NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation

ArXi:2605.10813v1 Announce Type: new LLM-powered multi-agent systems can now automate the full research pipeline from ideation to paper writing, but a fundamental question remains: automation for whom? Researchers operate under different resource configurations, hold different methodological preferences, and target different output formats. A system that produces uniform outputs regardless of these differences will systematically under-serve every individual user, making personalization a precondition for research automation to be genuinely usable.