| 1 |
AI Meets the Classroom: When Do Large Language Models Harm Learning? |
研究揭示LLM在教育中的双刃剑效应:过度替代学习活动或损害理解 |
large language model |
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| 2 |
Examination of Code generated by Large Language Models |
评估大型语言模型生成的代码质量与正确性,揭示不同模型、语言和时间的影响。 |
large language model |
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| 3 |
Acceptable Use Policies for Foundation Models |
分析大型模型可接受使用政策,揭示其对AI生态的影响与挑战 |
foundation model |
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| 4 |
HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications |
HyPA-RAG:面向AI法律与政策应用的混合参数自适应检索增强生成系统 |
large language model |
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| 5 |
Emerging Vulnerabilities in Frontier Models: Multi-Turn Jailbreak Attacks |
揭示前沿模型多轮越狱攻击漏洞,提出新型数据集用于评估防御能力 |
large language model |
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| 6 |
United in Diversity? Contextual Biases in LLM-Based Predictions of the 2024 European Parliament Elections |
评估LLM预测欧洲议会选举的背景偏差,揭示其在公共舆论预测中的局限性 |
large language model |
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