Datasets:
				
			
			
	
			
	
		
			
	
		| Question
				 stringlengths 2 3 | Design
				 stringclasses 4
				values | Criterion
				 stringclasses 4
				values | 
|---|---|---|
| 
	Q1 | 
	Kitchen Utensil Grip | 
	Lightweight | 
| 
	Q2 | 
	Kitchen Utensil Grip | 
	Resistant to Heat | 
| 
	Q3 | 
	Kitchen Utensil Grip | 
	Corrosion Resistant | 
| 
	Q4 | 
	Kitchen Utensil Grip | 
	High Strength | 
| 
	Q5 | 
	Spacecraft Component | 
	Lightweight | 
| 
	Q6 | 
	Spacecraft Component | 
	Resistant to Heat | 
| 
	Q7 | 
	Spacecraft Component | 
	Corrosion Resistant | 
| 
	Q8 | 
	Spacecraft Component | 
	High Strength | 
| 
	Q9 | 
	Underwater Component | 
	Lightweight | 
| 
	Q10 | 
	Underwater Component | 
	Resistant to Heat | 
| 
	Q11 | 
	Underwater Component | 
	Corrosion Resistant | 
| 
	Q12 | 
	Underwater Component | 
	High Strength | 
| 
	Q13 | 
	Safety Helmet | 
	Lightweight | 
| 
	Q14 | 
	Safety Helmet | 
	Resistant to Heat | 
| 
	Q15 | 
	Safety Helmet | 
	Corrosion Resistant | 
| 
	Q16 | 
	Safety Helmet | 
	High Strength | 
MSEval Dataset:
A benchmark designed to facilitate evaluation and modify the behavior of a foundation model through different existing techniques in the context of material selection for conceptual design.
The data is collected by conducting a survey of experts in the field of material selection. The same questions mentioned in keyquestions.csv are asked to experts.
This can be used to evaluate a Language model performance and its spread compared to a human evaluation.
To get into a more detailed explanation - use this link [https://arxiv.org/abs/2407.09719v1]
Overview
We introduce MSEval, a benchmark derived from survey results of experts in the field of material selection.
The MixEval consists of two files: CleanResponses and AllResponses. Below presents the dataset file tree:
 MSEval
    │
    ├── AllResponses.csv
    └── CleanResponses.csv
    └── KeyQuestions.csv
Dataset Usage
An example use of the dataset using the datasets library is shown in https://github.com/cmudrc/MSEval
To use this dataset using pandas:
import pandas as pd
df = pd.read_csv("hf://datasets/cmudrc/Material_Selection_Eval/AllResponses.csv")
Replace AllResponses with CleanResponses and KeyQuestions in the pathname if required.
Citation
If you found the dataset useful, please cite:
@misc{jain2024msevaldatasetmaterialselection,
      title={MSEval: A Dataset for Material Selection in Conceptual Design to Evaluate Algorithmic Models}, 
      author={Yash Patawari Jain and Daniele Grandi and Allin Groom and Brandon Cramer and Christopher McComb},
      year={2024},
      eprint={2407.09719},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2407.09719}, 
}
license: mit
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