Andreas Rücklé

Andreas Rücklé, M.Sc.

Doctoral researcher

+49 6151 16-25296
+49 6151 16-25295

Hochschulstraße 10
64289 Darmstadt

Office: S2|02 B115

Research interests

  • Automatic Question Answering
  • Representation Learning
  • Multilingual NLP

Projects

I am currently involved in the following projects:

Awards and grants

Teaching

Student supervision

I supervise or have supervised the following students or interns:

  • Martin Lichtblau (2019, master thesis)
  • Jana Vatter (2018, bachelor thesis)
  • Krishnkant Swarnkar (2018, internship)
  • Johann Wiedmeier (2017, master thesis). Enhanced Representation Learning for Question Retrieval with Transfer Learning.
  • Paul Dubs (2016/2017, master thesis). Large-Scale Semantic Question Retrieval in Community Question Answering.
  • Nadja Geisler (2016/2017, bachelor thesis): Enhancing Complex Question Answering with Rule-Based Question Understanding
  • Vu Xuan Son (2016, internship)
  • Omnia Zayed (2016, internship)

Biographical information

I hold a Master of Science in computer science from Technische Universität Darmstadt.

Publications

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Gruppiere nach: Publikationsjahr | Typ des Eintrags | Keine Gruppierung
Springe zu: 2019 | 2018 | 2017 | 2015
Anzahl der Einträge: 12.

2019

Rücklé, Andreas ; Moosavi, Nafise Sadat ; Gurevych, Iryna (2019):
Neural Duplicate Question Detection without Labeled Training Data.
In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing, Stroudsburg, PA, USA, Association for Computational Linguistics, In: The 2018 Conference on Empirical Methods in Natural Language Processing, Hong Kong, China, 03.11.2019-07.11.2019, [Konferenzveröffentlichung]

Eger, Steffen ; Rücklé, Andreas ; Gurevych, Iryna (2019):
Pitfalls in the Evaluation of Sentence Embeddings.
In: The 4th Workshop on Representation Learning for NLP (Repl4NLP 2019), Florence, Italy, 2 August 2019, [Online-Edition: https://arxiv.org/abs/1906.01575],
[Konferenzveröffentlichung]

Rücklé, Andreas ; Swarnkar, Krishnkant ; Gurevych, Iryna (2019):
Improved Cross-Lingual Question Retrieval for Community Question Answering.
In: Proceedings of The Web Conference (WWW-19), San Francisco, USA, San Francisco, USA, [Online-Edition: https://dl.acm.org/citation.cfm?id=3313502],
[Konferenzveröffentlichung]

Eger, Steffen ; Şahin, Gözde Gül ; Rücklé, Andreas ; Lee, Ji-Ung ; Schulz, Claudia ; Mesgar, Mohsen ; Swarnkar, Krishnkant ; Simpson, Edwin ; Gurevych, Iryna (2019):
Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems.
In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics, In: The 2019 Conference of the North American Chapter of the Association for Computational Linguistics, Minneapolis, USA, 02.06.2019--07.10.2019, [Konferenzveröffentlichung]

Rücklé, Andreas ; Moosavi, Nafise Sadat ; Gurevych, Iryna (2019):
COALA: A Neural Coverage-Based Approach for Long Answer Selection with Small Data.
In: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, USA, In: Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, USA, DOI: 10.1609/aaai.v33i01.33016932,
[Online-Edition: https://aaai.org/ojs/index.php/AAAI/article/view/4671/4549],
[Konferenzveröffentlichung]

2018

Eger, Steffen ; Rücklé, Andreas ; Gurevych, Iryna (2018):
PD3: Better Low-Resource Cross-Lingual Transfer By Combining Direct Transfer and Annotation Projection.
In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, In: 5th Workshop on Argument Mining, Brussels, Belgium, 31.10.2018, [Online-Edition: https://fileserver.ukp.informatik.tu-darmstadt.de/UKP_Webpag...],
[Konferenzveröffentlichung]

Rücklé, Andreas ; Eger, Steffen ; Peyrard, Maxime ; Gurevych, Iryna (2018):
Concatenated Power Mean Word Embeddings as Universal Cross-Lingual Sentence Representations.
In: arXiv:1803.01400, [Online-Edition: https://arxiv.org/abs/1803.01400],
[Artikel]

2017

Rücklé, Andreas ; Gurevych, Iryna (2017):
Real-Time News Summarization with Adaptation to Media Attention.
In: Proceedings of the 11th Conference on Recent Advances in Natural Language Processing (RANLP 2017), Association for Computational Linguistics, Varna, Bulgaria, DOI: 10.26615/978-954-452-049-6_079,
[Online-Edition: https://doi.org/10.26615/978-954-452-049-6_079],
[Konferenzveröffentlichung]

Rücklé, Andreas ; Gurevych, Iryna (2017):
Representation Learning for Answer Selection with LSTM-Based Importance Weighting.
In: Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017), Association for Computational Linguistics, Montpellier, France, Volume 2: Short papers, [Online-Edition: http://aclweb.org/anthology/W17-6935],
[Konferenzveröffentlichung]

Rücklé, Andreas ; Gurevych, Iryna (2017):
End-to-End Non-Factoid Question Answering with an Interactive Visualization of Neural Attention Weights.
In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics-System Demonstrations (ACL 2017), Association for Computational Linguistics, Vancouver, Canada, 4: System Demonstrations, [Online-Edition: http://aclweb.org/anthology/P17-4004],
[Konferenzveröffentlichung]

Bugert, Michael ; Puzikov, Yevgeniy ; Rücklé, Andreas ; Eckle-Kohler, Judith ; Martin, Teresa ; Martínez Cámara, Eugenio ; Sorokin, Daniil ; Peyrard, Maxime ; Gurevych, Iryna (2017):
LSDSem 2017: Exploring Data Generation Methods for the Story Cloze Test.
In: Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics, Association for Computational Linguistics, In: The 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics, Valencia, Spain, 03.04.2017--04.04.2017, ISBN 978-1-945626-40-1,
[Online-Edition: http://aclweb.org/anthology/W17-0908],
[Konferenzveröffentlichung]

2015

Rücklé, Andreas (2015):
Real-Time Summarization of Big Data Streams.
Technische Universität Darmstadt, [Online-Edition: https://download.hrz.tu-darmstadt.de/media/FB20/Dekanat/Publ...],
[Masterarbeit]

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