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No single LLM excels across all dimensions of long-horizon business operations, revealing critical trade-offs in performance metrics like asset growth and fraud avoidance.
Qwen-AgentWorld achieves unprecedented simulation fidelity, outperforming existing models and enabling scalable agentic reinforcement learning across diverse real-world environments.
No single AI model dominates across all professional industries, revealing distinct occupational capability profiles and highlighting the need for specialized AI development.
Vector fields can guide differentiable policy learning to achieve agile drone racing, enabling faster convergence and better sim-to-real transfer.
ToolRMs drastically improve tool-use accuracy in LLMs, outperforming existing models by up to 17.94%, while also reducing output token usage by over 66% through efficient inference-time scaling.
