166 citations · 293 across the 18 of their papers we have counts for
18 papers
Multilingual Extraction and Recognition of Implicit Discourse Relations in Speech and Text
Ahmed Ruby, Christian Hardmeier, Sara Stymne
Implicit discourse relation classification is a challenging task, as it requires inferring meaning from context. While contextual cues can be distributed across modalities and vary…
Mention Attention for Pronoun Translation
Gongbo Tang, Christian Hardmeier
Most pronouns are referring expressions, computers need to resolve what do the pronouns refer to, and there are divergences on pronoun usage across languages. Thus, dealing with th…
A Dataset for the Detection of Dehumanizing Language
Paul Engelmann, Peter Brunsgaard Trolle, Christian Hardmeier
Dehumanization is a mental process that enables the exclusion and ill treatment of a group of people. In this paper, we present two data sets of dehumanizing text, a large, automat…
Parallel Data Helps Neural Entity Coreference Resolution
Gongbo Tang, Christian Hardmeier
Coreference resolution is the task of finding expressions that refer to the same entity in a text. Coreference models are generally trained on monolingual annotated data but annota…
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity
Dennis Ulmer, Jes Frellsen, Christian Hardmeier
We investigate the problem of determining the predictive confidence (or, conversely, uncertainty) of a neural classifier through the lens of low-resource languages. By training mod…
deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks
Dennis Ulmer, Christian Hardmeier, Jes Frellsen
A lot of Machine Learning (ML) and Deep Learning (DL) research is of an empirical nature. Nevertheless, statistical significance testing (SST) is still not widely used. This endang…
Experimental Standards for Deep Learning in Natural Language Processing Research
Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein +5
The field of Deep Learning (DL) has undergone explosive growth during the last decade, with a substantial impact on Natural Language Processing (NLP) as well. Yet, compared to more…
Unsupervised Discovery of Unaccusative and Unergative Verbs
Sharid Loáiciga, Luca Bevacqua, Christian Hardmeier
We present an unsupervised method to detect English unergative and unaccusative verbs. These categories allow us to identify verbs participating in the causative-inchoative alterna…
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation
Dennis Ulmer, Christian Hardmeier, Jes Frellsen
Popular approaches for quantifying predictive uncertainty in deep neural networks often involve distributions over weights or multiple models, for instance via Markov Chain samplin…
How to Write a Bias Statement: Recommendations for Submissions to the Workshop on Gender Bias in NLP
Christian Hardmeier, Marta R. Costa-jussà, Kellie Webster +2
At the Workshop on Gender Bias in NLP (GeBNLP), we'd like to encourage authors to give explicit consideration to the wider aspects of bias and its social implications. For the 2020…
Principal Word Vectors
Ali Basirat, Christian Hardmeier, Joakim Nivre
We generalize principal component analysis for embedding words into a vector space. The generalization is made in two major levels. The first is to generalize the concept of the co…
Findings of the 2016 WMT Shared Task on Cross-lingual Pronoun Prediction
Liane Guillou, Christian Hardmeier, Preslav Nakov +6
We describe the design, the evaluation setup, and the results of the 2016 WMT shared task on cross-lingual pronoun prediction. This is a classification task in which participants a…
Getting Gender Right in Neural Machine Translation
Eva Vanmassenhove, Christian Hardmeier, Andy Way
Speakers of different languages must attend to and encode strikingly different aspects of the world in order to use their language correctly (Sapir, 1921; Slobin, 1996). One such d…
Pronoun Translation in English-French Machine Translation: An Analysis of Error Types
Christian Hardmeier, Liane Guillou
Pronouns are a long-standing challenge in machine translation. We present a study of the performance of a range of rule-based, statistical and neural MT systems on pronoun translat…
Automatic Reference-Based Evaluation of Pronoun Translation Misses the Point
Liane Guillou, Christian Hardmeier
We compare the performance of the APT and AutoPRF metrics for pronoun translation against a manually annotated dataset comprising human judgements as to the correctness of translat…
Universal Word Segmentation: Implementation and Interpretation
Yan Shao, Christian Hardmeier, Joakim Nivre
Word segmentation is a low-level NLP task that is non-trivial for a considerable number of languages. In this paper, we present a sequence tagging framework and apply it to word se…
Character-based Joint Segmentation and POS Tagging for Chinese using Bidirectional RNN-CRF
Yan Shao, Christian Hardmeier, Jörg Tiedemann +1
We present a character-based model for joint segmentation and POS tagging for Chinese. The bidirectional RNN-CRF architecture for general sequence tagging is adapted and applied wi…
Learning Structural Kernels for Natural Language Processing
Daniel Beck, Trevor Cohn, Christian Hardmeier +1
Structural kernels are a flexible learning paradigm that has been widely used in Natural Language Processing. However, the problem of model selection in kernel-based methods is usu…