Summary of Decoding-time Language Model Alignment with Multiple Objectives, by Ruizhe Shi et al.
Decoding-Time Language Model Alignment with Multiple Objectives
by Ruizhe Shi, Yifang Chen, Yushi Hu, Alisa Liu, Hannaneh Hajishirzi, Noah A. Smith, Simon S. Du
First submitted to arxiv on: 27 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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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 A machine learning model that can adapt to different user needs is proposed in this paper. The existing methods for optimizing language models are limited by focusing on a single objective, whereas this new approach, called multi-objective decoding (MOD), combines predictions of multiple base models based on various objectives. MOD uses a closed-form solution derived from an f-divergence regularized alignment approach and achieves better results than traditional methods. The paper shows that existing approaches can be sub-optimal in natural settings and provides optimality guarantees for MOD. Experimental results demonstrate the effectiveness of MOD, achieving 12.8% overall reward improvement when optimizing towards three objectives. Additionally, MOD is used to combine fully-finetuned language models for different tasks, reducing toxicity on Toxigen to nearly 0% and improving performance across other metrics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper proposes a new way to make language models better at understanding what people want. Right now, these models are only good at one thing, but this method lets them do many things well. It’s like having multiple smart assistants working together! The old ways of making language models work were limited because they focused on just one goal, but this new approach is more flexible and can adapt to different needs. The results show that this new way works really well, achieving big improvements in some areas. |
Keywords
» Artificial intelligence » Alignment » Machine learning
