Summary of Logicgame: Benchmarking Rule-based Reasoning Abilities Of Large Language Models, by Jiayi Gui et al.
LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models
by Jiayi Gui, Yiming Liu, Jiale Cheng, Xiaotao Gu, Xiao Liu, Hongning Wang, Yuxiao Dong, Jie Tang, Minlie Huang
First submitted to arxiv on: 28 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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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 have shown impressive capabilities across various tasks, showcasing complex problem-solving abilities. While they can understand and execute complex rules, as well as plan multiple steps ahead, evaluating these models as effective rule-based executors and planners remains underexplored. This paper introduces LogicGame, a novel benchmark designed to evaluate the comprehensive rule understanding, execution, and planning capabilities of Large Language Models. Unlike traditional benchmarks, LogicGame provides diverse games containing series of rules with an initial state, requiring models to comprehend and apply predefined regulations to solve problems. The evaluation considers not only final outcomes but also intermediate steps, providing a comprehensive assessment of model performance. Moreover, these intermediate steps are deterministic and can be automatically verified. LogicGame defines game scenarios with varying difficulty levels, from simple rule applications to complex reasoning chains, offering a precise evaluation of model performance on rule understanding and multi-step execution. Various Large Language Models were tested using LogicGame, identifying notable shortcomings in their rule-based logical reasoning abilities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models are really good at solving problems and making decisions. But how well do they understand rules and make plans? This paper introduces a new way to test these models called LogicGame. It’s like a game where the model has to follow rules to solve a problem. The game has different levels, from easy to hard, so we can see how good the model is at understanding rules and making plans. |
