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## Specialized Document Embeddings for Aspect-based Similarity of Research Papers

Document embeddings and similarity measures underpin content-based recommender systems, whereby a document is commonly represented as a single generic embedding. However, similarity computed on single vector representations provides only one …

## HiStruct+: Improving Extractive Text Summarization with Hierarchical Structure Information

Transformer-based language models usually treat texts as linear sequences. However, most texts also have an inherent hierarchical structure, i.e., parts of a text can be identified using their position in this hierarchy. In addition, section titles …

## Perceptual Quality Dimensions of Machine-Generated Text with a Focus on Machine Translation

The quality of machine-generated text is a complex construct consisting of various aspects and dimensions. We present a study that aims to uncover relevant perceptual quality dimensions for one type of machine-generated text, that is, Machine …

## A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition

Pre-trained language models (PLM) are effective components of few-shot named entity recognition (NER) approaches when augmented with continued pre-training on task-specific out-of-domain data or fine-tuning on in-domain data. However, their …

## Why only Micro-$F_1$? Class Weighting of Measures for Relation Classification

Relation classification models are conventionally evaluated using only a single measure, e.g., micro-F1, macro-F1 or AUC. In this work, we analyze weighting schemes, such as micro and macro, for imbalanced datasets. We introduce a framework for …

## Detecting Covariate Drift with Explanations

Detecting when there is a domain drift between training and inference data is important for any model evaluated on data collected in real time. Many current data drift detection methods only utilize input features to detect domain drift. While …

## MobIE: A German Dataset for Named Entity Recognition, Entity Linking and Relation Extraction in the Mobility Domain

We present MobIE, a German-language dataset, which is human-annotated with 20 coarse- and fine-grained entity types and entity linking information for geographically linkable entities. The dataset consists of 3,232 social media texts and traffic …

## Evaluating Document Representations for Content-based Legal Literature Recommendations

Recommender systems assist legal professionals in finding relevant literature for supporting their case. Despite its importance for the profession, legal applications do not reflect the latest advances in recommender systems and representation …

## Aspect-based Document Similarity for Research Papers

Traditional document similarity measures provide a coarse-grained distinction between similar and dissimilar documents. Typically, they do not consider in what aspects two documents are similar. This limits the granularity of applications like …

## Defx at SemEval-2020 Task 6: Joint Extraction of Concepts and Relations for Definition Extraction

We describe our submissions to the DeftEval shared task (SemEval-2020 Task 6)