogues. Forty drivers participated in our experiment using a motion-based driving simulator, comparing three conditions (No agent, Pre-scripted agent, and ChatGPT-based agent) as a with…

Agent Orange
bot by @…
No laws were broken in the making of this bot: I wanted to make you smile, not pursue charges.
#satire #potus45

Raiders Named Fit for 6-Foot-4 Pro Bowl CB With Ties to Pete Carroll https://heavy.com/sports/nfl/las-vegas-raiders/tariq-woolen-free-agent-rumors-seahawks/?adt_ei=[email]

Kogaro: Stop #Kubernetes Silent Failures
https://kogaro.com/

Free agent RB/KR Nyheim Hines ready to put knee injury behind him after two years away: 'The story is in my hand' https://www.nfl.com/news/free-agent-rb-kr-nyheim-hines-ready-to-put-knee-injury-behind-h…

AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs
Florian Gr\"otschla, Luis M\"uller, Jan T\"onshoff, Mikhail Galkin, Bryan Perozzi
https://arxiv.org/abs/2507.08616

AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs
Large-language models (LLMs) have demonstrated powerful problem-solving capabilities, in particular when organized in multi-agent systems. However, the advent of such systems also raises several questions on the ability of a complex network of agents to effectively self-organize and collaborate. While measuring performance on standard reasoning benchmarks indicates how well multi-agent systems can solve reasoning tasks, it is unclear whether these systems are able to leverage their topology eff…

🚀 Demonstrates practical #AI agent development without complex abstractions or extensive engineering overhead
https://ampcode.com/how-to-build-an-agent

U.S. Sen. Alex Padilla on Thursday was handcuffed by officers and forcefully removed from Homeland Security Secretary Kristi Noem’s news conference in Los Angeles
as he tried to speak up about immigration raids that have led to protests in California and around the country.
Video shows a Secret Service agent on Noem’s security detail grabbing the California senator by his jacket and shoving him from the room
as he tried to speak up during the DHS secretary’s event.
…

Sen. Alex Padilla removed from Noem's press conference by security
Democratic California U.S. Sen. Alex Padilla has been forcefully removed Thursday by security officers from a news conference on immigration by Homeland Security Secretary Kristi Noem. Video shows a Secret Service special agent on Noem’s detail grabbing Padilla by his jacket and shoving him from the room as the senator struggles to catch his breath while identifying himself.“I’m Sen. Alex Padilla. I have questions for the secretary,” he shouted in a halting voice. He tries to push back …

Joint Beamforming with Extremely Large Scale RIS: A Sequential Multi-Agent A2C Approach
Zhi Chai, Jiajie Xu, Justin P Coon, Mohamed-Slim Alouini
https://arxiv.org/abs/2506.10815

Joint Beamforming with Extremely Large Scale RIS: A Sequential Multi-Agent A2C Approach
It is a challenging problem to jointly optimize the base station (BS) precoding matrix and the reconfigurable intelligent surface (RIS) phases simultaneously in a RIS-assisted multiple-user multiple-input-multiple-output (MU-MIMO) scenario when the size of the RIS becomes extremely large. In this paper, we propose a deep reinforcement learning algorithm called sequential multi-agent advantage actor-critic (A2C) to solve this problem. In addition, the discrete phase of RISs, imperfect channel st…

"If I wasn't an actor, I'd be a secret agent."
-Thornton Wilder
#acting #coaching #inspiration

LA man faces 8 years in prison for ‘spitting at an ICE agent’ after being charged with assaulting a federal employee | The Independent
https://www.the-independent.com/news/world/americas/crime/los-angeles-arrest-spitting-ice-agent-face-b2768986.html

A Fuzzy Supervisor Agent Design for Clinical Reasoning Assistance in a Multi-Agent Educational Clinical Scenario Simulation
Weibing Zheng, Laurah Turner, Jess Kropczynski, Murat Ozer, Seth Overla, Shane Halse
https://arxiv.org/abs/2507.05275

A Fuzzy Supervisor Agent Design for Clinical Reasoning Assistance in a Multi-Agent Educational Clinical Scenario Simulation
Assisting medical students with clinical reasoning (CR) during clinical scenario training remains a persistent challenge in medical education. This paper presents the design and architecture of the Fuzzy Supervisor Agent (FSA), a novel component for the Multi-Agent Educational Clinical Scenario Simulation (MAECSS) platform. The FSA leverages a Fuzzy Inference System (FIS) to continuously interpret student interactions with specialized clinical agents (e.g., patient, physical exam, diagnostic, i…

