A survey on large language model based autonomous agents
Autonomous agents have long been a research focus in academic and industry
communities. Previous research often focuses on training agents with limited knowledge …
communities. Previous research often focuses on training agents with limited knowledge …
Exploring large language model based intelligent agents: Definitions, methods, and prospects
Intelligent agents stand out as a potential path toward artificial general intelligence (AGI).
Thus, researchers have dedicated significant effort to diverse implementations for them …
Thus, researchers have dedicated significant effort to diverse implementations for them …
Towards efficient llm grounding for embodied multi-agent collaboration
Grounding the reasoning ability of large language models (LLMs) for embodied tasks is
challenging due to the complexity of the physical world. Especially, LLM planning for multi …
challenging due to the complexity of the physical world. Especially, LLM planning for multi …
A survey of ai-generated text forensic systems: Detection, attribution, and characterization
We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs)
capable of generating high-quality text. While these LLMs have revolutionized text …
capable of generating high-quality text. While these LLMs have revolutionized text …
Retrieval-Augmented Hierarchical in-Context Reinforcement Learning and Hindsight Modular Reflections for Task Planning with LLMs
Large Language Models (LLMs) have demonstrated remarkable abilities in various
language tasks, making them promising candidates for decision-making in robotics. Inspired …
language tasks, making them promising candidates for decision-making in robotics. Inspired …
LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions
In recent years, Large Language Models (LLMs) have shown great abilities in various tasks,
including question answering, arithmetic problem solving, and poem writing, among others …
including question answering, arithmetic problem solving, and poem writing, among others …
Empowering LLM Agents with Zero-Shot Optimal Decision-Making through Q-learning
Current Large language model (LLM) agents succeed in making zero-shot decisions but
struggle to make optimal decisions, as they rely on pre-trained probabilities rather than …
struggle to make optimal decisions, as they rely on pre-trained probabilities rather than …
Best of Both Worlds: Harmonizing LLM Capabilities in Decision-Making and Question-Answering for Treatment Regimes
This paper introduces a framework that incorporates fine-tuning large language models
(LLM) with reinforcement learning (RL) in the application of the dynamic treatment regime …
(LLM) with reinforcement learning (RL) in the application of the dynamic treatment regime …