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announcement

Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels

May 18, 2026Perplexity AI
Event Summary

arXiv:2605.15208v1 Announce Type: new Abstract: Large Language Models are routinely compressed via post-training quantization to reduce inference costs and memory footprint for cloud and edge deployment, yet the impact of this compression on model quality remains poorly understood. Existing studies

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Source

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