Tootfinder

#GitHub #Copilot coding agent in public preview
https://github.blog/changelog/2025-…

R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
Yuante Li, Xu Yang, Xiao Yang, Minrui Xu, Xisen Wang, Weiqing Liu, Jiang Bian
https://arxiv.org/abs/2505.15155

R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
Financial markets pose fundamental challenges for asset return prediction due to their high dimensionality, non-stationarity, and persistent volatility. Despite advances in large language models and multi-agent systems, current quantitative research pipelines suffer from limited automation, weak interpretability, and fragmented coordination across key components such as factor mining and model innovation. In this paper, we propose R&D-Agent for Quantitative Finance, in short RD-Agent(Q), the fi…

RAGentA: Multi-Agent Retrieval-Augmented Generation for Attributed Question Answering
Ines Besrour, Jingbo He, Tobias Schreieder, Michael F\"arber
https://arxiv.org/abs/2506.16988

RAGentA: Multi-Agent Retrieval-Augmented Generation for Attributed Question Answering
We present RAGentA, a multi-agent retrieval-augmented generation (RAG) framework for attributed question answering (QA). With the goal of trustworthy answer generation, RAGentA focuses on optimizing answer correctness, defined by coverage and relevance to the question and faithfulness, which measures the extent to which answers are grounded in retrieved documents. RAGentA uses a multi-agent architecture that iteratively filters retrieved documents, generates attributed answers with in-line cita…

The #OpenAI paper by Baker et al, "Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation" comes to a troubling conclusion: #LLM s with #reasoning or

Agent-based Liquidity Risk Modelling for Financial Markets
Perukrishnen Vytelingum, Rory Baggott, Namid Stillman, Jianfei Zhang, Dingqiu Zhu, Tao Chen, Justin Lyon
https://arxiv.org/abs/2505.15296

Agent-based Liquidity Risk Modelling for Financial Markets
In this paper, we describe a novel agent-based approach for modelling the transaction cost of buying or selling an asset in financial markets, e.g., to liquidate a large position as a result of a margin call to meet financial obligations. The simple act of buying or selling in the market causes a price impact and there is a cost described as liquidity risk. For example, when selling a large order, there is market slippage -- each successive trade will execute at the same or worse price. When th…

Random thought: if browsers are going to implement AI and all the agent stuff, might as well use it to block ads, skip video ads, cookie banners, pop-ups, trackers, and all those annoyances? 🤔

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

Tom Brady played a part in Raiders avoiding top free-agent quarterback https://www.sportingnews.com/us/nfl/las-vegas-raiders/news/tom-brady-played-part-raiders-avoiding-top-free-agent-q…

Many people are detained at U.S. airports for reasons they find arbitrary and mysterious.
I got lucky—when I was stopped by Customs and Border Protection last week, after flying to Los Angeles from Melbourne, a border agent told me, explicitly and proudly, why I’d been pulled out of the customs line.
“Look, we both know why you are here,” the agent told me.
He identified himself to me as Adam, though his colleagues referred to him as Officer Martinez.
When I said that…

How My Reporting on the Columbia Protests Led to My Deportation
Alistair Kitchen on being detained at Los Angeles International Airport and sent back to Australia because of his reporting on the protests at Columbia University criticizing Israel’s actions in Gaza.

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

How an up-and-coming NFL agent (in Minneapolis!) finds his footing in a cut-throat league https://www.nytimes.com/athletic/6415008/2025/06/17/nfl-agent-minnesota-vikings-minneapolis-jonathan-allen/

Two different takes on the potential of AI for cataloguing in 'Catalogue and Index'
'Augmenting cataloguers' https://journals.cilip.org.uk/catalogue-and-index/article/view/750
'Smart enough to mislead'

Random thought: if browsers are going to implement AI and all the agent stuff, might as well use it to block ads, skip video ads, cookie banners, pop-ups, trackers, and all those annoyances? 🤔

Cowboys would be wise to pass on bringing $191 million future Hall of Famer back to Texas https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/06/20/cowboys-von-miller-free-agent-2025-pursu…

Funny, and so true.
#uspol #fascism
ICE Agent or Just Some Person?
"Your clothing should tell a story about you! Just not who you are or that you are acting in any kind of official capacity." @petridishes on the ICE dress code:

The ICE Dress Code
There’s a dress code to help you make that determination.

