A survey of LLM-based autonomous agents that proposes a unified framework for their construction and reviews applications in social science, natural science, and engineering along with evaluation methods and future directions.
Memory augmented large language models are computationally universal
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Pre-trained LLMs using recursive criticism and improvement prompting achieve state-of-the-art results on the MiniWoB++ computer task benchmark with only a handful of demonstrations and no task-specific reward function.
Existing proofs of autoregressive Transformer Turing-completeness apply to scaling families of models rather than fixed systems with context management, so they do not establish Turing-completeness for real-world LLMs.
A survey paper providing an overview of Large Language Models, their background, and recent advances in the field.
citing papers explorer
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A Survey on Large Language Model based Autonomous Agents
A survey of LLM-based autonomous agents that proposes a unified framework for their construction and reviews applications in social science, natural science, and engineering along with evaluation methods and future directions.
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Language Models can Solve Computer Tasks
Pre-trained LLMs using recursive criticism and improvement prompting achieve state-of-the-art results on the MiniWoB++ computer task benchmark with only a handful of demonstrations and no task-specific reward function.
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Position: The Turing-Completeness of Autoregressive Transformers Relies Heavily on Context Management
Existing proofs of autoregressive Transformer Turing-completeness apply to scaling families of models rather than fixed systems with context management, so they do not establish Turing-completeness for real-world LLMs.
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A Comprehensive Overview of Large Language Models
A survey paper providing an overview of Large Language Models, their background, and recent advances in the field.