70 citations · 96 across the 11 of their papers we have counts for
24 papers · 1 filter
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…
NLNDE at CANTEMIST: Neural Sequence Labeling and Parsing Approaches for Clinical Concept Extraction
Lukas Lange, Xiang Dai, Heike Adel +1
The recognition and normalization of clinical information, such as tumor morphology mentions, is an important, but complex process consisting of multiple subtasks. In this paper, w…
An Analysis of Simple Data Augmentation for Named Entity Recognition
Xiang Dai, Heike Adel
Simple yet effective data augmentation techniques have been proposed for sentence-level and sentence-pair natural language processing tasks. Inspired by these efforts, we design an…