This paper introduces tap, a file-based collaboration protocol enabling LLM agents from different vendors to collaborate on a shared codebase without shared memory or identical runtimes.

The paper proposes Multi-Agent Computer Use (MACU) systems, which significantly improve performance on complex, long-horizon tasks by enabling parallel execution and dynamic task decomposition compare…

The paper introduces Language-Based Agent Control (LBAC), a new programming model that extends static typing and runtime enforcement guarantees to agentic applications, ensuring that agent-generated c…

Agent libOS introduces a library-OS-inspired runtime substrate that treats LLM agents as schedulable processes, providing explicit capability control and robust auditing for long-running, stateful age…

The paper introduces CBCL, a provably safe and extensible agent communication language that constrains all message extensions to the deterministic context-free language (DCFL) class.

The paper introduces MAAD, a multi-agent framework that autonomously transforms software requirements into comprehensive, multi-view architectural blueprints, significantly improving completeness and…

This paper studies AI development frameworks for software engineering and proposes a six-dimension process taxonomy.

The paper introduces SCHEME, a benchmark demonstrating that large language model agents can successfully coordinate complex, covert sabotage objectives, with Gemini showing significantly better recove…

The paper introduces AC4A, an access control framework that allows users to precisely limit the capabilities of LLM agents, ensuring they only access the specific APIs or parts of web pages necessary…

Agentic-J is a containerized, multi-agent AI assistant designed to enable biologists to perform complex, reproducible biological microscopy image analysis by specifying tasks in natural language.

The paper proposes Multi-Order Communication (MOC) to overcome the limitations of standard first-order message passing in LLM-based multi-agent systems, significantly improving performance by capturin…

This paper presents EurekAgent, an environment-engineered agent system for metric-driven autonomous scientific discovery.

The paper proposes an empowerment-guided multi-agent system that uses semantic checkpoints and structured communication to ensure that complex scientific computing workflows maintain semantic consiste…

The paper introduces StreamMA, a streaming multi-agent reasoning system that significantly reduces latency and improves effectiveness by passing reasoning steps to downstream agents as they are genera…

This paper introduces Selective Field Transmission (SFT), a mechanism that dynamically adapts transmitted message components to each receiver's needs in publish-subscribe systems, achieving significan…

The paper proposes Proof-Carrying Agent Actions (PCAA), a runtime-neutral governance model that uses action certificates to consistently track and authorize high-risk actions across diverse and hetero…

The paper introduces a systematic framework and defense mechanisms to analyze and mitigate autonomous LLM agent worms that propagate through persistent agent state and cross-platform multi-agent syste…

AgenticVM is a multi-agent framework that uses LLMs and specialized tools to automate and drastically reduce the volume of software vulnerabilities into actionable, prioritized queues.

The paper proposes Sello, a novel protocol that allows an owner to reconstruct a tamper-evident and verifiable record of AI agent actions by having a trusted receiver sign and publish receipts of the…

The paper proposes the concept of an Agent Operating System (AOS) to provide a necessary systems foundation for managing the unique, non-deterministic, and goal-directed execution characteristics of m…