| 1 |
Automated Optimization Modeling through Expert-Guided Large Language Model Reasoning |
提出ORThought框架以自动化优化建模过程 |
large language model chain-of-thought |
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| 2 |
Building and Measuring Trust between Large Language Models |
提出信任构建与测量方法以解决LLMs间信任关系问题 |
large language model |
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| 3 |
PerFairX: Is There a Balance Between Fairness and Personality in Large Language Model Recommendations? |
提出PerFairX以解决大语言模型推荐中的公平性与个性化问题 |
large language model |
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| 4 |
NoteIt: A System Converting Instructional Videos to Interactable Notes Through Multimodal Video Understanding |
提出NoteIt系统以解决教学视频笔记生成不足的问题 |
multimodal |
✅ |
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| 5 |
MoEcho: Exploiting Side-Channel Attacks to Compromise User Privacy in Mixture-of-Experts LLMs |
提出MoEcho以解决Mixture-of-Experts模型中的用户隐私问题 |
large language model multimodal |
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| 6 |
Open-Universe Assistance Games |
提出开放宇宙辅助游戏框架以解决人类目标推断问题 |
embodied AI |
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| 7 |
Emergent Crowds Dynamics from Language-Driven Multi-Agent Interactions |
提出语言驱动的多智能体交互方法以解决人群动态模拟问题 |
large language model |
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| 8 |
ECHO: Frequency-aware Hierarchical Encoding for Variable-length Signals |
提出ECHO模型以解决变长信号建模问题 |
foundation model |
✅ |
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| 9 |
aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists |
提出aiXiv以解决AI生成研究内容发布难题 |
large language model |
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| 10 |
S3LoRA: Safe Spectral Sharpness-Guided Pruning in Adaptation of Agent Planner |
提出S3LoRA以解决LLM适应过程中的安全性问题 |
large language model |
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| 11 |
Enabling Multi-Agent Systems as Learning Designers: Applying Learning Sciences to AI Instructional Design |
将知识学习框架嵌入多智能体系统以提升教育内容设计质量 |
large language model |
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| 12 |
Who Sees What? Structured Thought-Action Sequences for Epistemic Reasoning in LLMs |
提出结构化思维-行动序列以提升LLM的视角理解能力 |
large language model |
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