Datasets › STAR Benchmark
STAR Benchmark (Situated Reasoning)
How to capture the present knowledge from surrounding situations and perform reasoning accordingly is crucial and challenging for machine intelligence. STAR Benchmark is a novel benchmark for Situated Reasoning, which provides 60K challenging situated questions in four types of tasks, 140K situated hypergraphs, symbolic situation programs, and logic-grounded diagnosis for real-world video situations. (Data Download, STAR Leaderboard)
Benchmarks archive 2025-07-28
All 2 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Video Question Answering | STAR Benchmark | VLAP (4 frames) Average Accuracy 67.1 | ViLA: Efficient Video-Language Alignment for Video... | xijun-cs/vila | 17 | Compare |
| Zero-Shot Video Question Answer | STAR Benchmark | VideoChat2 Accuracy 59.0 | MVBench: A Comprehensive Multi-modal Video Understanding... | opengvlab/ask-anything +2 | 4 | Compare |
Papers archive 2025-07-28
14 shown of 14 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 17. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- STAR Benchmark
1 variant name, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections