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Datasets/GTA

GTA

A Benchmark for General Tool Agents

ImagesTextsApache-2.0Introduced 2024-07-11

A benchmark to evaluate the tool-use capabilities of LLM-based agents in real-world scenarios.

Related Benchmarks

GTA-IM Dataset/1 Image, 2*2 Stitchi/Path ErrorGTA-IM Dataset/1 Image, 2*2 Stitchi/Pose ErrorGTA-IM Dataset/3D/Path ErrorGTA-IM Dataset/3D/Pose ErrorGTA-IM Dataset/Pose Estimation/Path ErrorGTA-IM Dataset/Pose Estimation/Pose ErrorGTA-IM Dataset/Trajectory Prediction/ADEGTA-IM Dataset/Trajectory Prediction/FDEGTA-IM Dataset/Trajectory Prediction/STBGTA-to-Avg(Cityscapes,BDD,Mapillary)/Domain Adaptation/mIoUGTA-to-Avg(Cityscapes,BDD,Mapillary)/Domain Generalization/mIoUGTA-to-FoggyCityscapes/Domain Adaptation/mIoUGTA5 to Cityscapes/Domain Adaptation/mIoUGTA5 to Cityscapes/Source-Free Domain Adaptation/mIoUGTA5+Synscapes to Cityscapes/Domain Adaptation/mIoUGTA5+Synscapes+Urbansyn to Cityscapes/Domain Adaptation/mIoUGTA5+Synscapes+Urbansyn to Cityscapes/Unsupervised Domain Adaptation/mIoUGTA5-to-Cityscapes/Domain Adaptation/mIoUGTA5-to-Cityscapes/Domain Generalization/mIoUGTA5-to-Cityscapes/Unsupervised Domain Adaptation/mIoUGTAV to Cityscapes+Mapillary/Domain Adaptation/mIoUGTAV+Synscapes to Cityscapes/Domain Adaptation/mIoUGTAV-to-Cityscapes Labels/1 Image, 2*2 Stitching/Per-pixel AccuracyGTAV-to-Cityscapes Labels/1 Image, 2*2 Stitching/fwIOUGTAV-to-Cityscapes Labels/1 Image, 2*2 Stitching/mIoUGTAV-to-Cityscapes Labels/10-shot image generation/mIoUGTAV-to-Cityscapes Labels/Domain Adaptation/mIoUGTAV-to-Cityscapes Labels/Image Generation/Per-pixel AccuracyGTAV-to-Cityscapes Labels/Image Generation/fwIOUGTAV-to-Cityscapes Labels/Image Generation/mIoUGTAV-to-Cityscapes Labels/Image-to-Image Translation/Per-pixel AccuracyGTAV-to-Cityscapes Labels/Image-to-Image Translation/fwIOUGTAV-to-Cityscapes Labels/Image-to-Image Translation/mIoUGTAV-to-Cityscapes Labels/Semantic Segmentation/mIoUGTAV-to-Cityscapes Labels/Unsupervised Domain Adaptation/mIoU

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