Tag: Alignment
All the articles with the tag "Alignment".
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A Statistical Case Against Empirical Human-AI Alignment
This position paper argues against forward empirical human-AI alignment due to statistical biases and anthropocentric limitations, advocating for prescriptive and backward alignment approaches to ensure transparency and minimize bias, supported by a case study on language model decoding strategies.
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Belief Injection for Epistemic Control in Linguistic State Space
This paper proposes belief injection as a proactive epistemic control mechanism to shape AI agents' internal linguistic belief states within the Semantic Manifold framework, offering diverse strategies for guiding reasoning and alignment, though it lacks empirical validation.
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Towards Safer Pretraining: Analyzing and Filtering Harmful Content in Webscale datasets for Responsible LLMs
This paper proposes a three-dimensional taxonomy and develops TTP and HarmFormer tools to filter harmful content from web-scale LLM pretraining datasets, revealing significant toxicity prevalence and persistent safety gaps through benchmarks like HAVOC.
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Reward Reasoning Model
本文提出奖励推理模型(RRMs),通过链式推理过程在生成奖励前自适应利用测试时计算资源,在多个奖励建模基准和实际应用中显著提升性能,尤其在复杂推理任务上表现优异。
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Beyond Output Matching: Bidirectional Alignment for Enhanced In-Context Learning
本文提出双向对齐(BiAlign)方法,通过对齐学生模型与教师模型的令牌级输出分布和输入偏好,显著提升了学生模型的上下文学习能力,并在多种任务上取得了优于基线的结果。