Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/Ensemble + Finetune

Ensemble + Finetune

Reported on 12 benchmarks across 2 tasks · 1 paper · 4 SOTA

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

Speech6 results

DialogueonVisual Dialog v1.0 test-std
Mean· 2019-11-26
6.53
best: 49.61 (qqhe)
SOTA
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
DialogueonVisual Dialog v1.0 test-std
NDCG (x 100)· 2019-11-26
74.88
best: 78.7 (Single)
SOTA
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
DialogueonVisual Dialog v1.0 test-std
MRR (x 100)· 2019-11-26
52.14
best: 71.24 (MRR ensemble (Naive))
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
DialogueonVisual Dialog v1.0 test-std
R@1· 2019-11-26
38.92
best: 58.3 (2 Step: Factor Graph Attention + VD-Bert)
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
DialogueonVisual Dialog v1.0 test-std
R@10· 2019-11-26
80.65
best: 95.08 (Ensemble FGA + BERT)
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
DialogueonVisual Dialog v1.0 test-std
R@5· 2019-11-26
66.6
best: 88.42 (Ensemble FGA + BERT)
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390

Computer Vision6 results

Visual DialogonVisual Dialog v1.0 test-std
Mean· 2019-11-26
6.53
best: 49.61 (qqhe)
SOTA
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
Visual DialogonVisual Dialog v1.0 test-std
NDCG (x 100)· 2019-11-26
74.88
best: 78.7 (Single)
SOTA
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
Visual DialogonVisual Dialog v1.0 test-std
MRR (x 100)· 2019-11-26
52.14
best: 71.24 (MRR ensemble (Naive))
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
Visual DialogonVisual Dialog v1.0 test-std
R@1· 2019-11-26
38.92
best: 58.3 (2 Step: Factor Graph Attention + VD-Bert)
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
Visual DialogonVisual Dialog v1.0 test-std
R@10· 2019-11-26
80.65
best: 95.08 (Ensemble FGA + BERT)
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390
Visual DialogonVisual Dialog v1.0 test-std
R@5· 2019-11-26
66.6
best: 88.42 (Ensemble FGA + BERT)
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs arXiv:1911.11390