zelaix/VS-Bench
Dataset Summary VS-Bench is a multimodal benchmark for evaluating VLMs in multi-agent environments. We evaluate fourteen state-of-the-art models in eight vision-grounded environments with two complementary dimensions, including offline evaluation of strategic reasoning by next-action prediction accuracy and online evaluation of decision-making by normalized episode return. Citation Information @article{xu2025vs, title={VS-Bench: Evaluating VLMs for Strategic Reasoning… See the full description on the dataset page: https://huggingface.co/datasets/zelaix/VS-Bench.
| Author / organization | zelaix |
|---|---|
| License (as declared) | mit |
| Downloads | 127 (as reported by Hugging Face) |
| Likes | 3 |
| Created | 2 June 2025 |
| Last updated at source | 4 June 2025 |
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