提出REAR方法，在推理阶段通过奖励分解实现偏好重新对齐，为大模型对齐提供高效新解法。
arXiv:2606.30339v1 Announce Type: cross Abstract: Aligning large language models (LLMs) with diverse user preferences is a critical yet challenging ta…
通过偏好对进行推理时对齐，提出高效方案避免昂贵微调
arXiv:2606.24004v1 Announce Type: cross Abstract: Steering a large language model (LLM) toward a desired behavior typically relies on an iterative pro…
紧凑模型代理也能玩转复杂工具链？这篇论文提出推理时进化工作流，让小型语言模型自主发现、编排和执行MCP工具，实现成本与性能双赢。
arXiv:2606.12674v1 Announce Type: new Abstract: Compact language models (LMs) reduce cost, latency, and deployment risk for tool agents. Yet MCP-style…