SheetMind: An End-to-End LLM-Powered Multi-Agent Framework for Spreadsheet Automation
Ruiyan Zhu, Xi Cheng, Ke Liu, Brian Zhu, Daniel Jin, Neeraj Parihar, Zhoutian Xu, Oliver Gao
https://arxiv.org/abs/2506.12339

SheetMind: An End-to-End LLM-Powered Multi-Agent Framework for Spreadsheet Automation
We present SheetMind, a modular multi-agent framework powered by large language models (LLMs) for spreadsheet automation via natural language instructions. The system comprises three specialized agents: a Manager Agent that decomposes complex user instructions into subtasks; an Action Agent that translates these into structured commands using a Backus Naur Form (BNF) grammar; and a Reflection Agent that validates alignment between generated actions and the user's original intent. Integrated int…

Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models
Lu Gao, Yongxin Liu, Hongyun Chen, Dahai Liu, Yunpeng Zhang, Jingran Sun
https://arxiv.org/abs/2506.16699

Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models
Intelligent Transportation Systems (ITS) are increasingly vulnerable to sophisticated cyberattacks due to their complex, interconnected nature. Ensuring the cybersecurity of these systems is paramount to maintaining road safety and minimizing traffic disruptions. This study presents a novel multi-agent framework leveraging Large Language Models (LLMs) to enhance traffic simulation and cybersecurity testing. The framework automates the creation of traffic scenarios, the design of cyberattack str…

This https://arxiv.org/abs/2409.06289 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Automate Strategy Finding with LLM in Quant Investment
We present a novel three-stage framework leveraging Large Language Models (LLMs) within a risk-aware multi-agent system for automate strategy finding in quantitative finance. Our approach addresses the brittleness of traditional deep learning models in financial applications by: employing prompt-engineered LLMs to generate executable alpha factor candidates across diverse financial data, implementing multimodal agent-based evaluation that filters factors based on market status, predictive quali…

Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems
Zhongzhi Yu, Mingjie Liu, Michael Zimmer, Yingyan Celine Lin, Yong Liu, Haoxing Ren
https://arxiv.org/abs/2506.13905

Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems
Despite recent progress in generating hardware RTL code with LLMs, existing solutions still suffer from a substantial gap between practical application scenarios and the requirements of real-world RTL code development. Prior approaches either focus on overly simplified hardware descriptions or depend on extensive human guidance to process complex specifications, limiting their scalability and automation potential. In this paper, we address this gap by proposing an LLM agent system, termed Spec2…

This Github repository conveniently lists and categorizes prime examples of LLM-based agent applications. Each example application features its own repository folder with its source code (Python), and a helpful README.md file describing its installation and use.
Categories include:
1. Starter AI Agents
2. Advanced AI Agents
3. Autonomous Game Playing Agents
4. Multi-Agent Teams
5. Voice AI Agents
6. RAG-Based Agents
"awesome-llm-apps"

L'agacement du jour : "l'agent en ressenti déceptif". Enfin, je cite celui-ci, mais je suis en ressenti répulsif sur une ribambelle d'autres, l'auteur en charge des pages en cours de correction ayant opté pour l'adoption répétée, récurrente, constante et durable d'un style relevant du jargon technique et spécifique en congruence… ou pas (pour une bien pâle imitation).
Éclatons de rire au lieu de nous arracher les cheveux…

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes
Jiahao Qiu, Xinzhe Juan, Yimin Wang, Ling Yang, Xuan Qi, Tongcheng Zhang, Jiacheng Guo, Yifu Lu, Zixin Yao, Hongru Wang, Shilong Liu, Xun Jiang, Liu Leqi, Mengdi Wang
https://arxiv.org/abs/2506.14728

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes
While knowledge distillation has become a mature field for compressing large language models (LLMs) into smaller ones by aligning their outputs or internal representations, the distillation of LLM-based agents, which involve planning, memory, and tool use, remains relatively underexplored. Existing agent distillation methods typically replay full teacher trajectories or imitate step-by-step teacher tool usage, but they often struggle to train student agents to dynamically plan and act in novel …

LLM Agent for Hyper-Parameter Optimization
Wanzhe Wang, Jianqiu Peng, Menghao Hu, Weihuang Zhong, Tong Zhang, Shuai Wang, Yixin Zhang, Mingjie Shao, Wanli Ni
https://arxiv.org/abs/2506.15167

