cs.CL（2024-03-15）

📊 共 16 篇论文 | 🔗 1 篇有代码

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支柱九：具身大模型 (Embodied Foundation Models) (14 🔗1) 支柱二：RL算法与架构 (RL & Architecture) (2)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (14 篇)

#题目一句话要点标签🔗⭐
1 Uni-SMART: Universal Science Multimodal Analysis and Research Transformer 提出Uni-SMART以解决科学文献多模态分析问题 large language model multimodal
2 EXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models 提出EXAMS-V基准以评估多模态视觉语言模型的能力 multimodal
3 A Question on the Explainability of Large Language Models and the Word-Level Univariate First-Order Plausibility Assumption 提出统计方法以评估大语言模型的可解释性问题 large language model
4 Whose Side Are You On? Investigating the Political Stance of Large Language Models 提出定量框架以调查大型语言模型的政治立场 large language model
5 Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models 提出多语言任务评估新方法以提升大语言模型性能 large language model
6 DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models 提出DRAGIN以解决动态检索增强生成中的信息需求问题 large language model ✅
7 Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection 提出自我检测框架以解决大型语言模型输出可信度问题 large language model
8 RAFT: Adapting Language Model to Domain Specific RAG 提出RAFT以解决领域特定知识更新问题 large language model chain-of-thought
9 Don't Half-listen: Capturing Key-part Information in Continual Instruction Tuning 提出基于关键部分信息增益的持续指令调优方法以解决遗忘问题 large language model instruction following
10 Discovering Latent Themes in Social Media Messaging: A Machine-in-the-Loop Approach Integrating LLMs 提出机器环路方法以发现社交媒体中的潜在主题 large language model
11 Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases 提出基于RAG的系统以提升LLM在特定领域查询的准确性 large language model
12 NLP Verification: Towards a General Methodology for Certifying Robustness 提出通用方法以解决NLP验证中的嵌入差距问题 large language model
13 ChatPattern: Layout Pattern Customization via Natural Language 提出ChatPattern以解决自由尺寸布局模式生成问题 large language model
14 Lost in Overlap: Exploring Logit-based Watermark Collision in LLMs 提出水印碰撞概念以解决LLM文本版权问题 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🔗⭐
15 TriSum: Learning Summarization Ability from Large Language Models with Structured Rationale 提出TriSum框架以解决大语言模型在文本摘要中的应用限制 curriculum learning large language model
16 EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning 提出EXPLORER以解决文本强化学习中的泛化问题 reinforcement learning

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