Papers/2610.36077
🧪 Test?View on arXiv

The Trinity: Capability-Driven Recursive Self-Improvement for Multimodal Agents

Author1, Author2, Author3, Author4, Author5

multimodalself-improvementcapability-drivenrecursive learning
2610.36077
Builder Relevance
80%
1h ago

Abstract

The paper introduces a framework for recursive self-improvement in multimodal agents, addressing the challenges of environment construction and task complexity.

Reality Card

Core Claim

The Trinity framework improves mean performance by 34 points across 28 training benchmarks and 26 points across 18 unseen benchmarks through a capability-driven approach.

Method / Result

Evolved Harnesses improve mean performance by 34 points across 28 training benchmarks.

Limitations

The complexity of constructing heterogeneous, verifiable environments may hinder reproducibility.

Paper to code

Verified implementation resources so builders can test the paper’s claims instead of stopping at the abstract.

No verified implementation link has been attached yet. AIBuzzHub will keep this panel separate from unverified search results.
← Back to all papers