Reasoning-tuned LLMs align with human comprehension failure patterns under code obfuscation using the Block Model, unlike instruction-tuned variants.
Enhancing code llm training with programmer attention,
3 Pith papers cite this work. Polarity classification is still indexing.
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KYA provides a framework-agnostic trust layer using inbound pipelines, policy composition, unified trust scoring, interaction multipliers, and delegation attribution to ensure authorized, conforming, and verifiable actions in autonomous systems.
Metagente is an LLM multi-agent system using Teacher-Student collaboration that outperforms baselines on real-world software documentation summarization for requirements analysis and technical docs.
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KYA: A Framework-Agnostic Trust Layer for Autonomous Systems with Verifiable Provenance and Hierarchical Policy Composition
KYA provides a framework-agnostic trust layer using inbound pipelines, policy composition, unified trust scoring, interaction multipliers, and delegation attribution to ensure authorized, conforming, and verifiable actions in autonomous systems.