Structured Generation: The Secret to Boosting Large Language Model Performance

Word count: 889 Estimated reading time: 4 minutes

Hey there, AI enthusiasts! If you're working with large language models (LLMs), you might be wondering how to get the most out of their performance. Well, buckle up because we've got some exciting findings to share with you. It turns out that structured generation could be the secret sauce you've been looking for!

Key Takeaways:

1. Structured generation consistently improves LLM performance across different models, with some seeing a whopping 70% lift!

2. Even models specifically tuned for a task can benefit from structured generation.

3. Structured generation can lead to "prompt consistency" and "thought-control," offering additional benefits beyond just performance gains.

4. Whether or not you need structured output, using structured generation is a smart move for better LLM performance.

The GSM8K Experiment

To put structured generation to the test, we ran the GSM8K test set evaluations on 8 different models. GSM8K is a collection of 1,319 grade school math word problems, and we used a standardized 8-shot prompt from the EleutherAI LM Evaluation Harness.

We compared the results of parsing unstructured output (like the LM Evaluation Harness does) with controlling the output using regex structured generation with Outlines. And boy, did we see some exciting results!

Structured Generation for the Win

Across all 8 models, structured generation led to performance improvements. In some cases, like with EleutherAI/gpt-j-6b, performance more than doubled! Even models specifically tuned for the GSM8K task, like Pearl-7B-slerp and MetaMath-Tulpar-7b-V2-slerp, saw gains.

But the benefits didn't stop there. We also found evidence of "prompt consistency" and "thought-control," two previously unexplored advantages of structured generation.

The Power of JSON Structuring

We decided to take things a step further and reformat the question, reasoning, and answer data into JSON, a common format for structured data. In the case of Mistral-7B-v0.1, using this JSON format alone (without structured generation) resulted in a 17.5% lift over the baseline unstructured prompt performance.

But here's the kicker: enforcing structure on the JSON formatted prompt provided an even further lift of 20.7% over baseline performance! It's like the cherry on top of an already delicious sundae.

Prompt Consistency and Thought-Control

Now, not all models followed the same pattern with JSON formatting. MetaMath-Tulpar-7b-v2-Slerp actually saw a significant drop in performance when the prompt was changed from the QA format to JSON.

But guess what? When using structured generation on both formats, the results were much more consistent, achieving comparable performance. This suggests that structured generation could be a way to ensure more consistent performance across different prompt formats, reducing the variance that can come with small changes in prompting.

We also stumbled upon "thought-control," which involves limiting the number of characters the model has to "think" during the reasoning stage. Early evidence suggests that increasing the lower bound may further improve performance. It's like giving the model just the right amount of space to work its magic!

The Future of Structured Generation

Our findings point towards a future where structured generation is an essential part of working with LLMs. Even if you don't need structured output for your project, using structured generation can boost your model's performance and offer additional benefits like prompt consistency and thought-control.

We're just scratching the surface of what structured generation can do, and we're excited to see where this technology takes us. So, if you want to get the most out of your LLMs, give structured generation a try!

What do you think about structured generation? Have you experimented with it in your own projects? Share your thoughts and experiences in the comments below!

And if you want to stay on the cutting edge of AI and LLM technology, sign up for the private Beta of our upcoming product. Trust us, you won't want to miss out on what the future holds!

Source: https://blog.dottxt.co/performance-gsm8k.html

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