A survey on machine reading comprehension systems
Machine Reading Comprehension (MRC) is a challenging task and hot topic in Natural
Language Processing. The goal of this field is to develop systems for answering the …
Language Processing. The goal of this field is to develop systems for answering the …
APER: adaptive evidence-driven reasoning network for machine reading comprehension with unanswerable questions
Abstract Machine Reading Comprehension with unanswerable questions requires that
systems not only answer questions when possible, but also output an unanswerable …
systems not only answer questions when possible, but also output an unanswerable …
A survey of methods for revealing and overcoming weaknesses of data-driven Natural Language Understanding
V Schlegel, G Nenadic… - Natural Language …, 2023 - cambridge.org
Recent years have seen a growing number of publications that analyse Natural Language
Understanding (NLU) datasets for superficial cues, whether they undermine the complexity …
Understanding (NLU) datasets for superficial cues, whether they undermine the complexity …
A cascaded retrieval-while-reasoning multi-document comprehension framework with incremental attention for medical question answering
Abstract Clinical Machine Reading Comprehension (MRC) is challenging due to the need
for medical expertise and comprehensive reasoning chains for diagnosis. This paper …
for medical expertise and comprehensive reasoning chains for diagnosis. This paper …
Improving the robustness of machine reading comprehension via contrastive learning
J Feng, J Sun, D Shao, J Cui - Applied Intelligence, 2023 - Springer
Pre-trained language models achieve high performance on machine reading
comprehension task, but these models lack robustness and are vulnerable to adversarial …
comprehension task, but these models lack robustness and are vulnerable to adversarial …
Verb-driven machine reading comprehension with dual-graph neural network
H Zhang, C Jiang - Pattern Recognition Letters, 2023 - Elsevier
Logical reasoning of context is vital for reading comprehension, which requires to explore
the logical relationship through sentence structure. However, previous methods of logical …
the logical relationship through sentence structure. However, previous methods of logical …
[HTML][HTML] Robustness-Eva-MRC: Assessing and analyzing the robustness of neural models in extractive machine reading comprehension
Deep neural networks, despite their remarkable success in various language understanding
tasks, have been found vulnerable to adversarial attacks and subtle input perturbations …
tasks, have been found vulnerable to adversarial attacks and subtle input perturbations …
Continual machine reading comprehension via uncertainty-aware fixed memory and adversarial domain adaptation
Continual Machine Reading Comprehension aims to incrementally learn from a continuous
data stream across time without access the previous seen data, which is crucial for the …
data stream across time without access the previous seen data, which is crucial for the …
An understanding-oriented robust machine reading comprehension model
Although existing machine reading comprehension models are making rapid progress on
many datasets, they are far from robust. In this article, we propose an understanding …
many datasets, they are far from robust. In this article, we propose an understanding …
Integrating a Heterogeneous Graph with Entity-aware Self-attention using Relative Position Labels for Reading Comprehension Model
Despite the significant progress made by transformer models in machine reading
comprehension tasks, they still face limitations in handling complex reasoning tasks due to …
comprehension tasks, they still face limitations in handling complex reasoning tasks due to …