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Authenticated Workflows: A Systems Approach to Protecting Agentic AI
Agentic AI systems automate enterprise workflows but existing defenses--guardrails, semantic filters--are probabilistic and routinely bypassed. We introduce authenticated workflows, the first complete trust layer for enterprise agentic AI. Security r...
Les Dissonances: Cross-Tool Harvesting and Polluting in Pool-of-Tools Empowered LLM Agents
Large Language Model (LLM) agents are autonomous systems powered by LLMs, capable of reasoning and planning to solve problems by leveraging a set of tools. However, the integration of multi-tool capabilities in LLM agents introduces challenges in sec...
Agent-Based Model Framework for the North Carolina Modeling Infectious Diseases Program (N…
To help facilitate a variety of simulations related to healthcare facilities in North Carolina, we have developed an agent-based model (ABM) to accurately simulate patient (i.e., agent) movement to and from these facilities. This is an Overview, Desi...
Luka Doncic's agent has spent the last 17 years repaying a client for his mistake
In 2003, NBA agent Bill Duffy somehow forgot to notify the Miami Heat that his client, Anthony Carter, was going to exercise his $4.1m player option. This made Carter a free agent, and since he wasn't...
Voice-Enabled AI Agents can Perform Common Scams
Recent advances in multi-modal, highly capable LLMs have enabled voice-enabled AI agents. These agents are enabling new applications, such as voice-enabled autonomous customer service. However, with all AI capabilities, these new capabilities have th...
AIDev: Studying AI Coding Agents on GitHub
AI coding agents are rapidly transforming software engineering by performing tasks such as feature development, debugging, and testing. Despite their growing impact, the research community lacks a comprehensive dataset capturing how these agents are...
Protecting agent (shipping) - Wikipedia
or anticipated from the shipping agent. The main task of the protecting agent is to protect the interest of his principal during the port call for which
Policy-focused Agent-based Modeling using RL Behavioral Models
Agent-based Models (ABMs) are valuable tools for policy analysis. ABMs help analysts explore the emergent consequences of policy interventions in multi-agent decision-making settings. But the validity of inferences drawn from ABM explorations depends...
SafeSearch: Automated Red-Teaming of LLM-Based Search Agents
Search agents connect LLMs to the Internet, enabling them to access broader and more up-to-date information. However, this also introduces a new threat surface: unreliable search results can mislead agents into producing unsafe outputs. Real-world in...
On Fair Allocation of Indivisible Goods to Submodular Agents
We consider the problem of fair allocation of indivisible goods to agents with submodular valuation functions, where agents may have either equal entitlements or arbitrary (possibly unequal) entitlements. We focus on share-based fairness notions, spe...
Target Defense Using a Turret and Mobile Defender Team
A scenario is considered wherein a stationary, turn constrained agent (Turret) and a mobile agent (Defender) cooperate to protect the former from an adversarial mobile agent (Attacker). The Attacker wishes to reach the Turret prior to getting capture...
The Division of Surplus and the Burden of Proof
A principal and an agent divide a surplus. Only the agent knows the surplus' true size and decides how much of it to reveal initially. Both parties can exert costly effort to conclusively prove the surplus' true size. The agent's liability is bounded...
Message passing-based inference in an autoregressive active inference agent
We present the design of an autoregressive active inference agent in the form of message passing on a factor graph. Expected free energy is derived and distributed across a planning graph. The proposed agent is validated on a robot navigation task, d...
A2Perf: Real-World Autonomous Agents Benchmark
Autonomous agents and systems cover a number of application areas, from robotics and digital assistants to combinatorial optimization, all sharing common, unresolved research challenges. It is not sufficient for agents to merely solve a given task; t...
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Real Estate Agent Carol Luciani of Davenport, IA. Read reviews, see agent listings, and contact for all your real estate needs.
Agentic Large Language Models, a survey
Background: There is great interest in agentic LLMs, large language models that act as agents. Objectives: We review the growing body of work in this area and provide a research agenda. Methods: Agentic LLMs are LLMs that (1) reason, (2) act, and...
MARTI-MARS$^2$: Scaling Multi-Agent Self-Search via Reinforcement Learning for Code Genera…
While the complex reasoning capability of Large Language Models (LLMs) has attracted significant attention, single-agent systems often encounter inherent performance ceilings in complex tasks such as code generation. Multi-agent collaboration offers...
WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?
We study the use of large language model-based agents for interacting with software via web browsers. Unlike prior work, we focus on measuring the agents' ability to perform tasks that span the typical daily work of knowledge workers utilizing enterp...
PACT: A Contract-Theoretic Framework for Pricing Agentic AI Services Powered by Large Lang…
Agentic AI, often powered by large language models (LLMs), is becoming increasingly popular and adopted to support autonomous reasoning, decision-making, and task execution across various domains. While agentic AI holds great promise, its deployment...