cs.CL（2024-01-27）

📊 共 13 篇论文 | 🔗 2 篇有代码

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支柱九：具身大模型 (Embodied Foundation Models) (9 🔗1) 支柱二：RL算法与架构 (RL & Architecture) (3 🔗1) 支柱一：机器人控制 (Robot Control) (1)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (9 篇)

#题目一句话要点标签🔗⭐
1 Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately 通过精调提升大语言模型在问答和信息提取中的表现 large language model
2 Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models 提出Self-BioRAG以解决生物医学推理问题 large language model foundation model
3 Hardware Phi-1.5B: A Large Language Model Encodes Hardware Domain Specific Knowledge 提出Hardware Phi-1.5B以解决半导体硬件领域知识不足问题 large language model
4 An Empirical Study on Large Language Models in Accuracy and Robustness under Chinese Industrial Scenarios 研究大型语言模型在中国工业场景下的准确性与鲁棒性 large language model
5 Baichuan2-Sum: Instruction Finetune Baichuan2-7B Model for Dialogue Summarization 提出Baichuan2-Sum以解决对话摘要生成问题 large language model
6 AI Does Not Alter Perceptions of Text Messages 探讨AI辅助文本消息对感知的影响 large language model
7 Do We Need Language-Specific Fact-Checking Models? The Case of Chinese 提出中文特定的事实核查模型以解决翻译方法的局限性 large language model
8 To Burst or Not to Burst: Generating and Quantifying Improbable Text 提出恢复性度量与突发采样以提升文本生成质量 large language model
9 MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries 提出MultiHop-RAG以解决多跳查询的检索增强生成问题 large language model ✅

🔬 支柱二：RL算法与架构 (RL & Architecture) (3 篇)

#题目一句话要点标签🔗⭐
10 A Comprehensive Survey of Compression Algorithms for Language Models 综述语言模型压缩算法以提升效率与准确性 distillation large language model
11 Learning to Trust Your Feelings: Leveraging Self-awareness in LLMs for Hallucination Mitigation 提出RLKF框架以减轻大型语言模型的事实幻觉问题 reinforcement learning large language model
12 LegalDuet: Learning Fine-grained Representations for Legal Judgment Prediction via a Dual-View Contrastive Learning 提出LegalDuet以解决法律判决预测中的细微差异识别问题 contrastive learning ✅

🔬 支柱一：机器人控制 (Robot Control) (1 篇)

#题目一句话要点标签🔗⭐
13 Fortifying Ethical Boundaries in AI: Advanced Strategies for Enhancing Security in Large Language Models 提出多重策略以增强大型语言模型的安全性和伦理边界 manipulation large language model

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