[R] REBUS: A Robust Evaluation Benchmark of Understanding Symbols

**Paper**: [https://arxiv.org/abs/2401.05604](https://arxiv.org/abs/2401.05604)

**Code**: [https://github.com/cvndsh/rebus](https://github.com/cvndsh/rebus)

**Dataset**: [https://huggingface.co/datasets/cavendishlabs/rebus](https://huggingface.co/datasets/cavendishlabs/rebus)

**Project page**: [https://cavendishlabs.org/rebus/](https://cavendishlabs.org/rebus/)

**Abstract**:

>We propose a new benchmark evaluating the performance of multimodal large language models on rebus puzzles. The dataset covers 333 original examples of image-based wordplay, cluing 13 categories such as movies, composers, major cities, and food. To achieve good performance on the benchmark of identifying the clued word or phrase, models must combine image recognition and string manipulation with hypothesis testing, multi-step reasoning, and an understanding of human cognition, making …

abstract benchmark cities dataset examples food good image image recognition language language models large language large language models machinelearning major manipulation movies multimodal performance recognition string word wordplay