← all papers · overview

UNO Arena For Evaluating Sequential Decision-making Capability Of Large Language Models

Abstract

Sequential decision-making refers to algorithms that take into account the dynamics of the environment, where early decisions affect subsequent decisions. With large language models (LLMs) demonstrating powerful capabilities between tasks, we can't help but ask: Can Current LLMs Effectively Make Sequential Decisions? In order to answer this question, we propose the UNO Arena based on the card game

Related papers

Ranked by semantic similarity — how closely each paper's abstract matches this one (100% = near-identical topic).