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View article: Efficient Methods for Natural Language Processing: A Survey
Efficient Methods for Natural Language Processing: A Survey Open
Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance means that resource consumption also grows. Such resources inc…
View article: NOHATE: Automatisierte Identifikation von Hate Speech in Nutzerkommentaren zum Thema Flucht und Migration (Projektdokumentation)
NOHATE: Automatisierte Identifikation von Hate Speech in Nutzerkommentaren zum Thema Flucht und Migration (Projektdokumentation) Open
In the interdisciplinary research project "NOHATE – Overcoming crises in public communication about refugees, migration, foreigners", communication scholars, information scientists and computer linguists analyzed hate speech in user commen…
View article: Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research
Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research Open
Many recent improvements in NLP stem from the development and use of large pre-trained language models (PLMs) with billions of parameters. Large model sizes makes computational cost one of the main limiting factors for training and evaluat…
View article: Efficient Methods for Natural Language Processing: A Survey
Efficient Methods for Natural Language Processing: A Survey Open
Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance means that resource consumption also grows. Such resources inc…
View article: This Patient Looks Like That Patient: Prototypical Networks for Interpretable Diagnosis Prediction from Clinical Text
This Patient Looks Like That Patient: Prototypical Networks for Interpretable Diagnosis Prediction from Clinical Text Open
The use of deep neural models for diagnosis prediction from clinical text has shown promising results. However, in clinical practice such models must not only be accurate, but provide doctors with interpretable and helpful results. We intr…
View article: Efficient Methods for Natural Language Processing: A Survey
Efficient Methods for Natural Language Processing: A Survey Open
Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance means that resource consumption also grows. Such resources inc…
View article: Cross-Lingual Knowledge Transfer for Clinical Phenotyping
Cross-Lingual Knowledge Transfer for Clinical Phenotyping Open
Clinical phenotyping enables the automatic extraction of clinical conditions from patient records, which can be beneficial to doctors and clinics worldwide. However, current state-of-the-art models are mostly applicable to clinical notes w…
View article: What Do You See in this Patient? Behavioral Testing of Clinical NLP Models
What Do You See in this Patient? Behavioral Testing of Clinical NLP Models Open
Decision support systems based on clinical notes have the potential to improve patient care by pointing doctors towards overseen risks. Predicting a patient's outcome is an essential part of such systems, for which the use of deep neural n…
View article: What Do You See in this Patient? Behavioral Testing of Clinical NLP Models
What Do You See in this Patient? Behavioral Testing of Clinical NLP Models Open
Decision support systems based on clinical notes have the potential to improve patient care by pointing doctors towards overseen risks. Predicting a patient's outcome is an essential part of such systems, for which the use of deep neural n…
View article: Assertion Detection in Clinical Notes: Medical Language Models to the Rescue?
Assertion Detection in Clinical Notes: Medical Language Models to the Rescue? Open
In order to provide high-quality care, health professionals must efficiently identify the presence, possibility, or absence of symptoms, treatments and other relevant entities in free-text clinical notes. Such is the task of assertion dete…
View article: Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration
Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration Open
Outcome prediction from clinical text can prevent doctors from overlooking possible risks and help hospitals to plan capacities. We simulate patients at admission time, when decision support can be especially valuable, and contribute a nov…
View article: VisBERT: Hidden-State Visualizations for Transformers
VisBERT: Hidden-State Visualizations for Transformers Open
Explainability and interpretability are two important concepts, the absence of which can and should impede the application of well-performing neural networks to real-world problems. At the same time, they are difficult to incorporate into …
View article: Learning Contextualized Document Representations for Healthcare Answer Retrieval
Learning Contextualized Document Representations for Healthcare Answer Retrieval Open
We present Contextual Discourse Vectors (CDV), a distributed document\nrepresentation for efficient answer retrieval from long healthcare documents.\nOur approach is based on structured query tuples of entities and aspects from\nfree text …
View article: VisBERT: Hidden-State Visualizations for Transformers
VisBERT: Hidden-State Visualizations for Transformers Open
Explainability and interpretability are two important concepts, the absence of which can and should impede the application of well-performing neural networks to real-world problems. At the same time, they are difficult to incorporate into …
View article: How Does BERT Answer Questions? A Layer-Wise Analysis of Transformer Representations
How Does BERT Answer Questions? A Layer-Wise Analysis of Transformer Representations Open
Bidirectional Encoder Representations from Transformers (BERT) reach state-of-the-art results in a variety of Natural Language Processing tasks. However, understanding of their internal functioning is still insufficient and unsatisfactory.…
View article: Challenges for Toxic Comment Classification: An In-Depth Error Analysis
Challenges for Toxic Comment Classification: An In-Depth Error Analysis Open
Toxic comment classification has become an active research field with many recently proposed approaches. However, while these approaches address some of the task's challenges others still remain unsolved and directions for further research…