MBIAS: Mitigating Bias in Large Language Models While Retaining Context

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Red teaming language models with language models

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“I’m sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor Dataset

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A robust bias mitigation procedure based on the stereotype content model

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Making llms even more accessible with bitsandbytes, 4-bit quantization and qlora

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Safety-tuned llamas: Lessons from improving the safety of large language models that follow instructions

Llama 2: Open foundation and fine-tuned chat models

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The dark side of generative artificial intelligence: A critical analysis of controversies and risks of chatgpt

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Aligning large language models with human: A survey

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Adept: A debiasing prompt framework

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LLMaAA: Making large language models as active annotators

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