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Found 6 papers, 5 papers with code
A Survey of Pre-trained Language Models for Processing Scientific Text
The number of Language Models (LMs) dedicated to processing scientific text is on the rise.
Solving Label Variation in Scientific Information Extraction via Multi-Task Learning
The complexity of this task is compounded by the necessity for domain-specific knowledge and the limited availability of annotated data.
Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question Answering
To explain the predicted answers and evaluate the reasoning abilities of models, several studies have utilized underlying reasoning (UR) tasks in multi-hop question answering (QA) datasets.
Multi-hop Question Answering
Open-Ended Question Answering
+1
How Well Do Multi-hop Reading Comprehension Models Understand Date Information?
Other results reveal that our probing questions can help to improve the performance of the models (e. g., by +10. 3 F1) on the main QA task and our dataset can be used for data augmentation to improve the robustness of the models.
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension
The issue of shortcut learning is widely known in NLP and has been an important research focus in recent years.
Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps
The evidence information has two benefits: (i) providing a comprehensive explanation for predictions and (ii) evaluating the reasoning skills of a model.
