Papers by Federico Marcuzzi
How Quantization Shapes Bias in Large Language Models (2026.eacl-long)
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| Challenge: | a systematic review of quantization's effects on model biases focuses on stereotypes, fairness, toxicity, and sentiment. |
| Approach: | They focus on weight and activation quantization strategies and examine their effects across bias types including stereotypes, fairness, toxicity, and sentiment. |
| Outcome: | The proposed method can reduce stereotypes and unfairness, but it tends to increase stereotypes in generative tasks. |