针对LLM智能体的提示词优化新方法，把约束条件纳入优化过程，让Agent更懂规则、少犯错。
arXiv:2608.16068v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as agents that rely on system prompts to use …
UZH共享任务2026论文：基于约束感知检索与选择性辩论的段落级论证挖掘新方法
arXiv:2607.20430v1 Announce Type: cross Abstract: We present LLM-INSTRUCT, the winning system for the UZH Shared Task at ArgMining 2026 on paragraph-l…
PCB布局AI评测首次耦合原理图与多模态数据，考验约束感知几何推理，为电路智能设计立标杆。
arXiv:2607.03261v1 Announce Type: new Abstract: Recent large language models (LLMs) have demonstrated remarkable progress in 3D spatial reasoning, spa…
引入约束感知强化学习，让LLM规划不再“天马行空”，ACL 2026最新研究。
arXiv:2607.04854v1 Announce Type: new Abstract: Despite their strong reasoning capabilities and extensive world knowledge, Large Language Models (LLMs…