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GSM8K Dataset vs COCO 2017

Side-by-side comparison of GSM8K Dataset (Dataset) and COCO 2017 (Dataset).

79.8
Composite Score
GSM8K Dataset
Dataset · OpenAI
82.5
Composite Score
COCO 2017
Dataset · Microsoft
Overall Winner
COCO 2017
GSM8K Dataset wins 1 of 6 categories · COCO 2017 wins 4 of 6 categories

Score Comparison

GSM8K DatasetvsCOCO 2017
Composite
79.8:82.5
Adoption
94:97
Quality
91:96
Freshness
74:65
Citations
96:98
Engagement
0:0

Details

FieldGSM8K DatasetCOCO 2017
TypeDatasetDataset
ProviderOpenAIMicrosoft
Version1.02017
Categorybenchmarkscomputer-vision
Pricingopen-sourcefree
LicenseMITCC-BY-4.0
DescriptionGrade School Math 8K is a dataset of 8,500 high-quality linguistically diverse grade school math word problems requiring 2-8 step reasoning. Created by OpenAI, GSM8K is widely used for evaluating multi-step arithmetic reasoning and the effectiveness of chain-of-thought prompting.Microsoft COCO (Common Objects in Context) 2017 provides 118K training images with 860K object instances annotated with bounding boxes, segmentation masks, keypoints, and captions across 80 object categories. It remains the primary benchmark for object detection and instance segmentation research.

Capabilities

Only GSM8K Dataset

math-evaluationreasoning-benchmarkchain-of-thought

Shared

None

Only COCO 2017

object-detectioninstance-segmentationkeypoint-detectionimage-captioning

Integrations

Only GSM8K Dataset

huggingface-datasetslm-eval-harness

Shared

None

Only COCO 2017

PyTorchTensorFlowDetectron2MMDetection

Tags

Only GSM8K Dataset

mathgrade-schoolword-problemschain-of-thought

Shared

benchmark

Only COCO 2017

object-detectionsegmentationkeypointscaptions

Use Cases

GSM8K Dataset

  • model evaluation
  • math reasoning
  • chain of thought research

COCO 2017

  • model training
  • benchmark
  • computer vision research
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https://aaas.blog/compare/gsm8k-dataset-vs-coco-2017

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