Papers with content composition

1 papers
Toxicity Red-Teaming: Benchmarking LLM Safety in Singapore’s Low-Resource Languages (2025.emnlp-main)

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Challenge: Large language models (LLMs) have transformed natural language processing, but their safety mechanisms remain under-explored in low-resource, multilingual settings.
Approach: They propose a red-teaming approach to probe LLM vulnerabilities in Singapore's diverse linguistic context using a dataset and evaluation framework.
Outcome: The proposed framework systematically probes LLM vulnerabilities in three real-world scenarios including Singlish, Chinese, Malay, and Tamil.

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