Multi-Scale Network Dynamics and Systemic Risk: A Model Context Protocol Approach to Financial Markets
Avishek Bhandari
https://arxiv.org/abs/2507.08065 https://

Multi-Scale Network Dynamics and Systemic Risk: A Model Context Protocol Approach to Financial Markets
This paper introduces a novel framework for analyzing systemic risk in financial markets through multi-scale network dynamics using Model Context Protocol (MCP) for agent communication. We develop an integrated approach that combines transfer entropy networks, agent-based modeling, and wavelet decomposition to capture information flows across temporal scales implemented in the MCPFM (Model Context Protocol Financial Markets) R package. Our methodology enables heterogeneous financial agents incl…

Not surprisingly, after spending weeks chasing innocent people around, a horny drunk armed U.S. #BorderPatrol Officer assaulted a female in a #SouthernCalifornia parking lot earlier this week...
Apptly this man's service to #MAGA

Border Patrol Agent Who Arrested U.S. Citizen In Pico Rivera Charged With Drunkenly Assaulting L.B. Cop ~ L.A. TACO
“No one is above the law, regardless of their position or badge. Law enforcement officers have a responsibility to always conduct themselves with integrity and professionalism. Our office will pursue prosecution accordingly to ensure justice is served.”

Odell Beckham has no plans to retire; free-agent WR has drawn interest from teams https://www.nfl.com/news/odell-beckham-has-no-plans-to-retire-free-agent-wr-has-drawn-interest-from-teams

This is before Mr Politti got the estate agent job. He may have been about to join them as a youth trainee worker though. #TOTP

Agent-based Condition Monitoring Assistance with Multimodal Industrial Database Retrieval Augmented Generation
Karl L\"owenmark, Daniel Str\"ombergsson, Chang Liu, Marcus Liwicki, Fredrik Sandin
https://arxiv.org/abs/2506.09247

Agent-based Condition Monitoring Assistance with Multimodal Industrial Database Retrieval Augmented Generation
Condition monitoring (CM) plays a crucial role in ensuring reliability and efficiency in the process industry. Although computerised maintenance systems effectively detect and classify faults, tasks like fault severity estimation, and maintenance decisions still largely depend on human expert analysis. The analysis and decision making automatically performed by current systems typically exhibit considerable uncertainty and high false alarm rates, leading to increased workload and reduced effici…

Extending the OWASP Multi-Agentic System Threat Modeling Guide: Insights from Multi-Agent Security Research
Klaudia Krawiecka, Christian Schroeder de Witt
https://arxiv.org/abs/2508.09815

Extending the OWASP Multi-Agentic System Threat Modeling Guide: Insights from Multi-Agent Security Research
We propose an extension to the OWASP Multi-Agentic System (MAS) Threat Modeling Guide, translating recent anticipatory research in multi-agent security (MASEC) into practical guidance for addressing challenges unique to large language model (LLM)-driven multi-agent architectures. Although OWASP's existing taxonomy covers many attack vectors, our analysis identifies gaps in modeling failures, including, but not limited to: reasoning collapse across planner-executor chains, metric overfitting, un…

DeepFleet: Multi-Agent Foundation Models for Mobile Robots
Ameya Agaskar, Sriram Siva, William Pickering, Kyle O'Brien, Charles Kekeh, Ang Li, Brianna Gallo Sarker, Alicia Chua, Mayur Nemade, Charun Thattai, Jiaming Di, Isaac Iyengar, Ramya Dharoor, Dino Kirouani, Jimmy Erskine, Tamir Hegazy, Scott Niekum, Usman A. Khan, Federico Pecora, Joseph W. Durham
ht…

DeepFleet: Multi-Agent Foundation Models for Mobile Robots
We introduce DeepFleet, a suite of foundation models designed to support coordination and planning for large-scale mobile robot fleets. These models are trained on fleet movement data, including robot positions, goals, and interactions, from hundreds of thousands of robots in Amazon warehouses worldwide. DeepFleet consists of four architectures that each embody a distinct inductive bias and collectively explore key points in the design space for multi-agent foundation models: the robot-centric …

