codenames-sample
Science Score: 18.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (10.2%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: tintinker
- Language: Python
- Default Branch: main
- Size: 408 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
CodenamesAI
A composite model for playing the codenames board game
Usage
- Make an account on PlaygrounRL with this referral link
- Download your
auth.jsonto the main directory - Update the line
model_name="default_model_name"inspymaster/codenames.pywith your own unique model name pip install -r requirements.txt- run
python3.11 -m gameplay.codenamesor./run10x.shfrom the main directory
Model Info / Pipeline
- Initial categories are downloaded from the semcat dataset
- Those categories are fed into a DSP few-shot learning GPT3.5 pipeline to generate 500 more categories from common themes, nouns, and adjectives in the top 1000 english words (
see category_generation/README.md) - DSP is re-applied as a RLHF model (with some manually selected gold standard categories) to check if categories are comprehensive using the top
20related Glove vectors (by cosine similarity) (see category_generation/README.md) - Decision tree and Neural Network models with uniform hyperparameter sweep are fit to predict categories from word glove embeddings (multi-label classification) (see
models/README.md,models/decisiontree.pyandmodels/neuralnet.py) - The best neural network models are selected based on test accuracy
- A Q-learning MDP is used to detirmine a scoring metric, as a function of the game state, to rank categories generated by the neural network model. Early in the game the Q table generally prefers a higher risk scoring metric; later in the game it generally prefers lower risk. (see
gameplay/README.md,data/q.json,gameplay/hint.py,gameplay/algo.py,gameplay/mdp.py)
Citations
See citations/README.md
```@article{khattab2022demonstrate, title={Demonstrate-Search-Predict: Composing Retrieval and Language Models for Knowledge-Intensive {NLP}}, author={Khattab, Omar and Santhanam, Keshav and Li, Xiang Lisa and Hall, David and Liang, Percy and Potts, Christopher and Zaharia, Matei}, journal={arXiv preprint arXiv:2212.14024}, year={2022} } @ARTICLE {SEMCAT, author = "Senel L. K., Utlu I., Yucesoy V., Koc A., Cukur T.", title = "Semantic Structure and Interpretability of Word Embeddings", year = "2018", organization = "IEEE/ACM Transactions on Audio, Speech, and Language Processing" }
Owner
- Name: Justin Tinker
- Login: tintinker
- Kind: user
- Location: Cleveland, OH
- Website: https://www.jtinker.org
- Repositories: 14
- Profile: https://github.com/tintinker
Citation (citations/citations.md)
# SEMCATdataset2018
This repository is to download the SEMCATdataset 2018 for the publication "Senel L. K., Utlu I., Yucesoy V., Koc A., Cukur T., Semantic Structure and Interpretability of Word Embeddings, IEEE/ACM Transactions on Audio, Speech, and Language Processing".
Author: Lutfi Kerem Senel
Last Update: 5.04.2018
CITATION:
If you use SEMCAT in your research, please cite (will be updated after publication):
@ARTICKLE {SEMCAT,
author = "Senel L. K., Utlu I., Yucesoy V., Koc A., Cukur T.",
title = "Semantic Structure and Interpretability of Word Embeddings",
year = "2018",
organization = "IEEE/ACM Transactions on Audio, Speech, and Language Processing"
}
Category words are in the files named "X-Y.txt" where X is the name of the category and Y is the number of the words in that category.
Justin's notes:
names of some compound categories edited
musical instrument, music theory -> music, band, harmonics,
bodies of water -> aquatic,
positive words -> positivity,
character traits -> personality
# wordlist_github.txt
https://github.com/Gullesnuffs/Codenames
# wordlist_mostcommon10k.txt
https://raw.githubusercontent.com/first20hours/google-10000-english/master/google-10000-english.txt
# wordlist_reddit.txt
https://www.reddit.com/r/boardgames/comments/9ynuxv/is_there_a_list_of_codenames_card_words/
# wordlist_mostcommon1k.txt
https://www.ef.com/wwen/english-resources/english-vocabulary/top-1000-words/
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