Agentic data science with the Data Agent Kit
cloud.google.com·6h ago
AI Research
arXiv CS.AI·25d ago·5 min read
Symbolic Temporal Supervision of LLM Agents Using Contracts
TL;DR
ContrAgent is a contract-based framework that provides symbolic temporal supervision for large language model (LLM) agents, ensuring safe and deterministic tool usage. It effectively reduces latency and matches state-of-the-art performance in both online and offline evaluations.
✦ Why It Matters
Implement ContrAgent to enhance the safety and efficiency of your LLM applications today.
Key Takeaways
- Utilize ContrAgent for safer LLM agent operations.
- Leverage the contract library for reusable knowledge.
- Implement assume-guarantee contracts to formalize agent behavior.
- Reduce latency in tool calls with deterministic evaluations.
How It Works
ContrAgent captures the behavior of LLM agents by recording their tool calls as a sequence, which is then formalized using assume-guarantee contracts in linear temporal logic (LTLf). These contracts are compiled into deterministic finite automata (DFA), which serve dual purposes: they gate agent actions in real-time and evaluate recorded actions for compliance with safety standards.
This approach allows for both proactive and retrospective supervision of agent behavior.