LLM Agent for Hyper-Parameter Optimization
Hyper-parameters are essential and critical for the performance of communication algorithms. However, current hyper-parameters tuning methods for warm-start particles swarm optimization with cross and mutation (WS-PSO-CM) algortihm for radio map-enabled unmanned aerial vehicle (UAV) trajectory and communication are primarily heuristic-based, exhibiting low levels of automation and unsatisfactory performance. In this paper, we design an large language model (LLM) agent for automatic hyper-parame…

Unified Software Engineering agent as AI Software Engineer
Leonhard Applis, Yuntong Zhang, Shanchao Liang, Nan Jiang, Lin Tan, Abhik Roychoudhury
https://arxiv.org/abs/2506.14683 …

Unified Software Engineering agent as AI Software Engineer
The growth of Large Language Model (LLM) technology has raised expectations for automated coding. However, software engineering is more than coding and is concerned with activities including maintenance and evolution of a project. In this context, the concept of LLM agents has gained traction, which utilize LLMs as reasoning engines to invoke external tools autonomously. But is an LLM agent the same as an AI software engineer? In this paper, we seek to understand this question by developing a U…

AgentFacts: Universal KYA Standard for Verified AI Agent Metadata & Deployment
Jared James Grogan
https://arxiv.org/abs/2506.13794 https://

AgentFacts: Universal KYA Standard for Verified AI Agent Metadata & Deployment
Enterprise AI deployment faces critical "Know Your Agent" (KYA) challenges where organizations must verify third-party agent capabilities and establish trust without standardized metadata or verification infrastructure. Current approaches rely on self-declared capabilities and custom integration processes that create trust gaps and coordination friction limiting confident enterprise adoption. This paper presents AgentFacts, a universal metadata standard that enables systematic agent verificatio…

Las Vegas Raiders Insider Says Free Agent Signing Was A Secret Standout at Minicamp https://heavy.com/sports/nfl/las-vegas-raiders/free-agent-signing-secret-standout-minicamp/?adt_ei=[email]

The Space Between Us: A Methodological Framework for Researching Bonding and Proxemics in Situated Group-Agent Interactions
Ana M\"uller, Anja Richert
https://arxiv.org/abs/2506.11829

The Space Between Us: A Methodological Framework for Researching Bonding and Proxemics in Situated Group-Agent Interactions
This paper introduces a multimethod framework for studying spatial and social dynamics in real-world group-agent interactions with socially interactive agents. Drawing on proxemics and bonding theories, the method combines subjective self-reports and objective spatial tracking. Applied in two field studies in a museum (N = 187) with a robot and a virtual agent, the paper addresses the challenges in aligning human perception and behavior. We focus on presenting an open source, scalable, and fiel…

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

Wasserstein-Barycenter Consensus for Cooperative Multi-Agent Reinforcement Learning
Ali Baheri
https://arxiv.org/abs/2506.12497 https://

Wasserstein-Barycenter Consensus for Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) demands principled mechanisms to align heterogeneous policies while preserving the capacity for specialized behavior. We introduce a novel consensus framework that defines the team strategy as the entropic-regularized $p$-Wasserstein barycenter of agents' joint state--action visitation measures. By augmenting each agent's policy objective with a soft penalty proportional to its Sinkhorn divergence from this barycenter, the proposed approach …

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

ICE agents say posting names endangers them, Nashville mayor says real problem is masking (Karen Aguilar/WZTV)
https://fox17.com/news/local/ice-agents-say-posting-names-endangers-them-nashville-mayor-says-real-problem-is-masking-dhs-google-news
http://www.memeorandum.com/250619/p122#a250619p122

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

ImmerseGen: Agent-Guided Immersive World Generation with Alpha-Textured Proxies
Jinyan Yuan, Bangbang Yang, Keke Wang, Panwang Pan, Lin Ma, Xuehai Zhang, Xiao Liu, Zhaopeng Cui, Yuewen Ma
https://arxiv.org/abs/2506.14315

ImmerseGen: Agent-Guided Immersive World Generation with Alpha-Textured Proxies
Automatic creation of 3D scenes for immersive VR presence has been a significant research focus for decades. However, existing methods often rely on either high-poly mesh modeling with post-hoc simplification or massive 3D Gaussians, resulting in a complex pipeline or limited visual realism. In this paper, we demonstrate that such exhaustive modeling is unnecessary for achieving compelling immersive experience. We introduce ImmerseGen, a novel agent-guided framework for compact and photorealist…

