title: ToVo: Toxicity Taxonomy via Voting
summary: Existing toxic detection models face significant limitations, such as lack of
  transparency, customization, and reproducibility. These challenges stem from
  the closed-source nature of their training data and the paucity of explanations
  for their evaluation mechanism. To address these issues, we propose a dataset
  creation mechanism that integrates voting and chain-of-thought processes,
  producing a high-quality open-source dataset for toxic content detection. Our
  methodology ensures diverse classification metrics for each sample and includes
  both classification scores and explanatory reasoning for the classifications.
    We utilize the dataset created through our proposed mechanism to train our
  model, which is then compared against existing widely-used detectors. Our
  approach not only enhances transparency and customizability but also
  facilitates better fine-tuning for specific use cases. This work contributes a
  robust framework for developing toxic content detection models, emphasizing
  openness and adaptability, thus paving the way for more effective and
  user-specific content moderation solutions.
paper_authors._id: 6678dab38a4064c02b75754d
paper_authors.name: Tinh Son Luong
paper_authors.status: extracted_pending
paper_authors.statusLastChangedAt: 2024-06-24T02:32:21.317Z
paper_authors._id: 619550cb4f08530be9bec2cf
paper_authors.avatarUrl: /avatars/d1df21b0ff7cfa098d6a0c5375e2c194.svg
paper_authors.fullname: Luong Son Tinh
paper_authors.type: user
paper_authors.user: convoicon
paper_authors._id: 6678dab38a4064c02b75754e
paper_authors.name: Thanh-Thien Le
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-06-24T14:25:17.287Z
paper_authors._id: 646540145cdb9ab50f85ede3
paper_authors.avatarUrl: /avatars/22f077f8ccec9785b8315836dffe1f2a.svg
paper_authors.fullname: Thanh-Thien Le
paper_authors.type: user
paper_authors.user: LeCielBleu
paper_authors._id: 6678dab38a4064c02b75754f
paper_authors.name: Thang Viet Doan
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-06-24T14:25:23.048Z
paper_authors._id: 66614a081761e2aff7bf673c
paper_authors.avatarUrl: /avatars/30f923af89da3656d88c0f6ef185374c.svg
paper_authors.fullname: Thang Viet Doan
paper_authors.type: user
paper_authors.user: babynotta
paper_authors._id: 6678dab38a4064c02b757550
paper_authors.name: Linh Ngo Van
paper_authors._id: 6678dab38a4064c02b757551
paper_authors.name: Thien Huu Nguyen
paper_authors._id: 6678dab38a4064c02b757552
paper_authors.name: Diep Thi-Ngoc Nguyen
paper_title: ToVo: Toxicity Taxonomy via Voting
paper_summary: Existing toxic detection models face significant limitations, such as lack of
  transparency, customization, and reproducibility. These challenges stem from
  the closed-source nature of their training data and the paucity of explanations
  for their evaluation mechanism. To address these issues, we propose a dataset
  creation mechanism that integrates voting and chain-of-thought processes,
  producing a high-quality open-source dataset for toxic content detection. Our
  methodology ensures diverse classification metrics for each sample and includes
  both classification scores and explanatory reasoning for the classifications.
    We utilize the dataset created through our proposed mechanism to train our
  model, which is then compared against existing widely-used detectors. Our
  approach not only enhances transparency and customizability but also
  facilitates better fine-tuning for specific use cases. This work contributes a
  robust framework for developing toxic content detection models, emphasizing
  openness and adaptability, thus paving the way for more effective and
  user-specific content moderation solutions.
paper_ai_summary: A framework for creating an open-source dataset with detailed explanations is proposed to improve transparency and customizability in toxic content detection models.
paper_ai_keywords: voting chain-of-thought open-source dataset classification metrics explanatory reasoning fine-tuning