| 1 |
MH-1M: A 1.34 Million-Sample Comprehensive Multi-Feature Android Malware Dataset for Machine Learning, Deep Learning, Large Language Models, and Threat Intelligence Research |
提出MH-1M：一个包含134万样本的综合性Android恶意软件多特征数据集，用于机器学习等研究。 |
large language model |
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| 2 |
Diverse Human Value Alignment for Large Language Models via Ethical Reasoning |
提出基于伦理推理的框架，提升大语言模型对多元人类价值观的对齐 |
large language model |
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| 3 |
Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs |
研究参数高效微调对LLM安全性与公平性的影响，揭示效率与对齐的权衡。 |
large language model |
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| 4 |
Better Call CLAUSE: A Discrepancy Benchmark for Auditing LLMs Legal Reasoning Capabilities |
CLAUSE：用于审计LLM法律推理能力的差异性基准测试 |
large language model |
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