cs.AI（2025-05-26）

📊 共 13 篇论文 | 🔗 4 篇有代码

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支柱九：具身大模型 (Embodied Foundation Models) (11 🔗4) 支柱二：RL算法与架构 (RL & Architecture) (2)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (11 篇)

#	题目	一句话要点	标签	🔗	⭐
1	On Path to Multimodal Historical Reasoning: HistBench and HistAgent	提出HistBench和HistAgent以解决历史推理中的多模态挑战	generalist agent large language model multimodal
2	ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows	提出ScienceBoard以评估多模态自主智能体在科学工作流中的应用	large language model multimodal	✅
3	Project Riley: Multimodal Multi-Agent LLM Collaboration with Emotional Reasoning and Voting	提出Project Riley以解决情感推理的多模态对话问题	large language model multimodal
4	Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution	提出Alita以解决现有智能体适应性不足的问题	generalist agent large language model	✅
5	Large Language Models as Autonomous Spacecraft Operators in Kerbal Space Program	提出基于大语言模型的自主航天器操作方案以解决卫星自主决策问题	large language model	✅
6	From Alignment to Advancement: Bootstrapping Audio-Language Alignment with Synthetic Data	提出BALSa框架以解决音频语言对齐问题	large language model instruction following
7	Ten Principles of AI Agent Economics	提出十项原则以解决AI代理经济学问题	multimodal
8	Capability-Based Scaling Laws for LLM Red-Teaming	提出能力差距框架以优化大型语言模型的红队测试	large language model
9	StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs	提出StructEval以评估大型语言模型生成结构化输出的能力	large language model
10	DCG-SQL: Enhancing In-Context Learning for Text-to-SQL with Deep Contextual Schema Link Graph	提出DCG-SQL以解决Text-to-SQL性能不足问题	large language model	✅
11	HS-STaR: Hierarchical Sampling for Self-Taught Reasoners via Difficulty Estimation and Budget Reallocation	提出HS-STaR以优化自学推理者的样本选择	large language model

🔬 支柱二：RL算法与架构 (RL & Architecture) (2 篇)

#	题目	一句话要点	标签	🔗	⭐
12	SCAR: Shapley Credit Assignment for More Efficient RLHF	提出SCAR以解决RLHF中的稀疏奖励问题	reinforcement learning RLHF large language model
13	MultiPhishGuard: An LLM-based Multi-Agent System for Phishing Email Detection	提出MultiPhishGuard以解决网络钓鱼邮件检测问题	reinforcement learning chain-of-thought

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