MAVEN: Improving Generalization in Agentic Tool Calling

📰 ArXiv cs.AI

Learn how MAVEN improves generalization in agentic tool calling for reliable reasoning systems

advanced Published 1 Jun 2026
Action Steps
  1. Implement MAVEN as a modular symbolic reasoning scaffold
  2. Use MAVEN to compose reasoning strategies across domains
  3. Preserve intermediate states using MAVEN's verification mechanism
  4. Coordinate tools across environments with MAVEN's execution network
  5. Evaluate MAVEN's performance on individual benchmarks and across domains
Who Needs to Know This

AI researchers and engineers working on agentic reasoning systems can benefit from MAVEN to improve generalization across environments

Key Insight

💡 MAVEN provides a lightweight symbolic reasoning scaffold to improve generalization in agentic tool calling

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🤖 Improve generalization in agentic tool calling with MAVEN! 🚀

Key Takeaways

Learn how MAVEN improves generalization in agentic tool calling for reliable reasoning systems

Full Article

Title: MAVEN: Improving Generalization in Agentic Tool Calling

Abstract:
arXiv:2605.30738v1 Announce Type: new Abstract: Generalization across agentic tool-calling environments remains a central challenge for reliable agentic reasoning systems. Although large language models achieve strong results on individual benchmarks, their ability to compose reasoning strategies, preserve intermediate states, and coordinate tools across domains remains underexplored. We present MAVEN (Modular Agentic Verification and Execution Network), a lightweight symbolic reasoning scaffold
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