title: EasyEdit2: An Easy-to-use Steering Framework for Editing Large Language
    Models
summary: 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.
paper_authors._id: 68073a2d19a9fa6096218691
paper_authors.name: Ziwen Xu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-22T11:02:20.981Z
paper_authors._id: 6549caee44e75a7de4fee2fa
paper_authors.avatarUrl: /avatars/5aea69671eb1299aaaa948d888b4b64f.svg
paper_authors.fullname: Xu Ziwen
paper_authors.type: user
paper_authors.user: xzwnlp
paper_authors._id: 68073a2d19a9fa6096218692
paper_authors.name: Shuxun Wang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-22T11:02:26.748Z
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paper_authors.fullname: Shuxun Wang
paper_authors.type: user
paper_authors.user: Saberlve
paper_authors._id: 68073a2d19a9fa6096218693
paper_authors.name: Kewei Xu
paper_authors.status: admin_assigned
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paper_authors.fullname: xukewei
paper_authors.type: user
paper_authors.user: xukewei
paper_authors._id: 68073a2d19a9fa6096218694
paper_authors.name: Haoming Xu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-22T11:02:43.867Z
paper_authors._id: 66f4bdbdc51768d9d4498d16
paper_authors.avatarUrl: /avatars/0f6ded5fd9cf4e6f0b180b5aa329ea33.svg
paper_authors.fullname: Haoming Xu
paper_authors.type: user
paper_authors.user: HaomingXu
paper_authors._id: 68073a2d19a9fa6096218695
paper_authors.name: Mengru Wang
paper_authors._id: 68073a2d19a9fa6096218696
paper_authors.name: Xinle Deng
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-22T11:02:50.386Z
paper_authors._id: 65cad52fd6c974694fc20b8e
paper_authors.avatarUrl: /avatars/8232a7c5db590ed26751a47c45d481b8.svg
paper_authors.fullname: Xinle Deng
paper_authors.type: user
paper_authors.user: Linear-Matrix-Probability
paper_authors._id: 68073a2d19a9fa6096218697
paper_authors.name: Yunzhi Yao
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-22T11:03:04.285Z
paper_authors._id: 6122fbe636a4c36a99dbea7b
paper_authors.avatarUrl: /avatars/c0cd2c1ef58e315d9adda9d26000f625.svg
paper_authors.fullname: Yunzhi Yao
paper_authors.type: user
paper_authors.user: cowTodd
paper_authors._id: 68073a2d19a9fa6096218698
paper_authors.name: Guozhou Zheng
paper_authors._id: 68073a2d19a9fa6096218699
paper_authors.name: Huajun Chen
paper_authors._id: 68073a2d19a9fa609621869a
paper_authors.name: Ningyu Zhang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-04-22T11:02:05.015Z
paper_authors._id: 620b3bbb0668e435407c8d0a
paper_authors.avatarUrl: /avatars/e0fccbb2577d76088e09f054c35cffbc.svg
paper_authors.fullname: Ningyu Zhang
paper_authors.type: user
paper_authors.user: Ningyu
paper_title: EasyEdit2: An Easy-to-use Steering Framework for Editing Large Language
    Models
paper_summary: 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.
paper_ai_summary: EasyEdit2 is a user-friendly framework for adjusting Large Language Model behaviors through test-time steering vectors without parameter modifications.
paper_ai_keywords: Large Language Model steering vector generator steering vector applier model steering LLM