EvidenT repairs 53.88% of real-world RISC-V system-level package build failures by preserving repair history and build artifacts in a closed-loop validation system, outperforming baselines by a wide margin.
Multi-Agent MCP Architecture for Enterprise Integration,
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The paper proposes Context-Aware Broker Protocol, Adaptive Timeout Budget Allocation, and Structured Error Recovery Framework to address gaps in identity, budgeting, and error handling for production AI agent deployments using MCP.
Context-mediated domain adaptation treats user modifications to AI artifacts as implicit domain specifications that reshape LLM-powered multi-agent reasoning, demonstrated via the Seedentia system which extracted 46 domain knowledge entries from expert edits.
citing papers explorer
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EvidenT: An Evidence-Preserving Framework for Iterative System-Level Package Repair
EvidenT repairs 53.88% of real-world RISC-V system-level package build failures by preserving repair history and build artifacts in a closed-loop validation system, outperforming baselines by a wide margin.
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Bridging Protocol and Production: Design Patterns for Deploying AI Agents with Model Context Protocol
The paper proposes Context-Aware Broker Protocol, Adaptive Timeout Budget Allocation, and Structured Error Recovery Framework to address gaps in identity, budgeting, and error handling for production AI agent deployments using MCP.
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Context-Mediated Domain Adaptation in Multi-Agent Sensemaking Systems
Context-mediated domain adaptation treats user modifications to AI artifacts as implicit domain specifications that reshape LLM-powered multi-agent reasoning, demonstrated via the Seedentia system which extracted 46 domain knowledge entries from expert edits.