70 citations · 161 across the 21 of their papers we have counts for
5 papers · 2 filters
CLIN-X: pre-trained language models and a study on cross-task transfer for concept extraction in the clinical domain
Lukas Lange, Heike Adel, Jannik Strötgen +1
The field of natural language processing (NLP) has recently seen a large change towards using pre-trained language models for solving almost any task. Despite showing great improve…
Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human Ratings
Hendrik Schuff, Hsiu-Yu Yang, Heike Adel +1
Natural language inference (NLI) requires models to learn and apply commonsense knowledge. These reasoning abilities are particularly important for explainable NLI systems that gen…
Boosting Transformers for Job Expression Extraction and Classification in a Low-Resource Setting
Lukas Lange, Heike Adel, Jannik Strötgen
In this paper, we explore possible improvements of transformer models in a low-resource setting. In particular, we present our approaches to tackle the first two of three subtasks…
Enriched Attention for Robust Relation Extraction
Heike Adel, Jannik Strötgen
The performance of relation extraction models has increased considerably with the rise of neural networks. However, a key issue of neural relation extraction is robustness: the mod…
To Share or not to Share: Predicting Sets of Sources for Model Transfer Learning
Lukas Lange, Jannik Strötgen, Heike Adel +1
In low-resource settings, model transfer can help to overcome a lack of labeled data for many tasks and domains. However, predicting useful transfer sources is a challenging proble…