揭秘Transformer训练中的动态机制，为AI可解释性提供新视角，大模型研究者必读。
arXiv:2410.24050v3 Announce Type: replace Abstract: Large-scale pretraining of transformers has been central to the success of foundation models. Howe…
这篇论文从机制层面探究大模型检测自杀内容的内在工作原理，并提出让因果断言更可信的方法，专业深度十足。
arXiv:2606.21078v1 Announce Type: new Abstract: Large language models are increasingly proposed for mental-health applications such as detecting suici…
颠覆认知：LLM中的巨大激活尖峰并非噪声，而是模型学习的偏差向量，并基于此提出无尖峰量化方法。
arXiv:2606.02288v1 Announce Type: new Abstract: Massive activation spikes in Large Language Models (LLMs) severely degrade quantization by stretching …
提出一种机制性解释策略，为可解释人工智能提供全新理论框架。
arXiv:2411.01332v5 Announce Type: replace-cross Abstract: Despite significant advancements in XAI, scholars note a persistent lack of solid conceptual…