ByteDance's GST-Bench: VLMs score 42.68 vs human 79.08 on global spatial awareness
ByteDance-Seed · hf · 2026-08-07
ByteDance Seed introduces GST-Bench, a VQA benchmark for global spatial intelligence in video, with human-verified questions from 6,790 min of synthetic video. Evaluating 22 SOTA VLMs, the best zero-shot model scores 42.68, far below human 79.08. Models show strong local understanding but fail to consolidate long-horizon observations into a globally consistent scene representation. GST-Train dataset is also provided.
More from Research
- AI will be superhuman at science regardless, and Europe can't opt out — teortaxesTex · 2026-10-16
- SERO augments long-horizon agentic RL with executable oracle continuations — Shanghai-AI-Laboratory · 2026-10-16
- Tsinghua and Amap propose OmniVerifier-C1, a graded verifier beating binary judges — Bowei Liu · 2026-10-16
- Alibaba open-sources MAI-Gym, an all-in-one GUI agent eval and RL training platform — Tongyi-MAI · 2026-10-16
- Peking University's SimForcing distills simulation motion priors into robot world models — PekingUniversity · 2026-10-16
- CoWorld Reasoner uses an evolving video world model as a visual reasoning engine — ModalityDance · 2026-10-16