This paper introduces Proof-or-Stop Lifecycle Control, a method that allows lifecycle transitions only when mechanically verifiable evidence is provided, and evaluates its implementation.

This paper proposes a distributed architecture for automating and controlling multi-vendor, multi-layer IP over DWDM networks using SDN, enabling end-to-end service lifecycle automation and closed-loo…

This paper proposes an automated method to generate complete PDDL planning problems directly from Asset Administration Shell (AAS) capability models, eliminating the need for specialized planning expe…

This paper explores tools for control engineers to design socio-technical systems in a more principled and ethical manner, using feedback optimization, control of Markov decision processes, and model…

The paper proposes a comprehensive monitoring and triage methodology for agentic systems, demonstrating that structural defects mask task-level errors and require specialized monitoring scopes for det…

The paper proposes Completion at the Boundary (CaB), a method that predicts event-local completion objects using Boundary-Phase Tokens to improve the reliability of multi-step, handoff-heavy tasks for…

The paper identifies and measures a critical failure mode where LLM agents violate policies by losing or corrupting directive-bearing state during the process of assembling the decision context, and p…

The paper introduces Policy-First Tooling, a model-agnostic permission layer that significantly enhances the safety and reliability of tool-orchestrated AI workflows by enforcing explicit constraints…

The paper presents a tool-making pipeline for production LLM agents that compiles repeated steps into validated, versioned tools before deployment, reducing latency and error rate.

The paper introduces VEHBench, an engineering-native diagnostic benchmark for LLM-assisted VEH design, featuring 763 literature-grounded tasks.

The paper introduces AgentWard, a lifecycle-oriented, defense-in-depth architecture designed to systematically secure autonomous AI agents by protecting them across all stages of their operation.

The paper introduces WorldDirector, a framework for creating controllable video worlds with persistent dynamic object memory and exact visual identities.

This paper proposes coupled egocentric control, a body-following teleoperation approach for whole-body robot control, improving efficiency, reducing effort, and increasing ease of use.

This paper introduces the Always-On Evaluation Protocol (AOEP-v0) for evaluating always-on agents by focusing on state mutation and recovery obligations.

This paper proposes a conceptual model for large language model workflows, represented as persistent knowledge objects with a distinction between deterministic computation and mediated judgment.