只需一个例子，就能轻松调整大模型行为。
EasyEdit2: An Easy-to-use Steering Framework for Editing Large Language Models
- 通过自动生成并应用控制向量，实现不修改参数的模型行为调节。
- 支持安全、情感、个性等多类行为干预，跨多个大模型验证有效。
- 零技术门槛，适合非专业用户快速精准控制模型输出。
本文提出 EasyEdit2，一个即插即用的大语言模型行为调控框架。该框架支持多种运行时干预，包括安全性、情感倾向、人格特征、推理模式、事实准确性及语言特性等。相较于前代，EasyEdit2采用新架构，包含控制向量生成器与应用模块，可自动生成并注入控制向量，无需修改模型参数即可引导其行为。主要优势在于易用性：仅需一个示例，用户即可高效精准地调整模型输出。我们在多个大模型上进行了实证评估，验证了该方法的有效性。源代码已开源至 GitHub（https://github.com/zjunlp/EasyEdit），并提供演示笔记和视频（https://www.youtube.com/watch?v=AkfoiPfp5rQ）以快速上手。
原文摘要 · Abstract (English)
In this paper, we introduce EasyEdit2, a framework designed to enable plug-and-play adjustability for controlling Large Language Model (LLM) behaviors. EasyEdit2 supports a wide range of test-time interventions, including safety, sentiment, personality, reasoning patterns, factuality, and language features. Unlike its predecessor, EasyEdit2 features a new architecture specifically designed for seamless model steering. It comprises key modules such as the steering vector generator and the steering vector applier, which enable automatic generation and application of steering vectors to influence the model's behavior without modifying its parameters. One of the main advantages of EasyEdit2 is its ease of use-users do not need extensive technical knowledge. With just a single example, they can effectively guide and adjust the model's responses, making precise control both accessible and efficient. Empirically, we report model steering performance across different LLMs, demonstrating the effectiveness of these techniques. We have released the source code on GitHub at https://github.com/zjunlp/EasyEdit along with a demonstration notebook. In addition, we provide a demo video at https://www.youtube.com/watch?v=AkfoiPfp5rQ for a quick introduction.
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