Question Answering On Wikihop
Metrics
Test
Results
Performance results of various models on this benchmark
Model Name | Test | Paper Title | Repository |
|---|---|---|---|
| Coref-GRU | 59.3 | Neural Models for Reasoning over Multiple Mentions using Coreference | - |
| CFC | 70.6 | Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering | - |
| MHPGM + NOIC | 57.9 | Commonsense for Generative Multi-Hop Question Answering Tasks | |
| BigBird-etc | 82.3 | Big Bird: Transformers for Longer Sequences | |
| BiDAF | 42.9 | Constructing Datasets for Multi-hop Reading Comprehension Across Documents | - |
| MultiHop (Chen et al., [2019a]) | 76.5 | Multi-hop Question Answering via Reasoning Chains | |
| MHQA | 65.4 | Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks | - |
| LUKE-Graph | 81.0 | LUKE-Graph: A Transformer-based Approach with Gated Relational Graph Attention for Cloze-style Reading Comprehension | - |
| Longformer-large | 81.9 | Longformer: The Long-Document Transformer |
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