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The game's difficulty comes from the anticipation and matching of the card played by a player to the criterion of the current round judge. Our aim was to create an agent capable of playing \"Apples to Apples,\" able to discover the current judge criterion and play the card in hand that best matches that criterion. To this end, we decided to explore the use of BERT pretrained models and evaluate their viability in word game agents. In this study, we leveraged fine tuned BERT models and developed a Naive Bayes classifier to simulate and predict judge personalities in \"Apples to Apples.\" Beyond these main contributions, this work also involved significant efforts in creating supporting tools for both training and testing processes. Specifically, we manually annotated nearly 1000 card pairs using a custom annotation program to reduce human error and fatigue and developed an environment testing tool to ensure platform consistency during training and testing. These contributions highlight our focus on both data quality and system robustness.<\/jats:p>","DOI":"10.1145\/3774399.3774404","type":"journal-article","created":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T16:45:18Z","timestamp":1764780318000},"page":"18-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Adapting BERT for 'Apples to Apples' Gameplay"],"prefix":"10.1145","volume":"11","author":[{"given":"Arikka","family":"Cherniwchan","sequence":"first","affiliation":[{"name":"MacEwan University"}]},{"given":"Austin","family":"Countaway","sequence":"additional","affiliation":[{"name":"MacEwan University"}]},{"given":"Chunyang","family":"Ding","sequence":"additional","affiliation":[{"name":"MacEwan University"}]},{"given":"Brandon","family":"Funk","sequence":"additional","affiliation":[{"name":"MacEwan University"}]},{"given":"Calin","family":"Anton","sequence":"additional","affiliation":[{"name":"MacEwan University"}]}],"member":"320","published-online":{"date-parts":[[2025,12,3]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2018-2263"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.conll-1.30"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.236"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.148"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-809633-8.20473-1"},{"key":"e_1_2_1_6_1","volume-title":"Proceedings of the 18th joint acl - iso workshop on interoperable semantic annotation within lrec2022 (pp. 42\u201352)","author":"Delmonte R.","year":"2022","unstructured":"Delmonte, R., & Busetto, N. (2022, June). Measuring similarity by linguistic features rather than frequency. In H. Bunt (Ed.), Proceedings of the 18th joint acl - iso workshop on interoperable semantic annotation within lrec2022 (pp. 42\u201352). Marseille, France: European Language Resources Association. Retrieved from https:\/\/aclanthology.org\/2022.isa-1.6\/"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1423"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.47852\/bonviewJCCE3202838"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijresmar.2022.05.005"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.paid.2018.12.008"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","unstructured":"Isaak N. (2022 06). A zero-shot classification approach for a word-guessing challenge. 10.48550\/arXiv.2206.13099","DOI":"10.48550\/arXiv.2206.13099"},{"key":"e_1_2_1_12_1","unstructured":"Koroteev M. (2021 03). 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Potthast (Eds.), Proceedings of the working notes of CLEF 2022 - conference and labs of the evaluation forum, bologna, italy, september 5th - to - 8th, 2022 (Vol. 3180, pp. 1828\u20131833). CEUR-WS.org. Retrieved from https:\/\/ceur-ws.org\/Vol-3180\/paper-142.pdf"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.3390\/info14040242"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05102-3"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICODSE.2015.7436992"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"e_1_2_1_22_1","volume-title":"Bert: A review of applications in sentiment analysis. HighTech and Innovation Journal.","author":"Sayeed M. S.","year":"2023","unstructured":"Sayeed, M. S., Mohan, V., & Muthu, K. S. (2023). Bert: A review of applications in sentiment analysis. HighTech and Innovation Journal. 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