Multi-Agent, Multi-Scale Systems with the Koopman Operator
Craig Bakker
https://arxiv.org/abs/2506.15589 https://arxiv.org/pdf/2506.1…

Multi-Agent, Multi-Scale Systems with the Koopman Operator
The Koopman Operator (KO) takes nonlinear state dynamics and ``lifts'' those dynamics to an infinite-dimensional functional space of observables in which those dynamics are linear. Computational applications typically use a finite-dimensional approximation to the KO. The KO can also be applied to controlled dynamical systems, and the linearity of the KO then facilitates analysis and control calculations. In principle, the potential benefits provided by the KO, and the way that it facilitates th…

PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
Wenhao Li, Selvakumar Manickam, Yung-wey Chong, Shankar Karuppayah
https://arxiv.org/abs/2506.15656 …

PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
Phishing websites continue to pose a significant cybersecurity threat, often leveraging deceptive structures, brand impersonation, and social engineering tactics to evade detection. While recent advances in large language models (LLMs) have enabled improved phishing detection through contextual understanding, most existing approaches rely on single-agent classification facing the risks of hallucination and lack interpretability or robustness. To address these limitations, we propose PhishDebate…

Komm mit dem früheren US Border Patrol Agent @… auf einen kurzen Ausflug in ihr altes Patrouillengebiet, wo die Grenze zu Mexico buchstäblich weit offen ist und viele sie überqueren, was den Berichten der Grenzpatrouille widerspricht.
How the Border Patrol has left the border wide open. Publicly the Border Patrol claims the military is guarding the southern…

Agent Orange
bot by @…
This is satire, not sedition: no investigating me please.
#satire #potus45

GUI-Robust: A Comprehensive Dataset for Testing GUI Agent Robustness in Real-World Anomalies
Jingqi Yang, Zhilong Song, Jiawei Chen, Mingli Song, Sheng Zhou, linjun sun, Xiaogang Ouyang, Chun Chen, Can Wang
https://arxiv.org/abs/2506.14477

GUI-Robust: A Comprehensive Dataset for Testing GUI Agent Robustness in Real-World Anomalies
The development of high-quality datasets is crucial for benchmarking and advancing research in Graphical User Interface (GUI) agents. Despite their importance, existing datasets are often constructed under idealized conditions, overlooking the diverse anomalies frequently encountered in real-world deployments. To address this limitation, we introduce GUI-Robust, a novel dataset designed for comprehensive GUI agent evaluation, explicitly incorporating seven common types of anomalies observed in …

« J'ai découvert le support SSH agent de Bitwarden et ses conséquences sur l'utilisation de Age »
#TIL

Agent's Take: What is holding up NFL Draft second-rounders from signing rookie deals?

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

The content of the user agent is the dumbest thing we've done to the web, and we've doing a whole lot of dumb things to the web—all the way back to spelling referrer incorrectly (and we still do).

Cowboys Urged to Sign $94 Million NFL All-Pro LB for Struggling Run Defense https://heavy.com/sports/nfl/dallas-cowboys/free-agent-cj-mosley-run-defense/?adt_ei=[email]

Investigating the Potential of Large Language Model-Based Router Multi-Agent Architectures for Foundation Design Automation: A Task Classification and Expert Selection Study
Sompote Youwai, David Phim, Vianne Gayl Murcia, Rianne Clair Onas
https://arxiv.org/abs/2506.13811

Investigating the Potential of Large Language Model-Based Router Multi-Agent Architectures for Foundation Design Automation: A Task Classification and Expert Selection Study
This study investigates router-based multi-agent systems for automating foundation design calculations through intelligent task classification and expert selection. Three approaches were evaluated: single-agent processing, multi-agent designer-checker architecture, and router-based expert selection. Performance assessment utilized baseline models including DeepSeek R1, ChatGPT 4 Turbo, Grok 3, and Gemini 2.5 Pro across shallow foundation and pile design scenarios. The router-based configuration…

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

ADAgent: LLM Agent for Alzheimer's Disease Analysis with Collaborative Coordinator
Wenlong Hou, Gangqian Yang, Ye Du, Yeung Lau, Lihao Liu, Junjun He, Ling Long, Shujun Wang
https://arxiv.org/abs/2506.11150

ADAgent: LLM Agent for Alzheimer's Disease Analysis with Collaborative Coordinator
Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. Early and precise diagnosis of AD is crucial for timely intervention and treatment planning to alleviate the progressive neurodegeneration. However, most existing methods rely on single-modality data, which contrasts with the multifaceted approach used by medical experts. While some deep learning approaches process multi-modal data, they are limited to specific tasks with a small set of input modalities and ca…

