Summary of Self-control Of Llm Behaviors by Compressing Suffix Gradient Into Prefix Controller, By Min Cai and Yuchen Zhang and Shichang Zhang and Fan Yin and Dan Zhang and Difan Zou and Yisong Yue and Ziniu Hu
Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller
by Min Cai, Yuchen Zhang, Shichang Zhang, Fan Yin, Dan Zhang, Difan Zou, Yisong Yue, Ziniu Hu
First submitted to arxiv on: 4 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed SelfControl method utilizes gradients to control the behavior of large language models (LLMs) without explicit human annotations. Given a desired behavior expressed in a natural language suffix string concatenated to the input prompt, SelfControl computes gradients of the LLM’s self-evaluation of the suffix with respect to its latent representations. The gradients are used to directly control the auto-regressive generation process towards desired behaviors, which eliminates human supervision, achieves precise and transparent control, and offers on-the-fly adaptability. SelfControl_{Prefix} is a compact module that encapsulates the learned representations from gradients into SelfControl_{Prefix}, facilitating efficient inference-time control with no latency compared to the original model and allowing control for multiple behaviors simultaneously. The method’s efficacy is demonstrated across multiple domains, including detoxification, truthfulness enhancement, controlling on emotion tones, and privacy protection. The experiments show that SelfControl improves over SOTA by 8.3% in detoxification, 3.1% in truthfulness enhancement, 4%~10% in controlling on emotion tones, and 48.2% in privacy protection, i.e., completely remove privacy leakage issue. Additionally, the method can be used for data synthesis and to improve reasoning abilities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The SelfControl method allows you to control large language models without any human supervision. This is done by giving the model a special instruction, which it uses to change its behavior. The model learns to do this by looking at how well it’s doing based on what it thinks about the instruction. This makes the process very efficient and flexible. The results show that SelfControl can be used in different areas such as cleaning up text, making text more honest, controlling the tone of the text, and keeping personal information private. It even works better than other methods by a lot! |
Keywords
» Artificial intelligence » Inference » Prompt
