Papers with SemEval-2018 Task
Hypernym Discovery via a Recurrent Mapping Model (2021.findings-acl)
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| Challenge: | Empirical studies on SemEval-2018 Task 9 confirm the effectiveness of the presented model. |
| Approach: | They propose a parallel style model that maps query words to their hypernyms . they use a lexical-semantic relation to name a specific instance or subtype hyponym . |
| Outcome: | Empirical results on SemEval-2018 Task 9 confirm the effectiveness of the proposed model. |
Improving Machine Reading Comprehension with General Reading Strategies (N19-1)
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| Challenge: | Recent studies have shown that reading strategies improve comprehension levels for readers lacking adequate prior knowledge. |
| Approach: | They propose three general strategies to improve machine reading comprehension (MRC) by fine-tuning a pre-trained model with strategies and a target task. |
| Outcome: | The proposed models improve non-extractive machine reading comprehension (MRC) on the largest general domain multiple-choice dataset RACE. |
Reproducing Neural Ensemble Classifier for Semantic Relation Extraction inScientific Papers (2020.lrec-1)
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| Challenge: | Replicability and reproducibility are core ideas of modern scientific methods. |
| Approach: | They describe challenges encountered in reproducing the results of a top performing system in computational linguistics. |
| Outcome: | The proposed system was able to reproduce the results of a task 7 in the domain of natural language processing and computational linguistics. |