EasyEdit2: An Easy-to-use Steering Framework for Editing Large Language
  Models
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://zjunlp.github.io/project/EasyEdit2/video for a quick introduction.
68073a2d19a9fa6096218691
Ziwen Xu
admin_assigned
2025-04-22T11:02:20.981Z
6549caee44e75a7de4fee2fa
/avatars/5aea69671eb1299aaaa948d888b4b64f.svg
Xu Ziwen
user
xzwnlp
68073a2d19a9fa6096218692
Shuxun Wang
admin_assigned
2025-04-22T11:02:26.748Z
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Shuxun Wang
user
Saberlve
68073a2d19a9fa6096218693
Kewei Xu
admin_assigned
2025-04-22T11:02:36.614Z
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xukewei
user
xukewei
68073a2d19a9fa6096218694
Haoming Xu
admin_assigned
2025-04-22T11:02:43.867Z
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Haoming Xu
user
HaomingXu
68073a2d19a9fa6096218695
Mengru Wang
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Xinle Deng
admin_assigned
2025-04-22T11:02:50.386Z
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Xinle Deng
user
Linear-Matrix-Probability
68073a2d19a9fa6096218697
Yunzhi Yao
admin_assigned
2025-04-22T11:03:04.285Z
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/avatars/c0cd2c1ef58e315d9adda9d26000f625.svg
Yunzhi Yao
user
cowTodd
68073a2d19a9fa6096218698
Guozhou Zheng
68073a2d19a9fa6096218699
Huajun Chen
68073a2d19a9fa609621869a
Ningyu Zhang
admin_assigned
2025-04-22T11:02:05.015Z
620b3bbb0668e435407c8d0a
/avatars/e0fccbb2577d76088e09f054c35cffbc.svg
Ningyu Zhang
user
Ningyu
EasyEdit2: An Easy-to-use Steering Framework for Editing Large Language
  Models
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://zjunlp.github.io/project/EasyEdit2/video for a quick introduction.
EasyEdit2 is a user-friendly framework for adjusting Large Language Model behaviors through test-time steering vectors without parameter modifications.
Large Language Model steering vector generator steering vector applier model steering LLM