ToxBuster: In-game Chat Toxicity Buster with BERT
Not on the map. Why?
Abstract (arXiv)
Detecting toxicity in online spaces is challenging and an ever more pressing problem given the increase in social media and gaming consumption. We introduce ToxBuster, a simple and scalable model trained on a relatively large dataset of 194k lines of game chat from Rainbow Six Siege and For Honor, carefully annotated for different kinds of toxicity. Compared to the existing state-of-the-art, ToxBuster achieves 82.95% (+7) in precision and 83.56% (+57) in recall. This improvement is obtained by leveraging past chat history and metadata. We also study the implication towards real-time and post-game moderation as well as the model transferability from one game to another.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 13 of its 32 references that are in the map. First posted on arXiv 21 May 2023.
Builds on
13 of 32 references.
References · 13
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 956
- 2019On Measuring Social Biases in Sentence Encoderscited by 398
- 2018Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systemscited by 234
- 2022A New Generation of Perspective API: Efficient Multilingual Character-level Transformerscited by 185
- 2021An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language Modelscited by 97
- 2020Toxicity Detection: Does Context Really Matter?cited by 93
- 2017Detecting Online Hate Speech Using Context Aware Modelscited by 72
- 2018Challenges for Toxic Comment Classification: An In-Depth Error Analysiscited by 56
- 2017One-step and Two-step Classification for Abusive Language Detection on Twittercited by 46
- 2018Convolutional Neural Networks for Toxic Comment Classificationcited by 24
- 2020Measuring and Characterizing Hate Speech on News Websitescited by 12
1 more
Built on by
Citing papers per year: 2023: 1; 2024: 0; 2025: 3; 2026: 1.
5 papers.
- 2023Model Breadcrumbs: Scaling Multi-Task Model Merging with Sparse Maskscited by 133
- 2025Stabilizing Black-Box Prompt Optimization with Textual Regularization and Signal Aggregationcited by 2
- 2025Prosocial Behavior Detection in Player Game Chat: From Aligning Human-AI Definitions to Efficient Annotation at Scalecited by 1
- 2025How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Modelscited by 0
- 2026Language-Specific Gaps in AI Safety Training Datasetscited by 0
- 2026Language-Specific Gaps in AI Safety Training Datasets13 Aug 2026
- 2025How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Models10 Nov 2025
- 2025Prosocial Behavior Detection in Player Game Chat: From Aligning Human-AI Definitions to Efficient Annotation at Scale8 Aug 2025
- 2025Stabilizing Black-Box Prompt Optimization with Textual Regularization and Signal Aggregation14 Jul 2025
- 2023Model Breadcrumbs: Scaling Multi-Task Model Merging with Sparse Masks11 Dec 2023