tiedong/vetbench
VET-Bench: Visual Entity Tracking Benchmark Paper | Project Page | GitHub VET-Bench is a synthetic diagnostic benchmark simulating the realistic shell game with visually indistinguishable objects that forces models to track entities through spatiotemporal continuity. The task is easy for human but difficult for current VLMs. State-of-the-art VLMs perform at random chance, while our proposed Molmo2-SGCoT achieves over 90% accuracy. Dataset Overview Cup Game… See the full description on the dataset page: https://huggingface.co/datasets/tiedong/vetbench.
| Author / organization | tiedong |
|---|---|
| License (as declared) | mit |
| Downloads | 249 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 10 March 2026 |
| Last updated at source | 2 April 2026 |
Popularity, last 2 days
249 now (+46 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- Can Vision-Language Models Solve the Shell Game?Paper · cites
Recent changes
- 17 Oct 2026 Description: VET-Bench: Visual Entity Tracking Benchmark Paper | Project Page | GitHub VET-Bench is a synthetic diagnostic benchmark simulating the realistic shell game with visually indistinguishable objects that forces models to track entities through → VET-Bench: Visual Entity Tracking Benchmark Paper | Project Page | GitHub VET-Bench is a synthetic diagnostic benchmark simulating the realistic shell game with visually indistinguishable objects that forces models to track entities through
Changes detected by Silytics between refreshes of the source.
Related papers
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.