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From Representational Harms to Quality-of-Service Harms: A Case Study on Llama 2 Safety Safeguards
Despite growing mitigation efforts to develop safety safeguards, such as supervised safety-oriented fine-tuning and leveraging safe reinforcement learning from human feedback, multiple concerns regarding the safety and ingrained biases in these models remain.
Unsupervised Layer-wise Score Aggregation for Textual OOD Detection
More importantly, we show that the usual choice (the last layer) is rarely the best one for OOD detection and that far better results could be achieved if the best layer were picked.
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