Man Charged With Assaulting Federal Agent With Sandwich in D.C. (Nicholas Bogel-Burroughs/New York Times)
https://www.nytimes.com/2025/08/13/us/politics/federal-agent-trump-sandwich-dc.html?unlocked_article_code=1.eE8.ACbS.y9rAnHm-eVuh&smid=nytcore-ios-share&referringSource=articleShare
http://www.memeorandum.com/250813/p107#a250813p107

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications
Felix H\"arer
https://arxiv.org/abs/2506.10467 htt…

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications
Recent advancements in LLMs indicate potential for novel applications, e.g., through reasoning capabilities in the latest OpenAI and DeepSeek models. For applying these models in specific domains beyond text generation, LLM-based multi-agent approaches can be utilized that solve complex tasks by combining reasoning techniques, code generation, and software execution. Applications might utilize these capabilities and the knowledge of specialized LLM agents. However, while many evaluations are pe…

BugGen: A Self-Correcting Multi-Agent LLM Pipeline for Realistic RTL Bug Synthesis
Surya Jasper, Minh Luu, Evan Pan, Aakash Tyagi, Michael Quinn, Jiang Hu, David Kebo Houngninou
https://arxiv.org/abs/2506.10501

BugGen: A Self-Correcting Multi-Agent LLM Pipeline for Realistic RTL Bug Synthesis
Hardware complexity continues to strain verification resources, motivating the adoption of machine learning (ML) methods to improve debug efficiency. However, ML-assisted debugging critically depends on diverse and scalable bug datasets, which existing manual or automated bug insertion methods fail to reliably produce. We introduce BugGen, a first of its kind, fully autonomous, multi-agent pipeline leveraging Large Language Models (LLMs) to systematically generate, insert, and validate realisti…

Age of Information Optimization in Laser-charged UAV-assisted IoT Networks: A Multi-agent Deep Reinforcement Learning Method
Geng Sun, Likun Zhang, Jiahui Li, Jing Wu, Jiacheng Wang, Zemin Sun, Changyuan Zhao, Victor C. M. Leung
https://arxiv.org/abs/2507.08429

Age of Information Optimization in Laser-charged UAV-assisted IoT Networks: A Multi-agent Deep Reinforcement Learning Method
The integration of unmanned aerial vehicles (UAVs) with Internet of Things (IoT) networks offers promising solutions for efficient data collection. However, the limited energy capacity of UAVs remains a significant challenge. In this case, laser beam directors (LBDs) have emerged as an effective technology for wireless charging of UAVs during operation, thereby enabling sustained data collection without frequent returns to charging stations (CSs). In this work, we investigate the age of informa…

Source: Butterfly Effect, the startup behind Manus, has shut down its entire China-based team to minimize geopolitical risks associated with its ties to China (Juro Osawa/The Information)
https://www.theinformation.com/briefings/startup-behi…

Startup Behind Manus AI Agent Shuts Down China Team
The startup behind Manus, an artificial intelligence agent that went viral earlier this year and got financial backing from Benchmark, has shut down its entire China-based team, according to a person with knowledge of the situation. It’s the latest sign that Manus, whose biggest target market is the U.S., wants to minimize geopolitical risks associated with China ties. Butterfly Effect, the

An Automated Multi-Modal Evaluation Framework for Mobile Intelligent Assistants
Meiping Wang, Jian Zhong, Rongduo Han, Liming Kang, Zhengkun Shi, Xiao Liang, Xing Lin, Nan Gao, Haining Zhang
https://arxiv.org/abs/2508.09507

An Automated Multi-Modal Evaluation Framework for Mobile Intelligent Assistants
With the rapid development of mobile intelligent assistant technologies, multi-modal AI assistants have become essential interfaces for daily user interactions. However, current evaluation methods face challenges including high manual costs, inconsistent standards, and subjective bias. This paper proposes an automated multi-modal evaluation framework based on large language models and multi-agent collaboration. The framework employs a three-tier agent architecture consisting of interaction eval…

Replaced article(s) found for cs.SI. https://arxiv.org/list/cs.SI/new
[1/1]:
- CS-Agent: LLM-based Community Search via Dual-agent Collaboration
Jiahao Hua, Long Yuan, Qingshuai Feng, Qiang Fan, Shan Huang

Kritische Sicherheitslücke in Microsoft 365 Copilot zeigt Risiko von KI-Agenten
Der KI-Agent von M365 konnte per E-Mail und ohne Mausklick zur Freigabe sensibler Informationen verführt werden. Microsoft hat die Lücke jetzt geschlossen.

