Dr. Ing. Nils Reimers

Postdoctoral researcher

Contact

work +49 6151 16-25296
fax +49 6151 16-25295

Work S2|02 B115
Hochschulstraße 10
64289 Darmstadt

Links

  • Event and Temporal Relation Extraction
    Millions of news articles are published every day. Finding, extracting and structuring the important information in an efficient way is a crucial task in many domains, for example in algorithmic trading. I do research on the automatic event and relation extraction on news articles. Each event is characterized by the involved entities, by a connecting property like a certain action, and a temporal information.Subsequently, temporal and causal relations are extracted for those events.
  • Deep Learning
    For my research, I apply various super- and semi-supervised machine learning techniques for the event and relation detection. A special research focus lies on deep learning, which allows to model high-level abstraction of data. I use and extend deep learning techniques in order to extract events and relations within documents and across documents.

Currently I work in two projects:

  • DARIAH DE-II: I'm involved in the development of quantitative methods to detect the evolution of narrative techniques in (German) novels over the past centuries.
  • Structuring Story-Chains: As thousands of news articles are published daily, it is challenging to stay up-to-date on every topic. The goal of the project is to help readers to tackle the information-overload. This is done by extracting and analyzing the causal connections between articles. The results are useful for various tasks, e.g. to get a quicker overview on a certain topic.
  • I participated in the Event Nugget Detection and Classification task at TAC 2015. The created deep neural network scored a F1-measure of 65.31% and is placed first among 14 systems.
  • I participated in the German Named Entity Recognition task at KONVENS 2014. The created state-of-the-art deep neural network scored a F1-measure of 75.1% and is placed 2nd among 11 systems.
  • 11/2017: Seminar Deep Learning for NLP at the University of Duisburg-Essen
  • WS 2015/2016: Deep Learning for NLP
  • WS 2014/2015: Foundations of Language Technology / Grundlagen Intelligenter Systeme

I'm supervising Bachelor- and Master-theses in the field of Natural Language Processing in combination with Machine Learning. In case you like to write a thesis in the following fields, feel free to approach me:

  • Structuring Story-Chains: You are interested to analyze thousands of news articles and creating an intelligent system, supporting either readers or editors of news websites? This project has the opportunity for various types of theses: Reading recommendation systems, visualization of large datasets & graphs, information extraction from news articles, link discovery, as well as human-machine-interaction.
  • The Deep Learning Revolution: Deep Learning uses deep neural networks to achieve state-of-the-art results in all domains of machine learning. In my research I investigate different deep learning approach and apply them to text data. In case you are interested to write a thesis in this field, feel free to approach me.

I have supervised the following theses:

  • Philip Beyer. Proposal for a STS Evaluation Framework for STS based Applications. Student Research Paper (Studienarbeit). Computer Science Department. Technical University of Darmstadt. Published at Coling 2016.
  • Ziyang Li. Related Articles Discovery in Large Corpora (Masterthesis). Computer Science Department. Technical University of Darmstadt.
  • Michael Bräunlein. Multi-Document High Precision Event Extraction (Masterthesis). Computer Science Department. Technical University of Darmstadt.

I hold a M.Sc. (Master of Science) in IT-Security from the Technical University of Darmstadt, a B.Sc. (Bachelor of Science) in Computer Science, and a B.Sc. in Mathematics from the University of Oldenburg.

Jump to: 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013
Number of items: 19.

2021

Thakur, Nandan and Reimers, Nils and Daxenberger, Johannes and Gurevych, Iryna (2021):
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks.
2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics, virtual Conference, 06.-11.06.2021, [Conference or Workshop Item]

2020

Reimers, Nils and Gurevych, Iryna (2020):
Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation.
pp. 4512-4525, Association for Computational Linguistics, The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), virtual Conference, 16.-20.11., [Conference or Workshop Item]

Bugert, Michael and Reimers, Nils and Barhom, Shany and Dagan, Ido and Gurevych, Iryna (2020):
Breaking the Subtopic Barrier in Cross-Document Event Coreference Resolution.
Text2Story@ECIR'20 - 3rd International Workshop on Narrative Extraction from Texts, Lisbon, Portugal, 14.04.2020, [Conference or Workshop Item]

2019

Reimers, Nils and Gurevych, Iryna (2019):
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.
pp. 3973-3983, The 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019), Hong Kong, China, 03.12.2019-07.12.2019, [Conference or Workshop Item]

