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README.md
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# WGO-Bench: What's Going On Benchmark
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> **Read the write-up:** [Segmenting Robot Video into Actionable Subtasks](https://macrodata.co/blog/annotating-robot-video-subtasks?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=wgo-bench) covers how WGO-Bench was built, the 60+ annotation pipeline experiments we ran on it, and what worked.
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WGO-Bench is a small, manually annotated benchmark for evaluating how well vision-language models can turn robot and egocentric manipulation videos into timestamped subtask annotations.
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## Related Resources
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- Blog post: [Segmenting Robot Video into Actionable Subtasks](https://macrodata.co/blog/annotating-robot-video-subtasks)
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- Refiner example: [Subtask annotations](https://macrodata.co/docs/examples/annotations/subtask-annotations)
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- Code: [macrodata-labs/refiner](https://github.com/macrodata-labs/refiner)
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# WGO-Bench: What's Going On Benchmark
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> **Read the write-up:** [Segmenting Robot Video into Actionable Subtasks](https://macrodata.co/blog/annotating-robot-video-subtasks?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=wgo-bench&utm_content=top_callout) covers how WGO-Bench was built, the 60+ annotation pipeline experiments we ran on it, and what worked.
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WGO-Bench is a small, manually annotated benchmark for evaluating how well vision-language models can turn robot and egocentric manipulation videos into timestamped subtask annotations.
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## Related Resources
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- Blog post: [Segmenting Robot Video into Actionable Subtasks](https://macrodata.co/blog/annotating-robot-video-subtasks?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=wgo-bench&utm_content=related_resources)
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- Refiner example: [Subtask annotations](https://macrodata.co/docs/examples/annotations/subtask-annotations?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=wgo-bench&utm_content=related_resources)
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- Code: [macrodata-labs/refiner](https://github.com/macrodata-labs/refiner)
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