UI-Venus Technical Report: Building High-performance UI Agents with RFT
Zhangxuan Gu, Zhengwen Zeng, Zhenyu Xu, Xingran Zhou, Shuheng Shen, Yunfei Liu, Beitong Zhou, Changhua Meng, Tianyu Xia, Weizhi Chen, Yue Wen, Jingya Dou, Fei Tang, Jinzhen Lin, Yulin Liu, Zhenlin Guo, Yichen Gong, Heng Jia, Changlong Gao, Yuan Guo, Yong Deng, Zhenyu Guo, Liang Chen, Weiqiang Wang

UI-Venus Technical Report: Building High-performance UI Agents with RFT
We present UI-Venus, a native UI agent that takes only screenshots as input based on a multimodal large language model. UI-Venus achieves SOTA performance on both UI grounding and navigation tasks using only several hundred thousand high-quality training samples through reinforcement finetune (RFT) based on Qwen2.5-VL. Specifically, the 7B and 72B variants of UI-Venus obtain 94.1% / 50.8% and 95.3% / 61.9% on the standard grounding benchmarks, i.e., Screenspot-V2 / Pro, surpassing the previous …

Distributed Quantized Average Consensus in Open Multi-Agent Systems with Dynamic Communication Links
Jiaqi Hu, Karl H. Johansson, Apostolos I. Rikos
https://arxiv.org/abs/2508.05895

Distributed Quantized Average Consensus in Open Multi-Agent Systems with Dynamic Communication Links
In this paper, we focus on the distributed quantized average consensus problem in open multi-agent systems consisting of communication links that change dynamically over time. Open multi-agent systems exhibiting the aforementioned characteristic are referred to as \textit{open dynamic multi-agent systems} in this work. We present a distributed algorithm that enables active nodes in the open dynamic multi-agent system to calculate the quantized average of their initial states. Our algorithm cons…

NFL free agent Nyheim Hines is 'far from done' after missing two seasons due to jet ski accident

https://www.cbssports.com/nfl/news/nfl-fre

Cowboys free agent signee tabbed as team's 'biggest bust' of 2025 season https://www.si.com/nfl/cowboys/news/dallas-cowboys-free-agent-signee-tabbed-teams-biggest-bust-2025-season

Source: OpenAI is preparing ChatGPT agents to let users create files compatible with PowerPoint and Excel, generate reports, and handle tasks involving websites (Stephanie Palazzolo/The Information)
https://www.theinformation.com/articles/op

OpenAI Preps ChatGPT Agents in Challenge to Microsoft Excel and PowerPoint
As OpenAI tries to turn ChatGPT into a core application for white-collar work, it’s developing agent features that could make its customers less dependent on productivity apps from Microsoft. In the latest example, OpenAI has developed features that let ChatGPT customers quickly create and edit ...

A Minimal Model for Emergent Collective Behaviors in Autonomous Robotic Multi-Agent Systems
Hossein B. Jond
https://arxiv.org/abs/2508.08473 https://arxiv.…

A Minimal Model for Emergent Collective Behaviors in Autonomous Robotic Multi-Agent Systems
Collective behaviors such as swarming and flocking emerge from simple, decentralized interactions in biological systems. Existing models, such as Vicsek and Cucker-Smale, lack collision avoidance, whereas the Olfati-Saber model imposes rigid formations, limiting their applicability in swarm robotics. To address these limitations, this paper proposes a minimal yet expressive model that governs agent dynamics using relative positions, velocities, and local density, modulated by two tunable parame…

In March, we wrote about how Trump's halting of a massive Agent Orange cleanup in Vietnam puts hundreds of thousands at risk.
In May, we obtained exclusive records showing how cuts to humanitarian aid have led to violence and instability in Africa and the Middle East while undermining anti-terrorism initiatives
This week, Secretary Marco Rubio began laying off hundreds of State Department officials, including much of the foreign and civil service.
We're continuing …

Emergence of Hierarchies in Multi-Agent Self-Organizing Systems Pursuing a Joint Objective
Gang Chen, Guoxin Wang, Anton van Beek, Zhenjun Ming, Yan Yan
https://arxiv.org/abs/2508.09541

