Andreas Rücklé

Name

Andreas Rücklé
Position
Doctoral Researcher
Affiliation
UKP-TUDA
E-Mail
rueckle(at)ukp.informatik.tu-darmstadt.de
Phone
+49 (6151) 16 - 25296
Fax
+49 (6151) 16 - 25295
Office
S2|02 B115
Address

TU Darmstadt - FB 20
Hochschulstraße 10
64289 Darmstadt
Germany

 

Work Information

My research interests include

  • Non-Factoid Question Answering
  • Representation Learning
  • Multilingual NLP

Projects

I am currently involved in the following projects:

Student Supervision

I supervise or have supervised the following students or interns:

  • 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

Additional Attributes

Type

Real-Time News Summarization with Adaptation to Media Attention

Andreas Rücklé, Iryna Gurevych
In: Proceedings of the 11th Conference on Recent Advances in Natural Language Processing (RANLP 2017), p. 610-617, September 2017
Association for Computational Linguistics
[Inproceedings]

Representation Learning for Answer Selection with LSTM-Based Importance Weighting

Andreas Rücklé, Iryna Gurevych
In: Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017), September 2017
Association for Computational Linguistics
[Online-Edition: https://github.com/UKPLab/iwcs2017-answer-selection]
[Inproceedings]

End-to-End Non-Factoid Question Answering with an Interactive Visualization of Neural Attention Weights

Andreas Rücklé, Iryna Gurevych
In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics-System Demonstrations (ACL 2017), Vol. 4: System Demonstrations, p. 19-24, August 2017
Association for Computational Linguistics
[Online-Edition: https://github.com/UKPLab/acl2017-non-factoid-qa]
[Inproceedings]

LSDSem 2017: Exploring Data Generation Methods for the Story Cloze Test

Michael Bugert, Yevgeniy Puzikov, Andreas Rücklé, Judith Eckle-Kohler, Teresa Martin, Eugenio Martínez Cámara, Daniil Sorokin, Maxime Peyrard, Iryna Gurevych
In: Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics (LSDSem, held in conjunction with EACL2017), p. 56-61, April 2017
Association for Computational Linguistics
[Online-Edition: https://github.com/UKPLab/lsdsem2017-story-cloze]
[Inproceedings]
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