cs.AI（2024-02-13）

📊 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) (11 🔗1) 支柱二：RL算法与架构 (RL & Architecture) (3)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (11 篇)

#题目一句话要点标签🔗⭐
1 VerMCTS: Synthesizing Multi-Step Programs using a Verifier, a Large Language Model, and Tree Search 提出VerMCTS以解决大语言模型生成代码可信性问题 large language model ✅
2 Combining Insights From Multiple Large Language Models Improves Diagnostic Accuracy 通过结合多种大型语言模型提升诊断准确性 large language model
3 Rec-GPT4V: Multimodal Recommendation with Large Vision-Language Models 提出Rec-GPT4V以解决多模态推荐中的用户偏好问题 multimodal
4 The Last JITAI? Exploring Large Language Models for Issuing Just-in-Time Adaptive Interventions: Fostering Physical Activity in a Conceptual Cardiac Rehabilitation Setting 利用大型语言模型提升数字健康中的即时适应干预效果 large language model
5 Large Language Models for the Automated Analysis of Optimization Algorithms 将大型语言模型应用于优化算法的自动分析 large language model
6 On Limitations of the Transformer Architecture 揭示Transformer架构在大型语言模型中的局限性 large language model
7 GhostWriter: Augmenting Collaborative Human-AI Writing Experiences Through Personalization and Agency 提出GhostWriter以解决个性化与控制不足的问题 large language model
8 LLMs and Stack Overflow Discussions: Reliability, Impact, and Challenges 分析LLMs在Stack Overflow中的可靠性与挑战 large language model
9 Tandem Transformers for Inference Efficient LLMs 提出串联变换器以解决大语言模型推理效率问题 large language model
10 Artificial Intelligence for Literature Reviews: Opportunities and Challenges 提出人工智能辅助文献综述以提升研究效率 large language model
11 LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents 提出LoTa-Bench以解决语言导向任务规划的评估问题 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🔗⭐
12 LLM-driven Imitation of Subrational Behavior : Illusion or Reality? 提出利用LLM生成合成示范以建模亚理性行为 reinforcement learning imitation learning large language model
13 Enabling Multi-Agent Transfer Reinforcement Learning via Scenario Independent Representation 提出一种新框架以实现多智能体强化学习的迁移学习 reinforcement learning
14 Modeling Balanced Explicit and Implicit Relations with Contrastive Learning for Knowledge Concept Recommendation in MOOCs 提出CL-KCRec以解决MOOCs知识概念推荐中的隐式关系问题 contrastive learning

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