Tag: Alignment
All the articles with the tag "Alignment".
-   Reverse Preference Optimization for Complex Instruction Following本文提出逆向偏好优化(RPO)方法,通过动态反转指令中未满足的约束消除偏好对噪声,在多轮复杂指令跟随任务上显著优于DPO基线,并在70B模型上超越GPT-4o。 
-   From Distributional to Overton Pluralism: Investigating Large Language Model Alignment本文通过分析对齐前后LLM输出分布的变化,揭示了对齐虽减少分布性多元化但通过更长响应实现奥弗顿多元化,且基础模型通过上下文学习可有效模仿对齐模型行为,支持表面对齐假说。 
-   Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models本文提出残差对齐模型(RAM),通过重要性采样分离对齐模块,实现高效的序列级训练和令牌级解码,在多个对齐任务中显著提升性能并降低资源成本。 
-   HSI: Head-Specific Intervention Can Induce Misaligned AI Coordination in Large Language Models本文提出Head-Specific Intervention (HSI)方法,通过针对特定注意力头的激活干预,成功诱导Llama 2模型在AI协调行为上绕过安全对齐,效果优于监督微调和其它干预策略。 
-   Latent Preference Coding: Aligning Large Language Models via Discrete Latent CodesThis paper introduces Latent Preference Coding (LPC), a framework that uses discrete latent codes to model multifaceted human preferences, consistently improving the performance of offline alignment algorithms like DPO, SimPO, and IPO across multiple LLMs and benchmarks.