반응형

2024/11/19 4

Towards End-to-End Embodied Decision Making via Multi-modal Large Language Model: Explorations with GPT4-Vision and Beyond - 논문 리뷰

https://arxiv.org/abs/2310.02071 Towards End-to-End Embodied Decision Making via Multi-modal Large Language Model: Explorations with GPT4-Vision and BeyondIn this study, we explore the potential of Multimodal Large Language Models (MLLMs) in improving embodied decision-making processes for agents. While Large Language Models (LLMs) have been widely used due to their advanced reasoning skills and..

Evolution of SAE Features Across Layers in LLMs - 논문 리뷰

https://arxiv.org/abs/2410.08869 Evolution of SAE Features Across Layers in LLMsSparse Autoencoders for transformer-based language models are typically defined independently per layer. In this work we analyze statistical relationships between features in adjacent layers to understand how features evolve through a forward pass. We provarxiv.org이 논문은 SAE의 초기 논문 같네요모든 Layer에 SAE를 장착하고, 그 SAE를 분석하여 ..

Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives - 논문 리뷰

https://arxiv.org/abs/2312.11970 Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and PerspectivesAgent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Integrating large language models into agent-based modeling and simulation prearxiv.org     논..

The Rise and Potential of Large Language Model Based Agents: A Survey - 논문 리뷰

https://arxiv.org/abs/2309.07864 The Rise and Potential of Large Language Model Based Agents: A SurveyFor a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are artificial entities that sense their environment, make decisions,arxiv.org 일단 80페이지 짜리 논문입니다....읽어보려고 했으나 ..

728x90
728x90