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…

Agent Interpolation for Knowledge
Marta B\'ilkov\'a, Wesley Fussner, Roman Kuznets
https://arxiv.org/abs/2505.23401 https://a…

Agent Interpolation for Knowledge
We define a new type of proof formalism for multi-agent modal logics with S5-type modalities. This novel formalism combines the features of hypersequents to represent S5 modalities with nested sequents to represent the T-like modality alternations. We show that the calculus is sound and complete, cut-free, and terminating and yields decidability and the finite model property for multi-agent S5. We also use it to prove the Lyndon (and hence Craig) interpolation property for multi-agent S5, consi…

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.

Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning
Haochen Zhang, Zhong Zheng, Lingzhou Xue
https://arxiv.org/abs/2506.04626

Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning
Motivated by real-world settings where data collection and policy deployment -- whether for a single agent or across multiple agents -- are costly, we study the problem of on-policy single-agent reinforcement learning (RL) and federated RL (FRL) with a focus on minimizing burn-in costs (the sample sizes needed to reach near-optimal regret) and policy switching or communication costs. In parallel finite-horizon episodic Markov Decision Processes (MDPs) with $S$ states and $A$ actions, existing m…

Anomaly, Class Division, and Decoupling in Wealth Dynamics
Jaeseok Hur, Meesoon Ha, Hawoong Jeong
https://arxiv.org/abs/2506.08175 https://

Anomaly, Class Division, and Decoupling in Wealth Dynamics
Economic inequality is shaped by the agent-network structure, the interaction between agents, and the individual agent's ability. We provide a comprehensive picture of anomalous diffusion, economic class division, and bimodal wealth distribution in an agent-based model, where the allocation of heterogeneous agent abilities/growth rates is tuned in sparse regular networks.In particular, we focus on the statistical characteristics of logarithmic scaled normalized wealth distributions with two abi…

Doppelg\"anger Method: Breaking Role Consistency in LLM Agent via Prompt-based Transferable Adversarial Attack
Daewon Kang, YeongHwan Shin, Doyeon Kim, Kyu-Hwan Jung, Meong Hi Son
https://arxiv.org/abs/2506.14539

Doppelgänger Method: Breaking Role Consistency in LLM Agent via Prompt-based Transferable Adversarial Attack
Since the advent of large language models, prompt engineering now enables the rapid, low-effort creation of diverse autonomous agents that are already in widespread use. Yet this convenience raises urgent concerns about the safety, robustness, and behavioral consistency of the underlying prompts, along with the pressing challenge of preventing those prompts from being exposed to user's attempts. In this paper, we propose the ''Doppelgänger method'' to demonstrate the risk of an agent being hij…

Levels of Autonomy for AI Agents
K. J. Kevin Feng, David W. McDonald, Amy X. Zhang
https://arxiv.org/abs/2506.12469 https://arxiv.org…

Levels of Autonomy for AI Agents
Autonomy is a double-edged sword for AI agents, simultaneously unlocking transformative possibilities and serious risks. How can agent developers calibrate the appropriate levels of autonomy at which their agents should operate? We argue that an agent's level of autonomy can be treated as a deliberate design decision, separate from its capability and operational environment. In this work, we define five levels of escalating agent autonomy, characterized by the roles a user can take when interac…

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff
https://arxiv.org/abs/2505.23124

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
We initiate the study of a repeated principal-agent problem over a finite horizon $T$, where a principal sequentially interacts with $K\geq 2$ types of agents arriving in an adversarial order. At each round, the principal strategically chooses one of the $N$ arms to incentivize for an arriving agent of unknown type. The agent then chooses an arm based on its own utility and the provided incentive, and the principal receives a corresponding reward. The objective is to minimize regret against the…

Replaced article(s) found for q-bio.QM. https://arxiv.org/list/q-bio.QM/new
[1/1]:
- Generative diffusion model surrogates for mechanistic agent-based biological models
Comlekoglu, Toledo-Mar\'in, DeSimone, Peirce, Fox, Glazier

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

IndoorWorld: Integrating Physical Task Solving and Social Simulation in A Heterogeneous Multi-Agent Environment
Dekun Wu, Frederik Brudy, Bang Liu, Yi Wang
https://arxiv.org/abs/2506.12331

