Summary of Gamearena: Evaluating Llm Reasoning Through Live Computer Games, by Lanxiang Hu et al.
GameArena: Evaluating LLM Reasoning through Live Computer Games
by Lanxiang Hu, Qiyu Li, Anze Xie, Nan Jiang, Ion Stoica, Haojian Jin, Hao Zhang
First submitted to arxiv on: 9 Dec 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 (LLMs) require novel benchmarks to assess their reasoning abilities, as traditional methods rely on static datasets or binary human feedback. The Chatbot Arena dynamic benchmark evaluates open-ended questions in real-world settings but lacks granularity in assessing specific reasoning capabilities. This paper introduces GameArena, a dynamic benchmark designed to evaluate LLM reasoning capabilities through interactive gameplay with humans. GameArena consists of three games testing deductive and inductive reasoning while keeping participants entertained and engaged. The study analyzes gaming data retrospectively to uncover underlying reasoning processes and measures fine-grained reasoning capabilities for five state-of-the-art LLMs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are super smart computers that can understand and generate human-like text. But how good are they at thinking critically? To figure this out, researchers created a new way to test their reasoning skills called GameArena. It’s like a video game where humans play with the computer, trying to solve problems together. The games are designed to challenge different kinds of thinking, like making logical conclusions or guessing patterns. By analyzing how the computers and humans work together, scientists can see what kind of critical thinking abilities the computers have. This is important because it helps us understand how we can use these powerful machines in the future. |
