Papers by Muhammad Alif Al Hakim

1 papers
Preserving Fairness and Safety in Quantized LLMs Through Critical Weight Protection (2026.findings-acl)

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Challenge: Existing quantization methods focus on general metrics like perplexity or accuracy on standard benchmarks.
Approach: They propose a method that preserves fairness- and safety-critical weights during quantization.
Outcome: The proposed method reduces bias and safety degradation without costly retraining or alignment while maintaining trustworthiness while retaining efficiency.

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