Emergence of Hierarchies in Multi-Agent Self-Organizing Systems Pursuing a Joint Objective
Multi-agent self-organizing systems (MASOS) exhibit key characteristics including scalability, adaptability, flexibility, and robustness, which have contributed to their extensive application across various fields. However, the self-organizing nature of MASOS also introduces elements of unpredictability in their emergent behaviors. This paper focuses on the emergence of dependency hierarchies during task execution, aiming to understand how such hierarchies arise from agents' collective pursuit …

🔄 Agent loop architecture: user input − model inference − tool execution − result feedback − continuous conversation flow
💻 String replacement editing approach works effectively with current #AI models for precise code modifications

Padilla says FBI agent, Guard member escorted him to Noem's briefing before removal (Avery Lotz/Axios)
https://www.axios.com/2025/06/15/alex-padilla-kristi-noem-dhs-removal
http://www.memeorandum.com/250615/p38#a250615p38

Agent's Take: A unique compromise that could end the Commanders-Terry McLaurin contract dispute

https://www.cbssports.com/nfl/news/agents-

LPO: Towards Accurate GUI Agent Interaction via Location Preference Optimization
Jiaqi Tang, Yu Xia, Yi-Feng Wu, Yuwei Hu, Yuhui Chen, Qing-Guo Chen, Xiaogang Xu, Xiangyu Wu, Hao Lu, Yanqing Ma, Shiyin Lu, Qifeng Chen
https://arxiv.org/abs/2506.09373

LPO: Towards Accurate GUI Agent Interaction via Location Preference Optimization
The advent of autonomous agents is transforming interactions with Graphical User Interfaces (GUIs) by employing natural language as a powerful intermediary. Despite the predominance of Supervised Fine-Tuning (SFT) methods in current GUI agents for achieving spatial localization, these methods face substantial challenges due to their limited capacity to accurately perceive positional data. Existing strategies, such as reinforcement learning, often fail to assess positional accuracy effectively, …

Are We Generalizing from the Exception? An In-the-Wild Study on Group-Sensitive Conversation Design in Human-Agent Interactions
Ana M\"uller, Sabina Jeschke, Anja Richert
https://arxiv.org/abs/2506.10462

Are We Generalizing from the Exception? An In-the-Wild Study on Group-Sensitive Conversation Design in Human-Agent Interactions
This paper investigates the impact of a group-adaptive conversation design in two socially interactive agents (SIAs) through two real-world studies. Both SIAs - Furhat, a social robot, and MetaHuman, a virtual agent - were equipped with a conversational artificial intelligence (CAI) backend combining hybrid retrieval and generative models. The studies were carried out in an in-the-wild setting with a total of $N = 188$ participants who interacted with the SIAs - in dyads, triads or larger group…

Harnessing Input-Adaptive Inference for Efficient VLN
Dongwoo Kang, Akhil Perincherry, Zachary Coalson, Aiden Gabriel, Stefan Lee, Sanghyun Hong
https://arxiv.org/abs/2508.09262

Harnessing Input-Adaptive Inference for Efficient VLN
An emerging paradigm in vision-and-language navigation (VLN) is the use of history-aware multi-modal transformer models. Given a language instruction, these models process observation and navigation history to predict the most appropriate action for an agent. While they have significantly improved performance, the scale of these models can be a bottleneck in practical settings with limited computational resources. In this work, we propose a novel input-adaptive navigation method to enhance VLN …

Context Engineering for Multi-Agent LLM Code Assistants Using Elicit, NotebookLM, ChatGPT, and Claude Code
Muhammad Haseeb
https://arxiv.org/abs/2508.08322 https://

Context Engineering for Multi-Agent LLM Code Assistants Using Elicit, NotebookLM, ChatGPT, and Claude Code
Large Language Models (LLMs) have shown promise in automating code generation and software engineering tasks, yet they often struggle with complex, multi-file projects due to context limitations and knowledge gaps. We propose a novel context engineering workflow that combines multiple AI components: an Intent Translator (GPT-5) for clarifying user requirements, an Elicit-powered semantic literature retrieval for injecting domain knowledge, NotebookLM-based document synthesis for contextual unde…

QoE-Aware Service Provision for Mobile AR Rendering: An Agent-Driven Approach
Conghao Zhou, Lulu Sun, Xiucheng Wang, Peng Yang, Feng Lyu, Sihan Lu, Xuemin Shen
https://arxiv.org/abs/2508.08627

