## MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following
Renze Lou, Kai Zhang, Jian Xie, Yuxuan Sun, Jihyun Ahn, Hanzi XU, Yu Su, Wenpeng Yin
Keywords: 
ICLR/2024/Proceedings/19563 - MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following.pdf
Project URL: nan

### Implementation
_Given the documentation shared by the authors on a new method, how much effort would it be to re-implement the method from scratch?_

[2]

Authors provide a project page in footnote 1 of the abstract where a link to the implementation can be found (https://github.com/RenzeLou/Muffin). Readme has an overview of the method, file/directory structure index, link to the dataset, model zoo with links, how to install, how to run the code with a few examples. Code could use more comments.

### Data
_Given the data description in the documentation, how much effort would it take to either: Find the same data set the authors used, or a similar data set and defend the comparability, or acquire one from scratch?_

[1]

(1/1)

The authors create a new dataset called MUFFIN, which is detailed in the paper and published (link in repo).

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for obtaining the reported results, and compare them against their computation budget?_

[1]

Authors benchmark SOTA on their dataset. Not applicable.

### Experimental Procedure
_Given the setup of experiments reported in the work, how difficult is it to set up a new experiment with the same procedure, similar to those presented in the original work?_

[1]

Authors measure Exact Match, Rouge, Rank Accuracy. Results are averaged across three runs. 

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying solely on the available documentation?_

[3]

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