From BERT to Qwen: Hate Detection across architectures
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911054811889664 |
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| author | Mon, Ariadna Fenollosa, Saúl Lecumberri, Jon |
| author_facet | Mon, Ariadna Fenollosa, Saúl Lecumberri, Jon |
| contents | Online platforms struggle to curb hate speech without over-censoring legitimate discourse. Early bidirectional transformer encoders made big strides, but the arrival of ultra-large autoregressive LLMs promises deeper context-awareness. Whether this extra scale actually improves practical hate-speech detection on real-world text remains unverified. Our study puts this question to the test by benchmarking both model families, classic encoders and next-generation LLMs, on curated corpora of online interactions for hate-speech detection (Hate or No Hate). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_10468 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From BERT to Qwen: Hate Detection across architectures Mon, Ariadna Fenollosa, Saúl Lecumberri, Jon Computation and Language Machine Learning Online platforms struggle to curb hate speech without over-censoring legitimate discourse. Early bidirectional transformer encoders made big strides, but the arrival of ultra-large autoregressive LLMs promises deeper context-awareness. Whether this extra scale actually improves practical hate-speech detection on real-world text remains unverified. Our study puts this question to the test by benchmarking both model families, classic encoders and next-generation LLMs, on curated corpora of online interactions for hate-speech detection (Hate or No Hate). |
| title | From BERT to Qwen: Hate Detection across architectures |
| topic | Computation and Language Machine Learning |
| url | https://arxiv.org/abs/2507.10468 |