arXiv:cs.AI· Simon Henniger, Gabriel Poesia·· 5 小时前
The Token Games:用解谜对决评估语言模型推理能力
The Token Games: Evaluating Language Model Reasoning with Puzzle Duels
AI 导读
研究者提出 The Token Games(TTG)评估框架,让模型互相出题、以编程解谜形式对决,再用成对对决结果计算 Elo 评分。在 10 个前沿模型上,TTG 排名与 Humanity's Last Exam 等现有基准高度吻合,成本不到 200 美元且无需人工出题。研究同时发现,当前模型生成优质谜题仍相当困难。
正文
Abstract:Evaluating the reasoning capabilities of Large Language Models is increasingly challenging as models improve. Human curation of hard questions is highly expensive, especially in recent benchmarks using PhD-level domain knowledge to challenge the most capable models. Even then, there is always a concern about whether these questions test genuine reasoning or if similar problems have been seen during training. Here, we take inspiration from 16th-century mathematical duels to design The Token Games (TTG): an evaluation framework where models challenge each other by creating their own puzzles. We leverage the format of Programming Puzzles - given a function that returns a boolean, find inputs that make it return True - to flexibly represent problems and enable verifying solutions. Using results from pairwise duels, we then compute Elo ratings, allowing us to compare models relative to each other. We evaluate 10 frontier models on TTG, and closely match the ranking from existing benchmarks such as Humanity's Last Exam, spending less than $200 USD and without involving any human effort in creating puzzles. We also find that creating good puzzles is still a highly challenging task for current models. Overall, our work suggests new paradigms for evaluating reasoning that avoid saturation by design, and that allow testing models for other skills like creativity and task creation alongside problem solving.
| Comments: | Project website: this https URL |
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2602.17831 [cs.AI] |
| (or arXiv:2602.17831v3 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2602.17831 arXiv-issued DOI via DataCite |
Submission history
From: Simon Henniger [view email]
[v1]
Thu, 19 Feb 2026 20:49:15 UTC (482 KB)
[v2]
Fri, 15 May 2026 20:00:59 UTC (459 KB)
[v3]
Mon, 12 Oct 2026 20:25:01 UTC (568 KB)
来源:arXiv:cs.AI · arxiv.org