cs.CL（2024-08-24）

📊 共 8 篇论文 | 🔗 3 篇有代码

🎯 兴趣领域导航

支柱九：具身大模型 (Embodied Foundation Models) (7 🔗3) 支柱二：RL算法与架构 (RL & Architecture) (1)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (7 篇)

#	题目	一句话要点	标签	🔗	⭐
1	GNN: Graph Neural Network and Large Language Model for Data Discovery	提出GNN模型，利用图神经网络和大型语言模型进行数据发现，扩展文本类型数据的理解能力。	large language model
2	Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models	提出NoiserBench，揭示RAG中噪声对大语言模型的影响，发现有益噪声。	large language model	✅
3	Utilizing Large Language Models for Named Entity Recognition in Traditional Chinese Medicine against COVID-19 Literature: Comparative Study	对比研究大型语言模型在COVID-19相关中医文献命名实体识别中的应用	large language model
4	Balancing Diversity and Risk in LLM Sampling: How to Select Your Method and Parameter for Open-Ended Text Generation	提出基于前缀树的LLM采样方法评估框架，平衡多样性与风险	large language model
5	Make Every Penny Count: Difficulty-Adaptive Self-Consistency for Cost-Efficient Reasoning	提出难度自适应自洽性推理(DSC)，提升成本效益并保持性能	chain-of-thought
6	Symbolic Working Memory Enhances Language Models for Complex Rule Application	提出神经符号框架，增强LLM在复杂规则应用中的推理能力	large language model	✅
7	HRGraph: Leveraging LLMs for HR Data Knowledge Graphs with Information Propagation-based Job Recommendation	HRGraph：利用LLM构建HR数据知识图谱，实现基于信息传播的职位推荐	large language model	✅

🔬 支柱二：RL算法与架构 (RL & Architecture) (1 篇)

#	题目	一句话要点	标签	🔗	⭐
8	Selective Preference Optimization via Token-Level Reward Function Estimation	提出SePO，通过token级奖励函数估计实现高效选择性偏好优化。	DPO direct preference optimization large language model

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