Sequential Reasoning

Sequential reasoning, the ability of artificial intelligence to understand and predict chains of events, is a rapidly developing area of research focusing on improving the performance of large language models (LLMs). Current efforts concentrate on developing benchmarks that evaluate LLMs' ability to handle complex, interconnected sequences, particularly within interactive and algorithmic contexts like economic modeling or graph traversal. These evaluations reveal significant performance differences between closed-source and open-source models, highlighting the need for further research into improving the sequential reasoning capabilities of LLMs, which has broad implications for fields ranging from economic forecasting to automated problem-solving.