突破线性限制，LLM行为控制新范式：可逆潜在变换实现更灵活激活引导
arXiv:2606.08454v1 Announce Type: new Abstract: Activation steering provides a lightweight inference-time mechanism for controlling large language mod…
通过对话偏好优化学习导师角色向量，精准引导LLM行为，ACL工作坊论文揭秘全新控制方法。
arXiv:2602.07639v2 Announce Type: replace Abstract: With the emergence of large language models (LLMs) as a powerful class of generative artificial in…
微软新规范让开发者精准定义AI智能体的行为边界，合规更高效。
The specification lets developer, compliance, and security teams define their own policies for agents to follow in portable policy files.
概念异质性感知的表示引导，突破单一方向局限，精准控制大模型行为
arXiv:2603.02237v2 Announce Type: replace Abstract: Representation steering offers a lightweight mechanism for controlling the behavior of large langu…
论文提出通过分段级注释优化提示工程，高效控制大模型行为，显著降低计算开销与搜索空间。
arXiv:2605.14561v1 Announce Type: new Abstract: Prompt engineering is crucial for effective interaction with generative artificial intelligence system…