The paper proposes a modular agent framework and novel learning methods to design and optimize practical, cost-effective, and controllable LLM-based agentic systems.

The paper introduces a unified framework to fairly evaluate LLM agentic capabilities by standardizing diverse benchmarks and separating the effects of the LLM model from the surrounding framework and…

The paper proposes a compositional governance framework to provide richer, dynamic authorization semantics necessary for governing autonomous agentic AI systems, moving beyond traditional static IAM m…

The paper proposes the Layered Attack Surface Model (LASM), a structural taxonomy that maps security threats and defenses across the complex, multi-layered architecture of AI agents, revealing signifi…

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 introduces HORIZON, a self-evolving agent framework for hardware design using git operations.

This tutorial explores advances and challenges in deploying large language model-based agentic systems across industries, with a focus on reasoning and planning, multi-agent coordination, and evaluati…

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

MOSAIC introduces a structured agentic framework that treats automated data science as a staged, context-grounded model selection problem, improving performance and traceability over traditional AutoM…

MemPro introduces a system-level evolution framework that treats the entire memory construction-retrieval pipeline as an evolvable program, significantly improving long-horizon agent performance over…

This paper investigates the forensic analysis of agentic AI systems using OpenClaw, proposing an agent artifact taxonomy and highlighting the challenges posed by non-determinism in agent-mediated exec…

The paper introduces GAIATrace, a comprehensive token-level dataset, and Vidur-Agent, a simulator, to enable reproducible and detailed system-level characterization of complex multi-model agentic AI s…

This paper analyzes 25,264 agentic pull requests from 2,361 GitHub repositories to investigate adoption, productivity, and collaboration patterns of agentic coding tools.

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.

This paper presents a tutorial-and-survey on integrating agentic AI into Next-Generation Networks (NGNs), addressing the gap in protocol integration, evaluation, and standardization alignment.

This paper proposes an organizational memory for LLM-based agents to access and share enterprise-specific procedural knowledge for reliable business process execution.

The paper proposes an interaction-based legal framework for assigning tort liability when autonomous AI systems cause harm, categorizing liability based on the nature of the human-AI interaction.

The study compares agentic data retrieval using unstructured web data versus structured, semantically-annotated datasets, concluding that semantic metadata remains essential for high-precision, reliab…

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…