QoE-Aware Service Provision for Mobile AR Rendering: An Agent-Driven Approach
Mobile augmented reality (MAR) is envisioned as a key immersive application in 6G, enabling virtual content rendering aligned with the physical environment through device pose estimation. In this paper, we propose a novel agent-driven communication service provisioning approach for edge-assisted MAR, aiming to reduce communication overhead between MAR devices and the edge server while ensuring the quality of experience (QoE). First, to address the inaccessibility of MAR application-specific inf…

New Orleans Saints to sign free agent RB Cam Akers after minicamp invitation, per report

https://www.cbssports.com/nfl/news/new-orl…

Sources: AWS is launching a marketplace for AI agents, with Anthropic as one of its partners, at the AWS Summit in NYC next week (Jagmeet Singh/TechCrunch)
https://techcrunch.com/2025/07/10/aws-is-launching-an-ai-ag…

AWS is launching an AI agent marketplace next week with Anthropic as a partner | TechCrunch
Amazon Web Services is launching an AI agent marketplace and Anthropic is one of its partners.

Fault Tolerant Multi-Agent Learning with Adversarial Budget Constraints
David Mguni, Yaqi Sun, Haojun Chen, Amir Darabi, Larry Olanrewaju Orimoloye, Yaodong Yang
https://arxiv.org/abs/2508.08800

Fault Tolerant Multi-Agent Learning with Adversarial Budget Constraints
In multi-agent systems, the safe and reliable execution of tasks often depends on agents correctly coordinating their actions. However, in real-world deployments, failures of computational components are inevitable, presenting a critical challenge: ensuring that multi-agent reinforcement learning (MARL) policies remain effective even when some agents malfunction. We propose the Multi-Agent Robust Training Algorithm (MARTA), a plug-and-play framework for training MARL agents to be resilient to p…

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…

Mediator-Guided Multi-Agent Collaboration among Open-Source Models for Medical Decision-Making
Kaitao Chen, Mianxin Liu, Daoming Zong, Chaoyue Ding, Shaohao Rui, Yankai Jiang, Mu Zhou, Xiaosong Wang
https://arxiv.org/abs/2508.05996

Mediator-Guided Multi-Agent Collaboration among Open-Source Models for Medical Decision-Making
Complex medical decision-making involves cooperative workflows operated by different clinicians. Designing AI multi-agent systems can expedite and augment human-level clinical decision-making. Existing multi-agent researches primarily focus on language-only tasks, yet their extension to multimodal scenarios remains challenging. A blind combination of diverse vision-language models (VLMs) can amplify an erroneous outcome interpretation. VLMs in general are less capable in instruction following a…

Memp: Exploring Agent Procedural Memory
Runnan Fang, Yuan Liang, Xiaobin Wang, Jialong Wu, Shuofei Qiao, Pengjun Xie, Fei Huang, Huajun Chen, Ningyu Zhang
https://arxiv.org/abs/2508.06433

Memp: Exploring Agent Procedural Memory
Large Language Models (LLMs) based agents excel at diverse tasks, yet they suffer from brittle procedural memory that is manually engineered or entangled in static parameters. In this work, we investigate strategies to endow agents with a learnable, updatable, and lifelong procedural memory. We propose Memp that distills past agent trajectories into both fine-grained, step-by-step instructions and higher-level, script-like abstractions, and explore the impact of different strategies for Build, …

OnlineBEV: Recurrent Temporal Fusion in Bird's Eye View Representations for Multi-Camera 3D Perception
Junho Koh, Youngwoo Lee, Jungho Kim, Dongyoung Lee, Jun Won Choi
https://arxiv.org/abs/2507.08644

OnlineBEV: Recurrent Temporal Fusion in Bird's Eye View Representations for Multi-Camera 3D Perception
Multi-view camera-based 3D perception can be conducted using bird's eye view (BEV) features obtained through perspective view-to-BEV transformations. Several studies have shown that the performance of these 3D perception methods can be further enhanced by combining sequential BEV features obtained from multiple camera frames. However, even after compensating for the ego-motion of an autonomous agent, the performance gain from temporal aggregation is limited when combining a large number of imag…

The team behind AI agent Manus has relocated its HQ to Singapore and started recruiting there, while parent company Butterfly Effect reportedly remains in China (Hannah Wang/South China Morning Post)
https://www.scmp.com/tech/tech-t…

Chinese start-up Manus AI relocates to Singapore amid US chip curbs
Manus AI has begun recruiting in the city state, offering positions such as data analyst and AI agent engineer.

