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cs.AI2026
MCPDisCo: Seesaw-Mitigated Tuning for MCP-Native Agents
Kounianhua Du, Jianxing Liu, Shuai Shao +3
The Model Context Protocol provides a shared interaction substrate for the agentic web, allowing heterogeneous services to expose capabilities through a standardized interface. Lea…
cs.AI2026
Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning
Xuan Zhang, Zhijian Zhou, Lingfeng Qiao +6
Large language model (LLM) agents have demonstrated strong capability in sequential decision-making, yet they remains fundamentally reactive in long-horizon tasks. Unlike humans wh…