Mimosa Framework: Adaptive Multi-Agent Systems for Science
Discover Mimosa, an evolving multi-agent framework that automates and refines scientific workflows using dynamic tools and AI-driven feedback.
Boost Policy Learning with World-Action Model (WAM)
Discover how the World-Action Model (WAM) enhances AI policy learning with improved action prediction and higher success rates in manipulation tasks.
Emergent Social Dynamics in Semi-Autonomous AI Agents
Explore how semi-autonomous AI agents form complex social structures and the implications for governance and AI system stability.
Category-Theoretic Framework for Comparing AGI Models
Explore a novel category-theoretic framework to compare and evaluate diverse Artificial General Intelligence architectures and guide future AGI research.
ChartDiff: Benchmark for Comparative Chart Understanding
Discover ChartDiff, a large-scale benchmark designed to improve AI models in comparing and summarizing pairs of charts effectively.