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Models/IOG

IOG

Reported on 13 benchmarks across 3 tasks

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing8 results

  • Sentiment AnalysisonSemEval-2014 Task-4
    Laptop 2014 (F1)
    71.35
    best: 80.55 (BARTABSA)
  • Sentiment AnalysisonSemEval-2014 Task-4
    Restaurant 2014 (F1)
    80.02
    best: 85.38 (BARTABSA)
  • Sentiment AnalysisonSemEval-2014 Task-4
    Restaurant 2015 (F1)
    73.25
    best: 80.52 (BARTABSA)
  • Sentiment AnalysisonSemEval-2014 Task-4
    Restaurant 2016 (F1)
    81.69
    best: 87.92 (BARTABSA)
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval-2014 Task-4
    Laptop 2014 (F1)
    71.35
    best: 80.55 (BARTABSA)
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval-2014 Task-4
    Restaurant 2014 (F1)
    80.02
    best: 85.38 (BARTABSA)
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval-2014 Task-4
    Restaurant 2015 (F1)
    73.25
    best: 80.52 (BARTABSA)
  • Aspect-Based Sentiment Analysis (ABSA)onSemEval-2014 Task-4
    Restaurant 2016 (F1)
    81.69
    best: 87.92 (BARTABSA)

Computer Vision5 results

  • Interactive SegmentationonPASCAL2COCO(Unseen)
    Instance Average IoU
    82.1
  • Interactive SegmentationonRooftop
    Instance Average IoU
    94
  • Interactive SegmentationonssTEM
    Instance Average IoU
    83.7
  • Interactive SegmentationonCOCO (Common Objects in Context)
    Instance Average IoU
    85.2
  • Interactive SegmentationonCityscapes val
    Instance Average IoU
    83.8