Reimers, Nils and Schiller, Benjamin and Beck, Tilman and Daxenberger, Johannes and Stab, Christian and Gurevych, Iryna (2019):
Classification and Clustering of Arguments with Contextualized Word Embeddings.
pp. 567-578, The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), Florence, Italy, 28.07.2019-02.08.2019, [Conference or Workshop Item]

Barhom, Shany and Shwartz, Vered and Eirew, Alon and Bugert, Michael and Reimers, Nils and Dagan, Ido (2019):
Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution.
pp. 4179-4189, The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), Florence, Italy, 28.07.2019-02.08.2019, [Conference or Workshop Item]

Reimers, Nils and Gurevych, Iryna (2019):
Alternative Weighting Schemes for ELMo Embeddings.
In: CoRR, abs/1904.02954, [Article]

2018

Reimers, Nils and Gurevych, Iryna (2018):
Why Comparing Single Performance Scores Does Not Allow to Draw Conclusions About Machine Learning Approach.
In: arXiv:1803.09578, [Article]

Reimers, Nils and Dehghani, Nazanin and Gurevych, Iryna (2018):
Event Time Extraction with a Decision Tree of Neural Classifiers.
In: Transactions of the Association for Computational Linguistics, 6, pp. 77-89. ISSN 2307-387X,
[Article]

2017

Reimers, Nils and Gurevych, Iryna (2017):
Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging.
In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 338-348,
Copenhagen, Denmark, [Conference or Workshop Item]

Reimers, Nils and Gurevych, Iryna (2017):
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks.
In: arXiv preprint arXiv:1707.06799, [Article]

2016

Reimers, Nils and Beyer, Philip and Gurevych, Iryna (2016):
Task-Oriented Intrinsic Evaluation of Semantic Textual Similarity.
In: Proceedings of the 26th International Conference on Computational Linguistics (COLING), pp. 87-96,
Osaka, Japan, [Conference or Workshop Item]

Reimers, Nils and Dehghani, Nazanin and Gurevych, Iryna (2016):
Temporal Anchoring of Events for the TimeBank Corpus.
Volume 1: Long Papers, In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL 2016), pp. 2195-2204,
Association for Computational Linguistics, Berlin, Germany, [Conference or Workshop Item]

Reimers, Nils and Jannidis, Fotis and Pielström, Steffen and Pernes, Stefan and Reger, Isabella (2016):
A Tool for NLP-Preprocessing in Literary Text Analysis.
Leipzig, Germany, [Conference or Workshop Item]

Jannidis, Fotis and Pernes, Stefan and Pielström, Steffen and Reger, Isabella and Reimers, Nils and Vitt, Thorsten (2016):
DARIAH-DKPro-Wrapper Output Format (DOF) Specification.
(20), [Report]

2015

Reimers, Nils and Gurevych, Iryna (2015):
Event Nugget Detection, Classification and Coreference Resolution using Deep Neural Networks and Gradient Boosted Decision Trees.
In: Proceedings of the Eighth Text Analysis Conference (TAC 2015),
National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA, [Conference or Workshop Item]

2014

Reimers, Nils and Eckle-Kohler, Judith and Schnober, Carsten and Kim, Jungi and Gurevych, Iryna Faaß, Gertrud and Ruppenhofer, Josef (eds.) (2014):
GermEval-2014: Nested Named Entity Recognition with Neural Networks.
In: Workshop Proceedings of the 12th Edition of the KONVENS Conference, pp. 117-120,
Universitätsverlag Hildesheim, Hildesheim, Germany, [Conference or Workshop Item]

2013

Deiseroth, B. and Fehr, Victoria and Fischlin, Marc and Maasz, M. and Reimers, Nils and Stein, R. (2013):
Computing on Authenticated Data for Adjustable Predicates.
In: Lecture Notes in Computer Science, 7954, pp. 53-68. [Article]

Steinebach, M. and Klöckner, P. and Reimers, Nils and Wienand, D. and Wolf, Patrick (2013):
Robust Hash Algorithms for Text.
In: Lecture Notes in Computer Science, In: Proceeding of 14th Joint IFIP TC6 and TC11 Conference on Communications and Multimedia Security -- CMS'2013, September 25-26, 2013, Magdeburg, Germany,
[Conference or Workshop Item]

This list was generated on Mon Apr 12 04:49:45 2021 CEST.