Summary of Glee: a Unified Framework and Benchmark For Language-based Economic Environments, by Eilam Shapira et al.
GLEE: A Unified Framework and Benchmark for Language-based Economic Environments
by Eilam Shapira, Omer Madmon, Itamar Reinman, Samuel Joseph Amouyal, Roi Reichart, Moshe Tennenholtz
First submitted to arxiv on: 7 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Computer Science and Game Theory (cs.GT); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Large Language Models (LLMs) have significant potential in economic and strategic interactions, where communication via natural language is prevalent. The paper explores whether LLMs behave rationally, mimic human behavior, and tend to reach an efficient and fair outcome. It also examines the role of natural language in these dynamics and how characteristics of the economic environment influence them. The study’s findings have crucial implications for integrating LLM-based agents into real-world data-driven systems, such as online retail platforms and recommender systems. The research community has been exploring LLMs’ potential in multi-agent setups, but varying assumptions, design choices, and evaluation criteria make it challenging to draw robust conclusions. To address this, the paper introduces a benchmark for standardizing research on two-player, sequential, language-based games. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models can be used to understand how people interact with each other economically. The study looks at whether these models behave in a smart way, act like humans, and make fair decisions. It also investigates how the environment affects their behavior. This is important because we want to know if these models can be used in real-life systems that involve online shopping or recommendations. |
