Repository: microsoft/promptbench
Issue: The `prompt engineering` leaderboard is cut off in half...
Root cause: Documentation Deficiency

![image](https://github.com/microsoft/promptbench/assets/8592144/3f92b060-0cba-4119-8aa2-040312f55996)
The second leaderboard seems to be part of the first one (since it does not come with any **name** on top like the first one) but it is cut off mysteriously...
Check https://llm-eval.github.io/pages/leaderboard/pe.html

It seems the unified leaderboard looks like below:
![image](https://github.com/microsoft/promptbench/assets/8592144/6fe6e11d-b0c4-49b4-97d8-8e7a4354ee05)
However, many evaluation results are missing from the table in this case...
@madhavMathur @jindongwang @msftgits @dnfclas 


Additionally, would you consider merging the initial cells in the first row into a single cell? Currently, the segmented display somehow detracts from the overall readability and aesthetic appeal.
![image](https://github.com/microsoft/promptbench/assets/8592144/299eced8-51d1-4411-93e9-c125c6a8aa78)
I created a [PR](https://github.com/llm-eval/llm-eval.github.io/pull/4) accordingly and hope you to take a look :)
 

Thank you for your attention and advice! 
The first and second issues stem from a common cause:  different prompt engineering methods are applicable to different tasks.  
The 'Least to Most' method aims to help LLM solve complex problems through Decomposition and Subproblem solving. 
![image](https://github.com/microsoft/promptbench/assets/89716710/536df313-db46-4259-901a-f6e849ae4488)
So compared with methods in first table, 'Least to Most' is more applicable to math, symbolic tasks, rather than common sense reasoning, which led to this method using different datasets from the first table. Finally, we presented results to two tables.

> Thank you for your attention and advice! The first and second issues stem from a common cause: different prompt engineering methods are applicable to different tasks. The 'Least to Most' method aims to help LLM solve complex problems through Decomposition and Subproblem solving. ![image](https://private-user-images.githubusercontent.com/89716710/306537344-536df313-db46-4259-901a-f6e849ae4488.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.lE91XUzyG0saJw5lfzrd2JgB7Y6oBgKBGW5GD4JGT94) So compared with methods in first table, 'Least to Most' is more applicable to math, symbolic tasks, rather than common sense reasoning, which led to this method using different datasets from the first table. Finally, we presented results to two tables.

ok, that makes more sense. As I said, the current table looks split, and hope there could be a better display for demonstration purposes. Would you mind taking a look at my https://github.com/llm-eval/llm-eval.github.io/pull/4?

@zhimin-z Merged your PR