可视化工具助你定位与编辑Transformer中的知识
KnowledgeDebugger -- an Exploration Tool for Knowledge Localization and Editing in Transformers
- 基于GUI的无代码工具，可快速探索模型知识
- 集成EasyEdit库，支持主流知识编辑方法
- 适合研究人员快速验证知识定位与修改想法
近期研究日益关注Transformer如何存储和处理知识，以及如何对这些知识进行编辑。该领域工作通常分为两个阶段：首先在单个样本上探索现象；若结果有潜力，再开展更统计稳健的实验。为支持第一阶段，我们提出KnowledgeDebugger，一个基于GUI的知识定位与编辑探索工具。该工具受LM-Debugger启发，提供对EasyEdit（一个广泛使用的先进知识编辑方法库）的无代码访问。通过近期该领域发现的案例研究，我们展示了该工具的有效性。
原文摘要 · Abstract (English)
Recent research has increasingly focused on understanding how Transformers store and process knowledge, as well as how this knowledge can be edited. Research work in this area is often conducted in two phases: first, phenomena are explored on individual samples. Then, when results appear promising, more statistically robust experiments follow. To support the first phase, we propose KnowledgeDebugger, a GUI-based exploration tool for knowledge localization and editing in Transformers. Our tool - inspired by LM-Debugger - offers no-code access to the methods in EasyEdit, a widely used library of state-of-the-art Knowledge Editing approaches. We demonstrate the tool's effectiveness through case studies of recent findings in this field.
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