cs.CL（2024-04-05）

📊 共 14 篇论文 | 🔗 1 篇有代码

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支柱九：具身大模型 (Embodied Foundation Models) (13 🔗1) 支柱二：RL算法与架构 (RL & Architecture) (1)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (13 篇)

#题目一句话要点标签🔗⭐
1 SAAS: Solving Ability Amplification Strategy for Enhanced Mathematical Reasoning in Large Language Models 提出SAAS以增强大型语言模型的数学推理能力 large language model chain-of-thought
2 Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategies 利用大语言模型进行政治实体情感分析的零-shot与少-shot策略 large language model chain-of-thought
3 Scope Ambiguities in Large Language Models 研究大型语言模型中的范围歧义问题及其处理 large language model
4 Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model 提出CT-LLM以解决中文语言模型训练不足问题 large language model
5 Social Skill Training with Large Language Models 利用大型语言模型提升社交技能训练的可及性 large language model
6 Teaching Llama a New Language Through Cross-Lingual Knowledge Transfer 通过跨语言知识迁移提升低资源语言模型适应性 large language model instruction following
7 SEME at SemEval-2024 Task 2: Comparing Masked and Generative Language Models on Natural Language Inference for Clinical Trials 比较掩码语言模型与生成语言模型在临床试验自然语言推理中的应用 large language model chain-of-thought
8 Simple Techniques for Enhancing Sentence Embeddings in Generative Language Models 提出简化技术以增强生成语言模型的句子嵌入 large language model chain-of-thought
9 Assisting humans in complex comparisons: automated information comparison at scale 提出ASC²End以解决信息比较的可扩展性问题 large language model
10 Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction 提出EDC框架以解决知识图谱构建中的复杂模式问题 large language model ✅
11 Effects of Different Prompts on the Quality of GPT-4 Responses to Dementia Care Questions 提出创新提示模板以提升GPT-4在痴呆护理问题上的响应质量 large language model
12 GroundCocoa: A Benchmark for Evaluating Compositional & Conditional Reasoning in Language Models 提出GroundCocoa基准以评估语言模型的组合与条件推理能力 large language model
13 Assessing the quality of information extraction 提出自动化框架以评估信息提取质量 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🔗⭐
14 Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data 提出Quote-Tuning以解决语言模型可验证性问题 preference learning large language model

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