IndoorWorld: Integrating Physical Task Solving and Social Simulation in A Heterogeneous Multi-Agent Environment
Virtual environments are essential to AI agent research. Existing environments for LLM agent research typically focus on either physical task solving or social simulation, with the former oversimplifying agent individuality and social dynamics, and the latter lacking physical grounding of social behaviors. We introduce IndoorWorld, a heterogeneous multi-agent environment that tightly integrates physical and social dynamics. By introducing novel challenges for LLM-driven agents in orchestrating …

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 …

Factor-Graph-Based Passive Acoustic Navigation for Decentralized Cooperative Localization Using Bearing Elevation Depth Difference
Kalliyan Velasco, Timothy W. McLain, Joshua G. Mangelson
https://arxiv.org/abs/2506.14690

Factor-Graph-Based Passive Acoustic Navigation for Decentralized Cooperative Localization Using Bearing Elevation Depth Difference
Accurate and scalable underwater multi-agent localization remains a critical challenge due to the constraints of underwater communication. In this work, we propose a multi-agent localization framework using a factor-graph representation that incorporates bearing, elevation, and depth difference (BEDD). Our method leverages inverted ultra-short baseline (inverted-USBL) derived azimuth and elevation measurements from incoming acoustic signals and relative depth measurements to enable cooperative …

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…

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

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

Local Differential Privacy for Distributed Stochastic Aggregative Optimization with Guaranteed Optimality
Ziqin Chen, Yongqiang Wang
https://arxiv.org/abs/2506.15106

Local Differential Privacy for Distributed Stochastic Aggregative Optimization with Guaranteed Optimality
Distributed aggregative optimization underpins many cooperative optimization and multi-agent control systems, where each agent's objective function depends both on its local optimization variable and an aggregate of all agents' optimization variables. Existing distributed aggregative optimization approaches typically require access to accurate gradients of the objective functions, which, however, are often hard to obtain in real-world applications. For example, in machine learning, gradients ar…

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 …

Code Researcher: Deep Research Agent for Large Systems Code and Commit History
Ramneet Singh, Sathvik Joel, Abhav Mehrotra, Nalin Wadhwa, Ramakrishna B Bairi, Aditya Kanade, Nagarajan Natarajan
https://arxiv.org/abs/2506.11060

Code Researcher: Deep Research Agent for Large Systems Code and Commit History
Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code remains underexplored. Due to the size and complexities of systems code, making changes to a systems codebase is a daunting task, even for humans. It requires researching about many pieces of context, derived from the large codebase and its massive commit history, before making changes. Inspired by the recent progress on deep research agents, we design the fi…

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

StorySage: Conversational Autobiography Writing Powered by a Multi-Agent Framework
Shayan Talaei, Meijin Li, Kanu Grover, James Kent Hippler, Diyi Yang, Amin Saberi
https://arxiv.org/abs/2506.14159

StorySage: Conversational Autobiography Writing Powered by a Multi-Agent Framework
Every individual carries a unique and personal life story shaped by their memories and experiences. However, these memories are often scattered and difficult to organize into a coherent narrative, a challenge that defines the task of autobiography writing. Existing conversational writing assistants tend to rely on generic user interactions and pre-defined guidelines, making it difficult for these systems to capture personal memories and develop a complete biography over time. We introduce Story…

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.

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems
Yingfan Deng, Anhao Zhou, Yuan Yuan, Xian Zhang, Yifei Zou, Dongxiao Yu
https://arxiv.org/abs/2506.11803

PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems
Multi-Agent Systems have recently emerged as a promising paradigm for collaborative reasoning and solving complex tasks. However, the design of collaborative learning algorithms in multi-agent systems faces several challenges, including high communication overhead and insufficient agent-level personalization. In this paper, we propose PE-MA (Parameter-Efficient Multi-Agent Co-Evolution), a novel collaboration framework that supports efficient, scalable, and personalized co-evolution in multi-ag…

Should the Dallas Cowboys target top NFL free agent Asante Samuel Jr? https://www.si.com/nfl/cowboys/news/should-dallas-cowboys-target-top-nfl-free-agent-asante-samuel-jr

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

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, …

Recently Released Raiders Starter Sends Clear Message to NFL Teams https://heavy.com/sports/nfl/las-vegas-raiders/jack-jones-free-agent-future/?adt_ei=[email]

