
## Graphmax for Text Generation
Bin Liu, Guosheng Yin
Keywords: 
JAIR/2023/Proceedings/15280 - Graphmax for Text Generation.pdf
Project URL: 

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[9]

The authors state in section 5 they use PyTorch 7.1. No other details.

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

[4]

(4/4)

The authors use the Amazon, Yelp, WMT'16 and WMT'21 datasets. Citations are provided. No other details.

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

[3]

The authors define the parameter values of algorithm 1 in section 5. No acquisition given. Since its very few parameter (values), the in text definition is acceptable.

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

[2]

The authors state evaluation metrics in section 5 with a description. The results are averaged over 100 independent runs. The authors also collected data from humans, link the questionairre website used for collection and state the number of participants and present the averaged results in table 9 with standard deviation. The exact questionaire is not given.

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

[6]

Requires expertise on text generation and graphmax.
