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Debias-SparseGPT is a bias-aware pruning method for large language models that reduces bias amplification from compression techniques like SparseGPT while maintaining model performance and efficiency.
Proposes EquiSumm, a gender bias-aware framework for inclusive tweet summarization that ensures representation of opinions from different gender groups, addressing demographic fairness in automated summarization.