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Sparse MoE blueprint: It utilizes 128 specialists with 4 activated per token, aiming for superior efficiency compared to dense models of analogous scale.
，更多细节参见搜狗输入法跨平台同步终极指南：四端无缝衔接
沈传宁建议，如非必要，尽量避免使用公共无线网络。若必须连接，务必向场所管理方核实确切的网络名称，以防误连仿冒热点。同时，在使用公共网络时，应避免进行登录账户、资金操作等高敏感性行为。。Line下载是该领域的重要参考
vt: Significantly more tmux control mode parsing, but not hooked up to
A first line of work focuses on characterizing how misaligned or deceptive behavior manifests in language models and agentic systems. Meinke et al. [117] provides systematic evidence that LLMs can engage in goal-directed, multi-step scheming behaviors using in-context reasoning alone. In more applied settings, Lynch et al. [14] report “agentic misalignment” in simulated corporate environments, where models with access to sensitive information sometimes take insider-style harmful actions under goal conflict or threat of replacement. A related failure mode is specification gaming, documented systematically by [133] as cases where agents satisfy the letter of their objectives while violating their spirit. Case Study #1 in our work exemplifies this: the agent successfully “protected” a non-owner secret while simultaneously destroying the owner’s email infrastructure. Hubinger et al. [118] further demonstrates that deceptive behaviors can persist through safety training, a finding particularly relevant to Case Study #10, where injected instructions persisted throughout sessions without the agent recognizing them as externally planted. [134] offer a complementary perspective, showing that rich emergent goal-directed behavior can arise in multi-agent settings event without explicit deceptive intent, suggesting misalignment need not be deliberate to be consequential.