DART is a modular runtime that certifies semantically recoverable boundaries for failed tool-agent instances and selects admissible restore points that preserve downstream commitments or blocks recovery.
Autonomous control leveraging
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 3verdicts
UNVERDICTED 3roles
background 1polarities
support 1representative citing papers
A systematic review of LLM applications in process systems engineering finds genuine utility for natural-language tasks but persistent challenges for real-time execution, constraint satisfaction, and safety guarantees.
The paper proposes a bidirectional continuum between LLMs and control systems, covering LLM-assisted controller design, control-based LLM steering, and state-space modeling of LLMs.
citing papers explorer
-
DART: Semantic Recoverability for Structured Tool Agents
DART is a modular runtime that certifies semantically recoverable boundaries for failed tool-agent instances and selects admissible restore points that preserve downstream commitments or blocks recovery.
-
Large Language Models in Process Systems Engineering: Opportunities, Architectures, and Industrial Deployment Challenges
A systematic review of LLM applications in process systems engineering finds genuine utility for natural-language tasks but persistent challenges for real-time execution, constraint satisfaction, and safety guarantees.
-
When control meets large language models: From words to dynamics
The paper proposes a bidirectional continuum between LLMs and control systems, covering LLM-assisted controller design, control-based LLM steering, and state-space modeling of LLMs.