cs.AI（2024-11-25）

📊 共 14 篇论文 | 🔗 3 篇有代码

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支柱九：具身大模型 (Embodied Foundation Models) (10 🔗2) 支柱二：RL算法与架构 (RL & Architecture) (4 🔗1)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (10 篇)

#题目一句话要点标签🔗⭐
1 DocEDA: Automated Extraction and Design of Analog Circuits from Documents with Large Language Model DocEDA：利用大语言模型自动从文档中提取和设计模拟电路 large language model chain-of-thought
2 ASSERTIFY: Utilizing Large Language Models to Generate Assertions for Production Code ASSERTIFY：利用大型语言模型为生产代码生成断言，提升代码质量。 large language model
3 From Pretraining to Privacy: Federated Ultrasound Foundation Model with Self-Supervised Learning 提出UltraFedFM：基于联邦学习的隐私保护超声影像基础模型 foundation model
4 Enhancing Multi-Agent Consensus through Third-Party LLM Integration: Analyzing Uncertainty and Mitigating Hallucinations in Large Language Models 提出基于第三方LLM集成的多Agent共识方法，缓解LLM幻觉问题 large language model
5 Blockchain Meets LLMs: A Living Survey on Bidirectional Integration 综述性研究：探索区块链与大型语言模型双向融合的技术与应用 large language model multimodal
6 Towards Agentic Schema Refinement 提出基于多智能体LLM模拟的数据库Schema精炼方法，提升数据分析效率。 large language model
7 From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge 探索LLM作为裁判：机遇、挑战与未来方向的全面综述 large language model ✅
8 Human Motion Instruction Tuning LLaMo：保留原始运动数据的多模态人体运动指令调优框架 multimodal ✅
9 LLMPirate: LLMs for Black-box Hardware IP Piracy 提出LLMPirate以解决硬件IP盗版检测问题 large language model
10 Deciphering genomic codes using advanced NLP techniques: a scoping review 综述：利用先进NLP技术解读基因组编码，聚焦LLM与Transformer架构 large language model

🔬 支柱二：RL算法与架构 (RL & Architecture) (4 篇)

#题目一句话要点标签🔗⭐
11 CATP-LLM: Empowering Large Language Models for Cost-Aware Tool Planning 提出CATP-LLM框架，赋能大语言模型进行成本感知的工具规划。 reinforcement learning offline reinforcement learning large language model ✅
12 Why the Agent Made that Decision: Contrastive Explanation Learning for Reinforcement Learning 提出VisionMask，通过对比学习为强化学习决策提供可解释性 reinforcement learning contrastive learning
13 The brain versus AI: World-model-based versatile circuit computation underlying diverse functions in the neocortex and cerebellum 基于世界模型的通用电路计算理论，解析新皮层与小脑多样功能 world model
14 Probing for Consciousness in Machines 探索机器意识：利用强化学习训练智能体形成世界和自我模型 reinforcement learning world model

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