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Models/SEAL

SEAL

Reported on 6 benchmarks across 4 tasks · 3 papers · 3 SOTA

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

Graphs4 results

Link PredictiononUSAir
AUC· 2018-02-27
97.09
SOTA
Link Prediction Based on Graph Neural Networks arXiv:1802.09691
Link Property Predictiononogbl-ddi
Number of params· 2020-10-30
531138
best: 976022023 (HyperFusion)
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning arXiv:2010.16103
Link Property Predictiononogbl-citation2
Number of params· 2020-10-30
260802
best: 749757283 (MPLP)
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning arXiv:2010.16103
Link Property Predictiononogbl-ppa
Number of params· 2020-10-30
709122
best: 295848449 (Refined-GAE)
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning arXiv:2010.16103

Natural Language Processing2 results

Visual Question Answering (VQA)onV*bench
Accuracy· uses extra data· 2023-12-21
75.39
best: 92.15 (LLaVA-OneVision7B w. FOCUS)
SOTA
V*: Guided Visual Search as a Core Mechanism in Multimodal LLMs arXiv:2312.14135
Visual Question AnsweringonV*bench
Accuracy· uses extra data· 2023-12-21
75.39
best: 92.15 (LLaVA-OneVision7B w. FOCUS)
SOTA
V*: Guided Visual Search as a Core Mechanism in Multimodal LLMs arXiv:2312.14135