Toxic Comment Classification

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

7 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

13 shown of 13 papers with code (28 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• NLPGuard: A Framework for Mitigating the Use of Protected Attributes by NLP Classifiers
  1 Jul 2024 1 repository listed
  AI regulations are expected to prohibit machine learning models from using sensitive attributes during training.
• PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning
  31 Mar 2024 1 repository listed Syntology ran 2 of 2 samples · 0 unverified
  We present PyTorch Frame, a PyTorch-based framework for deep learning over multi-modal tabular data.
• Evaluating The Effectiveness of Capsule Neural Network in Toxic Comment Classification using Pre-trained BERT Embeddings
  12 Oct 2023 1 repository listed
  By comparing the performance of CapsNet to that of other architectures, such as DistilBERT, Vanilla Neural Networks (VNN), and Convolutional Neural Networks (CNN), we were able to achieve an accuracy of 90.
• CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
  19 May 2023 1 repository listed Syntology ran 4 of 5 samples · 1 unverified
  Unlike these models, humans typically utilize external tools to cross-check and refine their initial content, like using a search engine for fact-checking, or a code interpreter for debugging.
• A benchmark for toxic comment classification on Civil Comments dataset
  26 Jan 2023 1 repository listed
  BiLSTM remains a good compromise between performance and inference time.
• FHAC at GermEval 2021: Identifying German toxic, engaging, and fact-claiming comments with ensemble learning
  7 Sep 2021 1 repository listed
  The availability of language representations learned by large pretrained neural network models (such as BERT and ELECTRA) has led to improvements in many downstream Natural Language Processing tasks in recent years.
• Data Integration for Toxic Comment Classification: Making More Than 40 Datasets Easily Accessible in One Unified Format
  1 Aug 2021 1 repository listed
  With the rise of research on toxic comment classification, more and more annotated datasets have been released.
• From Hero to Z\'eroe: A Benchmark of Low-Level Adversarial Attacks
  1 Dec 2020 1 repository listed
  Adversarial attacks are label-preserving modifications to inputs of machine learning classifiers designed to fool machines but not humans.
• From Hero to Zéroe: A Benchmark of Low-Level Adversarial Attacks
  12 Oct 2020 1 repository listed Syntology ran 2 of 3 samples · 1 unverified
  Adversarial attacks are label-preserving modifications to inputs of machine learning classifiers designed to fool machines but not humans.
• Trojaning Language Models for Fun and Profit
  1 Aug 2020 1 repository listed
  Recent years have witnessed the emergence of a new paradigm of building natural language processing (NLP) systems: general-purpose, pre-trained language models (LMs) are composed with simple downstream models and…
• Can We Achieve More with Less? Exploring Data Augmentation for Toxic Comment Classification
  2 Jul 2020 1 repository listed
  This paper tackles one of the greatest limitations in Machine Learning: Data Scarcity.
• Is preprocessing of text really worth your time for online comment classification?
  7 Jun 2018 1 repository listed
  A large proportion of online comments present on public domains are constructive, however a significant proportion are toxic in nature.
• Convolutional Neural Networks for Toxic Comment Classification
  27 Feb 2018 1 repository listed
  To justify this decision we choose to compare CNNs against the traditional bag-of-words approach for text analysis combined with a selection of algorithms proven to be very effective in text classification.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.