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 …
Challenges and applications of large language models
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …
A survey of large language models
Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …
Palm-e: An embodied multimodal language model
Large language models excel at a wide range of complex tasks. However, enabling general
inference in the real world, eg, for robotics problems, raises the challenge of grounding. We …
inference in the real world, eg, for robotics problems, raises the challenge of grounding. We …
Reflexion: Language agents with verbal reinforcement learning
Large language models (LLMs) have been increasingly used to interact with external
environments (eg, games, compilers, APIs) as goal-driven agents. However, it remains …
environments (eg, games, compilers, APIs) as goal-driven agents. However, it remains …
Pal: Program-aided language models
Large language models (LLMs) have demonstrated an impressive ability to perform
arithmetic and symbolic reasoning tasks, when provided with a few examples at test time (" …
arithmetic and symbolic reasoning tasks, when provided with a few examples at test time (" …
Mimic-it: Multi-modal in-context instruction tuning
High-quality instructions and responses are essential for the zero-shot performance of large
language models on interactive natural language tasks. For interactive vision-language …
language models on interactive natural language tasks. For interactive vision-language …
Rt-1: Robotics transformer for real-world control at scale
A Brohan, N Brown, J Carbajal, Y Chebotar… - arXiv preprint arXiv …, 2022 - arxiv.org
By transferring knowledge from large, diverse, task-agnostic datasets, modern machine
learning models can solve specific downstream tasks either zero-shot or with small task …
learning models can solve specific downstream tasks either zero-shot or with small task …
Rt-2: Vision-language-action models transfer web knowledge to robotic control
A Brohan, N Brown, J Carbajal, Y Chebotar… - arXiv preprint arXiv …, 2023 - arxiv.org
We study how vision-language models trained on Internet-scale data can be incorporated
directly into end-to-end robotic control to boost generalization and enable emergent …
directly into end-to-end robotic control to boost generalization and enable emergent …
Large language models are human-level prompt engineers
By conditioning on natural language instructions, large language models (LLMs) have
displayed impressive capabilities as general-purpose computers. However, task …
displayed impressive capabilities as general-purpose computers. However, task …