Comparison of text preprocessing methods
CP Chai - Natural Language Engineering, 2023 - cambridge.org
Text preprocessing is not only an essential step to prepare the corpus for modeling but also
a key area that directly affects the natural language processing (NLP) application results. For …
a key area that directly affects the natural language processing (NLP) application results. For …
Nl-augmenter: A framework for task-sensitive natural language augmentation
Data augmentation is an important component in the robustness evaluation of models in
natural language processing (NLP) and in enhancing the diversity of the data they are …
natural language processing (NLP) and in enhancing the diversity of the data they are …
Robust encodings: A framework for combating adversarial typos
Despite excellent performance on many tasks, NLP systems are easily fooled by small
adversarial perturbations of inputs. Existing procedures to defend against such perturbations …
adversarial perturbations of inputs. Existing procedures to defend against such perturbations …
Context-aware misinformation detection: A benchmark of deep learning architectures using word embeddings
New mass media paradigms for information distribution have emerged with the digital age.
With new digital-enabled mass media, the communication process is centered around the …
With new digital-enabled mass media, the communication process is centered around the …
Text adversarial attacks and defenses: Issues, taxonomy, and perspectives
Deep neural networks (DNNs) have been widely used in many fields due to their powerful
representation learning capabilities. However, they are exposed to serious threats caused …
representation learning capabilities. However, they are exposed to serious threats caused …
Computational models to study language processing in the human brain: A survey
Despite differing from the human language processing mechanism in implementation and
algorithms, current language models demonstrate remarkable human-like or surpassing …
algorithms, current language models demonstrate remarkable human-like or surpassing …
Classification benchmarks for under-resourced bengali language based on multichannel convolutional-lstm network
MR Karim, BR Chakravarthi… - 2020 IEEE 7th …, 2020 - ieeexplore.ieee.org
Exponential growths of social media and micro-blogging sites not only provide platforms for
empowering freedom of expressions and individual voices, but also enables people to …
empowering freedom of expressions and individual voices, but also enables people to …
Automatic classification of scanned electronic health record documents
Abstract Objectives Electronic Health Records (EHRs) contain scanned documents from a
variety of sources such as identification cards, radiology reports, clinical correspondence …
variety of sources such as identification cards, radiology reports, clinical correspondence …
On learning and representing social meaning in NLP: a sociolinguistic perspective
The field of NLP has made substantial progress in building meaning representations.
However, an important aspect of linguistic meaning, social meaning, has been largely …
However, an important aspect of linguistic meaning, social meaning, has been largely …
Improving zero-shot cross-lingual transfer learning via robust training
Pre-trained multilingual language encoders, such as multilingual BERT and XLM-R, show
great potential for zero-shot cross-lingual transfer. However, these multilingual encoders do …
great potential for zero-shot cross-lingual transfer. However, these multilingual encoders do …