Ondřej Bajgar

Also published as: Ondrej Bajgar


pdf bib
Knowledge Base Completion: Baselines Strike Back
Rudolf Kadlec | Ondrej Bajgar | Jan Kleindienst
Proceedings of the 2nd Workshop on Representation Learning for NLP

Many papers have been published on the knowledge base completion task in the past few years. Most of these introduce novel architectures for relation learning that are evaluated on standard datasets like FB15k and WN18. This paper shows that the accuracy of almost all models published on the FB15k can be outperformed by an appropriately tuned baseline — our reimplementation of the DistMult model. Our findings cast doubt on the claim that the performance improvements of recent models are due to architectural changes as opposed to hyper-parameter tuning or different training objectives. This should prompt future research to re-consider how the performance of models is evaluated and reported.


pdf bib
Text Understanding with the Attention Sum Reader Network
Rudolf Kadlec | Martin Schmid | Ondrej Bajgar | Jan Kleindienst
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)