A LoRA fine-tuned Qwen2.5 system with majority voting and multi-temperature sampling detects, classifies, and mitigates Chinese gender bias, ranking fourth in NLPCC-2025 Task 7 with an average score of 47.90%.
Advances in neural information processing systems29(2016)
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From Detection to Mitigation: Addressing Gender Bias in Chinese Texts via Efficient Tuning and Voting-Based Rebalancing
A LoRA fine-tuned Qwen2.5 system with majority voting and multi-temperature sampling detects, classifies, and mitigates Chinese gender bias, ranking fourth in NLPCC-2025 Task 7 with an average score of 47.90%.