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…

Robot Context Protocol (RCP): A Runtime-Agnostic Interface for Agent-Aware Robot Control
Lambert Lee, Joshua Lau
https://arxiv.org/abs/2506.11650 https://

Robot Context Protocol (RCP): A Runtime-Agnostic Interface for Agent-Aware Robot Control
The Robot Context Protocol (RCP) is a lightweight, middleware-agnostic communication protocol designed to simplify the complexity of robotic systems and enable seamless interaction between robots, users, and autonomous agents. RCP provides a unified and semantically meaningful interface that decouples client-facing operations from backend implementations, supporting a wide range of deployment environments including physical robots, cloud-based orchestrators, and simulated platforms. Built on HT…

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…

‘Plausible’ Chance Cowboys Part Ways With $3 Million Free Agent RB https://heavy.com/sports/nfl/dallas-cowboys/part-ways-free-agent-javonte-williams/?adt_ei=[email]

Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
Jianhong Wang, Yang Li, Samuel Kaski, Jonathan Lawry
https://arxiv.org/abs/2506.11285

Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
Open multi-agent systems are increasingly important in modeling real-world applications, such as smart grids, swarm robotics, etc. In this paper, we aim to investigate a recently proposed problem for open multi-agent systems, referred to as n-agent ad hoc teamwork (NAHT), where only a number of agents are controlled. Existing methods tend to be based on heuristic design and consequently lack theoretical rigor and ambiguous credit assignment among agents. To address these limitations, we model a…

This https://arxiv.org/abs/2506.02841 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Ensemble-MIX: Enhancing Sample Efficiency in Multi-Agent RL Using Ensemble Methods
Multi-agent reinforcement learning (MARL) methods have achieved state-of-the-art results on a range of multi-agent tasks. Yet, MARL algorithms typically require significantly more environment interactions than their single-agent counterparts to converge, a problem exacerbated by the difficulty in exploring over a large joint action space and the high variance intrinsic to MARL environments. To tackle these issues, we propose a novel algorithm that combines a decomposed centralized critic with d…

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…

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…

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…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[7/8]:
Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing

Can you see how I learn? Human observers' inferences about Reinforcement Learning agents' learning processes
Bernhard Hilpert, Muhan Hou, Kim Baraka, Joost Broekens
https://arxiv.org/abs/2506.13583

Can you see how I learn? Human observers' inferences about Reinforcement Learning agents' learning processes
Reinforcement Learning (RL) agents often exhibit learning behaviors that are not intuitively interpretable by human observers, which can result in suboptimal feedback in collaborative teaching settings. Yet, how humans perceive and interpret RL agent's learning behavior is largely unknown. In a bottom-up approach with two experiments, this work provides a data-driven understanding of the factors of human observers' understanding of the agent's learning process. A novel, observation-based paradi…

Is Talanoa Hufanga the next great Broncos safety? https://www.espn.com/nfl/story/_/id/45480888/broncos-safety-talanoa-hufanga-free-agent-signing-excitement-injuries-fit

The Raiders are hoping to get a 2-for-1 deal with their top free agent addition https://raiderswire.usatoday.com/story/sports/nfl/raiders/2025/06/09/raiders-versatile-db-jerem…

Deceptive Path Planning: A Bayesian Game Approach
Violetta Rostobaya, James Berneburg, Yue Guan, Michael Dorothy, Daigo Shishika
https://arxiv.org/abs/2506.13650

Deceptive Path Planning: A Bayesian Game Approach
This paper investigates how an autonomous agent can transmit information through its motion in an adversarial setting. We consider scenarios where an agent must reach its goal while deceiving an intelligent observer about its destination. We model this interaction as a dynamic Bayesian game between a mobile Attacker with a privately known goal and a Defender who infers the Attacker's intent to allocate defensive resources effectively. We use Perfect Bayesian Nash Equilibrium (PBNE) as our solut…

Hierarchical Multi-Agent Reinforcement Learning-based Coordinated Spatial Reuse for Next Generation WLANs
Jiaming Yu, Le Liang, Hao Ye, Shi Jin
https://arxiv.org/abs/2506.14187

Hierarchical Multi-Agent Reinforcement Learning-based Coordinated Spatial Reuse for Next Generation WLANs
High-density Wi-Fi deployments often result in significant co-channel interference, which degrades overall network performance. To address this issue, coordination of multi access points (APs) has been considered to enable coordinated spatial reuse (CSR) in next generation wireless local area networks. This paper tackles the challenge of downlink spatial reuse in Wi-Fi networks, specifically in scenarios involving overlapping basic service sets, by employing hierarchical multi-agent reinforceme…

