Critic: Large language models can self-correct with tool-interactive critiquing

Z Gou, Z Shao, Y Gong, Y Shen, Y Yang… - arxiv preprint arxiv …, 2023 - arxiv.org
Recent developments in large language models (LLMs) have been impressive. However,
these models sometimes show inconsistencies and problematic behavior, such as …

Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions

H Trivedi, N Balasubramanian, T Khot… - arxiv preprint arxiv …, 2022 - arxiv.org
Prompting-based large language models (LLMs) are surprisingly powerful at generating
natural language reasoning steps or Chains-of-Thoughts (CoT) for multi-step question …

Cognitive architectures for language agents

TR Sumers, S Yao, K Narasimhan… - arxiv preprint arxiv …, 2023 - arxiv.org
Recent efforts have incorporated large language models (LLMs) with external resources (eg,
the Internet) or internal control flows (eg, prompt chaining) for tasks requiring grounding or …

Frugalgpt: How to use large language models while reducing cost and improving performance

L Chen, M Zaharia, J Zou - arxiv preprint arxiv:2305.05176, 2023 - arxiv.org
There is a rapidly growing number of large language models (LLMs) that users can query for
a fee. We review the cost associated with querying popular LLM APIs, eg GPT-4, ChatGPT …