swainsubhankar/ToxicTags

195 downloads in 30 days6 likesLast modified 29 Sep 2026View on Hugging Face

The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at b8a4744
Licence files: No licence file at the top level of the repositoryEvidence: file list at b8a4744
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Citation text from the card

@article{10.1162/TACL.a.801,
    author = {Swain, Subhankar and Rizwan, Naquee and Gangadhar S, Vishwa and Deb, Nayandeep and Mukherjee, Animesh},
    title = {STEMTOX: From Collaborative Tags to Fine-Grained Toxic Meme Detection via Entropy-Guided Multi-Task Learning},
    journal = {Transactions of the Association for Computational Linguistics},
    volume = {14},
    pages = {2281-2300},
    year = {2026},
    month = {08},
    abstract = {Memes, as a widely used mode of online communication, often serve as vehicles for spreading harmful content. However, limitations in data accessibility and the high costs of dataset curation hinder the development of robust meme moderation systems. To address this challenge, in this work, we introduce a first-of-its-kind dataset – TOXICTAGS consisting of 6,300 real-world meme-based posts annotated in two stages: (i) binary classification into toxic and normal, and (ii) fine-grained labelling of toxic memes as hateful, dangerous, or offensive. A key feature of this dataset is that it includes collaborative tags associated with the original posts, enhancing the context of each meme. In addition, we propose a novel entropy-guided multi-tasking framework – STEMTOX – that leverages these collaborative tags alongside visual and textual inputs within a robust classification framework. Experimental results show that incorporating these tags substantially enhances the performance of state-of-the-art VLMs in toxicity detection tasks. Our contribut

All datasets marked Permissive or share-alike | JSON

The same facts for your agent

A free MCP server at mcp.datalicense.uk/mcp. Connect it from an MCP client such as Claude or Cursor.

dataset_licence({ "id": "swainsubhankar/ToxicTags" })
signal: "permissive"
stated_licence: "mit"
sources: 0