Welbl, J. (2020). Training Datasets for Machine Reading Comprehension and Their Limitations (Doctoral dissertation). UCL (University College London).

Welbl, J., Saito Stenetorp, P. L. E. P. S., & Riedel, S. (2018). Constructing Datasets for Multi-hop Reading Comprehension Across Documents. Transactions of the Association for Computational Linguistics. doi:10.1162/tacl_a_00021

Weissenborn, D., Minervini, P., Augenstein, I., Welbl, J., Rocktäschel, T., Bosnjak, M., . . . Riedel, S. (2018). Jack the Reader - A Machine Reading Framework. Proceedings of ACL 2018, Melbourne, Australia, July 15-20, 2018, System Demonstrations, 25-30.

Daniluk, M., Rocktäschel, T., Welbl, J., & Riedel, S. (2017). Frustratingly Short Attention Spans in Neural Language Modeling. International Conference on Learning Representations (ICLR).

Trouillon, T., Dance, C. R., Welbl, J., Riedel, S., Gaussier, É., & Bouchard, G. (2017). Knowledge Graph Completion via Complex Tensor Factorization. Journal of Machine Learning Research, 18 (130), 1-38.

Trouillon, T., Welbl, J., Riedel, S., Ciaussier, E., & Bouchard, G. (2016). Complex embeddings for simple link prediction. 33rd International Conference on Machine Learning, ICML 2016, 5, 3021-3032.