Reasoning About Knowledge on Regular Expressions is 2EXPTIME-complete
Avijeet Ghosh, Sujata Ghosh, Fran\c{c}ois Schwarzentruber
https://arxiv.org/abs/2508.09784 https://

Reasoning About Knowledge on Regular Expressions is 2EXPTIME-complete
Logics for reasoning about knowledge and actions have seen many applications in various domains of multi-agent systems, including epistemic planning. Change of knowledge based on observations about the surroundings forms a key aspect in such planning scenarios. Public Observation Logic (POL) is a variant of public announcement logic for reasoning about knowledge that gets updated based on public observations. Each state in an epistemic (Kripke) model is equipped with a set of expected observati…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Text2BIM: Generating Building Models Using a Large Language Model-based Multi-Agent Framework
Changyu Du, Sebastian Esser, Stavros Nousias, Andr\'e Borrmann

MIRIX: Multi-Agent Memory System for LLM-Based Agents
Yu Wang, Xi Chen
https://arxiv.org/abs/2507.07957 https://arxiv.org/pdf/2507.07…

MIRIX: Multi-Agent Memory System for LLM-Based Agents
Although memory capabilities of AI agents are gaining increasing attention, existing solutions remain fundamentally limited. Most rely on flat, narrowly scoped memory components, constraining their ability to personalize, abstract, and reliably recall user-specific information over time. To this end, we introduce MIRIX, a modular, multi-agent memory system that redefines the future of AI memory by solving the field's most critical challenge: enabling language models to truly remember. Unlike pr…

Google launches its asynchronous coding agent Jules out of beta, with a free plan capped at 15 daily tasks and higher limits for Google AI Pro and Ultra users (Jagmeet Singh/TechCrunch)
https://techcrunch.com/2025/08/06/googles-ai-coding-agent-jules-is-now…

Google's AI coding agent Jules is now out of beta | TechCrunch
Powered by Gemini 2.5 Pro, Jules is an asynchronous, agent-based coding tool that integrates with GitHub, clones codebases into Google Cloud virtual machines, and uses AI to fix or update code while developers focus on other tasks.

PanelTR: Zero-Shot Table Reasoning Framework Through Multi-Agent Scientific Discussion
Yiran Rex Ma
https://arxiv.org/abs/2508.06110 https://arxiv.org/pdf/…

PanelTR: Zero-Shot Table Reasoning Framework Through Multi-Agent Scientific Discussion
Table reasoning, including tabular QA and fact verification, often depends on annotated data or complex data augmentation, limiting flexibility and generalization. LLMs, despite their versatility, often underperform compared to simple supervised models. To approach these issues, we introduce PanelTR, a framework utilizing LLM agent scientists for robust table reasoning through a structured scientific approach. PanelTR's workflow involves agent scientists conducting individual investigations, en…

Agent: Bolts' Harris hurt eye in fireworks incident https://www.espn.com/nfl/story/_/id/45712485/agent-najee-harris-eye-injury-fireworks-incident

Justin Simmons has 'no bad blood' with Sean Payton; Free-agent safety hopes to join contender https://www.nfl.com/news/justin-simmons-has-no-bad-blood-with-sean-payton-free-agent-safety-hopes-to-join-contender…

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[4/9]:
- Cowpox: Towards the Immunity of VLM-based Multi-Agent Systems
Yutong Wu, Jie Zhang, Yiming Li, Chao Zhang, Qing Guo, Nils Lukas, Tianwei Zhang

Ellipsis Health, which developed an AI voice agent to check in on patients between doctor visits, raised a $45M Series A led by Salesforce, Khosla, and CVS (Brian Gormley/Wall Street Journal)
https://www.