This https://arxiv.org/abs/2410.04444 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Gödel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement
The rapid advancement of large language models (LLMs) has significantly enhanced the capabilities of AI-driven agents across various tasks. However, existing agentic systems, whether based on fixed pipeline algorithms or pre-defined meta-learning frameworks, cannot search the whole agent design space due to the restriction of human-designed components, and thus might miss the globally optimal agent design. In this paper, we introduce Gödel Agent, a self-evolving framework inspired by the Göde…

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.

Jonnu Smith's agent says Dolphins Pro Bowl tight end 'would definitely like to stay in Miami'

https://www.cbssports.com/nfl/news/jonnu-s

This https://arxiv.org/abs/2502.14847 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Red-Teaming LLM Multi-Agent Systems via Communication Attacks
Large Language Model-based Multi-Agent Systems (LLM-MAS) have revolutionized complex problem-solving capability by enabling sophisticated agent collaboration through message-based communications. While the communication framework is crucial for agent coordination, it also introduces a critical yet unexplored security vulnerability. In this work, we introduce Agent-in-the-Middle (AiTM), a novel attack that exploits the fundamental communication mechanisms in LLM-MAS by intercepting and manipulat…

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Hongjun Wu, Heng Zhang, Pengsong Zhang, Jin Wang, Cong Wang
https://arxiv.org/abs/2506.08296

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Recent advances in multimodal vision-language-action (VLA) models have revolutionized traditional robot learning, enabling systems to interpret vision, language, and action in unified frameworks for complex task planning. However, mastering complex manipulation tasks remains an open challenge, constrained by limitations in persistent contextual memory, multi-agent coordination under uncertainty, and dynamic long-horizon planning across variable sequences. To address this challenge, we propose \…

One Free Agent Signing The Las Vegas Raiders Would Greatly Benefit From https://raiderramble.com/2025/06/03/one-free-agent-las-vegas-raiders-would-greatly-benefit-from/

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…

Steelers not expected to trade for Jonnu Smith, per report, agent says TE wants to remain with Dolphins

https://www.cbssports.com/nfl/news/steeler…

The Automated but Risky Game: Modeling Agent-to-Agent Negotiations and Transactions in Consumer Markets
Shenzhe Zhu, Jiao Sun, Yi Nian, Tobin South, Alex Pentland, Jiaxin Pei
https://arxiv.org/abs/2506.00073

The Automated but Risky Game: Modeling Agent-to-Agent Negotiations and Transactions in Consumer Markets
AI agents are increasingly used in consumer-facing applications to assist with tasks such as product search, negotiation, and transaction execution. In this paper, we explore a future scenario where both consumers and merchants authorize AI agents to fully automate negotiations and transactions. We aim to answer two key questions: (1) Do different LLM agents vary in their ability to secure favorable deals for users? (2) What risks arise from fully automating deal-making with AI agents in consum…

Bills $21 million free agent starter predicted to sign with Raiders https://www.sportingnews.com/us/nfl/las-vegas-raiders/news/bills-21-million-free-agent-starter-predicted-sign-raiders/c321a5…

Agent's Take: Inside the Bengals' contract issues with Trey Hendrickson and why there's no clear end in sight

https://www.cbssports.…

It’s Super Bowl or Bust for This Raiders Free Agent Signing https://heavy.com/sports/nfl/las-vegas-raiders/super-bowl-or-bust-free-agent/?adt_ei=[email]

G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems
Guibin Zhang, Muxin Fu, Guancheng Wan, Miao Yu, Kun Wang, Shuicheng Yan
https://arxiv.org/abs/2506.07398

G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems
Large language model (LLM)-powered multi-agent systems (MAS) have demonstrated cognitive and execution capabilities that far exceed those of single LLM agents, yet their capacity for self-evolution remains hampered by underdeveloped memory architectures. Upon close inspection, we are alarmed to discover that prevailing MAS memory mechanisms (1) are overly simplistic, completely disregarding the nuanced inter-agent collaboration trajectories, and (2) lack cross-trial and agent-specific customiza…

Lamar Jackson urges Ravens to sign ex-Packers CB Jaire Alexander, NFL MVP's former college teammate

https://www.cbssports.com/nfl/news/lamar-j