Core Viewpoint - The article discusses the concept of Specification Alignment in large models, emphasizing the need for these models to adhere to both safety and behavioral specifications in various contexts, thereby ensuring user safety while meeting diverse behavioral requirements [3][9][30]. Group 1: Specification Alignment - Specification Alignment is introduced as a new concept requiring large models to comply with both safety specifications (safety-spec) and behavioral specifications (behavioral-spec) in different scenarios [3][9]. - Safety specifications define the boundaries that models must not cross, such as avoiding violent content in children's stories or refusing to generate malicious code [9][10]. - Behavioral specifications guide how models should operate, reflecting user or organizational preferences, such as including educational morals in stories or providing multiple travel plans [9][10]. Group 2: SpecBench and Evaluation - The research team developed SpecBench, the first benchmark for evaluating specification alignment, covering five application scenarios, 103 specifications, and 1500 prompts [6][15]. - A new metric, Specification Alignment Rate (SAR), was introduced to assess models' adherence to specifications, emphasizing the principle of "safety first, then utility" [16][30]. - Testing revealed that most models exhibited significant gaps in specification alignment, with GPT-5 showing a clear lead across all scenarios, attributed to OpenAI's safe-completion training [23][24]. Group 3: Test-time Deliberation - The article presents Test-time Deliberation (TTD) as a flexible approach to achieve specification alignment, allowing models to reflect on specifications during inference without altering model parameters [18][21]. - The Align3 method, part of TTD, effectively integrates safety and behavioral specifications into the reasoning process, enhancing model reliability [21][27]. - Experimental results indicate that TTD methods, including Align3, significantly improve specification alignment while maintaining lower computational costs compared to other methods [27][28]. Group 4: Future Outlook - Specification alignment is identified as a critical academic challenge and a key threshold for large models to integrate into society and industry [30]. - Future models must balance safety and practicality while adapting to increasingly diverse and personalized specifications [30]. - The ongoing development of SpecBench and methods like Align3 represents the initial steps toward achieving more capable and responsible AI systems [30][31].