| 1 |
Lessons from Neuroscience for AI: How integrating Actions, Compositional Structure and Episodic Memory could enable Safe, Interpretable and Human-Like AI |
融合动作、组合结构与情景记忆,提升AI安全性、可解释性和类人能力 |
large language model foundation model chain-of-thought |
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| 2 |
Nightjar: Dynamic Adaptive Speculative Decoding for Large Language Models Serving |
Nightjar:一种动态自适应推测解码方法,提升大语言模型服务吞吐量。 |
large language model |
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| 3 |
Learning Multi-Modal Mobility Dynamics for Generalized Next Location Recommendation |
提出M³ob模型,利用多模态时空知识增强下一位置推荐的泛化能力。 |
large language model |
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| 4 |
TravelBench: A Broader Real-World Benchmark for Multi-Turn and Tool-Using Travel Planning |
提出TravelBench:一个更广泛的真实世界旅行规划多轮对话与工具使用基准 |
large language model |
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| 5 |
The Wisdom of Deliberating AI Crowds: Does Deliberation Improve LLM-Based Forecasting? |
通过群体审议提升LLM预测能力:一种基于LLM间互相审查的改进方法 |
large language model |
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| 6 |
Hierarchical Pedagogical Oversight: A Multi-Agent Adversarial Framework for Reliable AI Tutoring |
提出分层教学监督框架,利用对抗性多智能体提升AI辅导的可靠性 |
large language model |
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| 7 |
Monadic Context Engineering |
提出Monadic Context Engineering,为自主Agent设计提供形式化基础。 |
large language model |
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