## Compositional Preference Models for Aligning LMs
DONGYOUNG GO, Tomek Korbak, Germàn Kruszewski, Jos Rozen, Marc Dymetman
Keywords: 
ICLR/2024/Proceedings/17607 - Compositional Preference Models for Aligning LMs.pdf
Project URL: https://openreview.net/attachment?id=tiiAzqi6Ol&name=supplementary_material

### 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?_

[3]

Authors provide a link to their implementation in footnote 1 of the introduction (https://github.com/dongyoung-go/CPM). In the readme they state which code file is used as an entry point for what. No installation instructions. Code has few 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?_

[3]

(2/2)

HH-RLHF and SHP, both cited. For first a link is given in the paper. Descriptions are very brief.

### 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?_

[4]

HP values summarised in appendix A.2. No structured overview. No structured overview or acquisition.

### 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?_

[4]

Authors measure PM-score (not explained), data split specified in 4.2. Agg/var not given.

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

[3]

-
