Auto-gpt for online decision making: Benchmarks and additional opinions

H Yang, S Yue, Y He - arXiv preprint arXiv:2306.02224, 2023 - arxiv.org
Auto-GPT is an autonomous agent that leverages recent advancements in adapting Large
Language Models (LLMs) for decision-making tasks. While there has been a growing …

Expel: Llm agents are experiential learners

A Zhao, D Huang, Q Xu, M Lin, YJ Liu… - Proceedings of the AAAI …, 2024 - ojs.aaai.org
The recent surge in research interest in applying large language models (LLMs) to decision-
making tasks has flourished by leveraging the extensive world knowledge embedded in …

Automl-gpt: Automatic machine learning with gpt

S Zhang, C Gong, L Wu, X Liu, M Zhou - arXiv preprint arXiv:2305.02499, 2023 - arxiv.org
AI tasks encompass a wide range of domains and fields. While numerous AI models have
been designed for specific tasks and applications, they often require considerable human …

Can we trust the evaluation on ChatGPT?

R Aiyappa, J An, H Kwak, YY Ahn - arXiv preprint arXiv:2303.12767, 2023 - arxiv.org
ChatGPT, the first large language model (LLM) with mass adoption, has demonstrated
remarkable performance in numerous natural language tasks. Despite its evident …

Chatgpt's one-year anniversary: are open-source large language models catching up?

H Chen, F Jiao, X Li, C Qin, M Ravaut, R Zhao… - arXiv preprint arXiv …, 2023 - arxiv.org
Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of
AI, both in research and commerce. Through instruction-tuning a large language model …

Autoact: Automatic agent learning from scratch via self-planning

S Qiao, N Zhang, R Fang, Y Luo, W Zhou… - arXiv preprint arXiv …, 2024 - arxiv.org
Language agents have achieved considerable performance on various complex tasks.
Despite the incessant exploration in this field, existing language agent systems still struggle …

Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face

Y Shen, K Song, X Tan, D Li, W Lu… - Advances in Neural …, 2024 - proceedings.neurips.cc
Solving complicated AI tasks with different domains and modalities is a key step toward
artificial general intelligence. While there are numerous AI models available for various …

Retroformer: Retrospective large language agents with policy gradient optimization

W Yao, S Heinecke, JC Niebles, Z Liu, Y Feng… - arXiv preprint arXiv …, 2023 - arxiv.org
Recent months have seen the emergence of a powerful new trend in which large language
models (LLMs) are augmented to become autonomous language agents capable of …

Tptu-v2: Boosting task planning and tool usage of large language model-based agents in real-world systems

Y Kong, J Ruan, Y Chen, B Zhang, T Bao, S Shi… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) have demonstrated proficiency in addressing tasks that
necessitate a combination of task planning and the usage of external tools that require a …

Lumos: Learning agents with unified data, modular design, and open-source llms

D Yin, F Brahman, A Ravichander, K Chandu… - arXiv preprint arXiv …, 2023 - arxiv.org
We introduce Lumos, a novel framework for training language agents that employs a unified
data format and a modular architecture based on open-source large language models …