Rudolf Kadlec


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.

Hybrid Dialog State Tracker with ASR Features
Miroslav Vodolán | Rudolf Kadlec | Jan Kleindienst
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

This paper presents a hybrid dialog state tracker enhanced by trainable Spoken Language Understanding (SLU) for slot-filling dialog systems. Our architecture is inspired by previously proposed neural-network-based belief-tracking systems. In addition, we extended some parts of our modular architecture with differentiable rules to allow end-to-end training. We hypothesize that these rules allow our tracker to generalize better than pure machine-learning based systems. For evaluation, we used the Dialog State Tracking Challenge (DSTC) 2 dataset - a popular belief tracking testbed with dialogs from restaurant information system. To our knowledge, our hybrid tracker sets a new state-of-the-art result in three out of four categories within the DSTC2.


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)


pdf bib
IBM’s Belief Tracker: Results On Dialog State Tracking Challenge Datasets
Rudolf Kadlec | Jindřich Libovický | Jan Macek | Jan Kleindienst
Proceedings of the EACL 2014 Workshop on Dialogue in Motion