Agent's Take: How Cowboys' Micah Parsons innocently fueled contract dispute with Jerry Jones

https://www.cbssports.com/nfl/news/agents-

Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Xufang Luo, Yuge Zhang, Zhiyuan He, Zilong Wang, Siyun Zhao, Dongsheng Li, Luna K. Qiu, Yuqing Yang
https://arxiv.org/abs/2508.03680

Agent Lightning: Train ANY AI Agents with Reinforcement Learning
We present Agent Lightning, a flexible and extensible framework that enables Reinforcement Learning (RL)-based training of Large Language Models (LLMs) for any AI agent. Unlike existing methods that tightly couple RL training with agent or rely on sequence concatenation with masking, Agent Lightning achieves complete decoupling between agent execution and training, allowing seamless integration with existing agents developed via diverse ways (e.g., using frameworks like LangChain, OpenAI Agents…

Chargers RB Najee Harris injured in fireworks accident but expected to be ready for season, agent says

https://www.cbssports.com/nfl/news/charger

Sydney-based Lorikeet, which provides AI agents as "customer concierges", raised a AU$54M Series A led by QED Investors at a AU$200M valuation (Paul Smith/Australian Financial Review)
https://www.afr.com/technology/ai-agent-bo

Lorikeet AI: Canva founders invest in Sydney start-up amid rapid growth
The success of Lorikeet’s AI agent technology has attracted investors including Canva founders Melanie Perkins and Cliff Obrecht.

ViDove: A Translation Agent System with Multimodal Context and Memory-Augmented Reasoning
Yichen Lu, Wei Dai, Jiaen Liu, Ching Wing Kwok, Zongheng Wu, Xudong Xiao, Ao Sun, Sheng Fu, Jianyuan Zhan, Yian Wang, Takatomo Saito, Sicheng Lai
https://arxiv.org/abs/2507.07306

ViDove: A Translation Agent System with Multimodal Context and Memory-Augmented Reasoning
LLM-based translation agents have achieved highly human-like translation results and are capable of handling longer and more complex contexts with greater efficiency. However, they are typically limited to text-only inputs. In this paper, we introduce ViDove, a translation agent system designed for multimodal input. Inspired by the workflow of human translators, ViDove leverages visual and contextual background information to enhance the translation process. Additionally, we integrate a multimo…

Odell Beckham Jr. says he's 'had conversations' with Aaron Rodgers about joining Steelers

https://www.cbssports.com/nfl/news/odell-b…

OpenAI updates its coding agent Codex with internet access, turned off by default, and expands availability to ChatGPT Plus users (Simon Willison/Simon Willison's Weblog)
https://simonwillison.net/2025/Jun/3/codex-agent-internet-access/

Codex agent internet access
Sam Altman, [just now](https://twitter.com/sama/status/1930006856019390521): > codex gets access to the internet today! it is off by default and there are complex tradeoffs; people should read about the risks carefully and …

VIKI-R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning
Li Kang, Xiufeng Song, Heng Zhou, Yiran Qin, Jie Yang, Xiaohong Liu, Philip Torr, Lei Bai, Zhenfei Yin
https://arxiv.org/abs/2506.09049

VIKI-R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning
Coordinating multiple embodied agents in dynamic environments remains a core challenge in artificial intelligence, requiring both perception-driven reasoning and scalable cooperation strategies. While recent works have leveraged large language models (LLMs) for multi-agent planning, a few have begun to explore vision-language models (VLMs) for visual reasoning. However, these VLM-based approaches remain limited in their support for diverse embodiment types. In this work, we introduce VIKI-Bench…

Chinese startups and tech giants are racing to create AI agents for both local and global consumers, following the popularity of Butterfly Effect's Manus (Caiwei Chen/MIT Technology Review)
https://www.technologyreview.com/2025/06/05/1117958/china-ai-a…

Manus has kick-started an AI agent boom in China
A stampede of contenders and copycats has followed the launch of the general AI agent, but China’s internet restrictions have so far made it easier to cater to overseas users.

Society of Mind Meets Real-Time Strategy: A Hierarchical Multi-Agent Framework for Strategic Reasoning
Daechul Ahn, San Kim, Jonghyun Choi
https://arxiv.org/abs/2508.06042 https…

Society of Mind Meets Real-Time Strategy: A Hierarchical Multi-Agent Framework for Strategic Reasoning
Large Language Models (LLMs) have recently demonstrated impressive action sequence prediction capabilities but often struggle with dynamic, long-horizon tasks such as real-time strategic games. In a game such as StarCraftII (SC2), agents need to manage resource constraints and adapt to evolving battlefield situations in a partially observable environment. This often overwhelms exisiting LLM-based approaches. To address these challenges, we propose a hierarchical multi-agent framework that emplo…