Hugging Face Trending Papers June 28, 2026

The Joint Effect of Quantization and Sampling Temperature on LLM Safety Alignment: A Factorial Analysis

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Modern LLM deployments routinely compress models and raise sampling temperature to reduce cost, latency, or repetition, yet safety evaluations usually treat these choices as fixed implementation details. This leaves a practical uncertainty: does a model that is safe at FP16 and greedy decoding remain safe after it is quantized and sampled stochastically, or do the two deployment knobs amplify one another?

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