Aggregation and Ordering in Factorised Databases. - Nurzhan Bakibayev; Tomás Kociský; Dan Olteanu; Jakub Zavodny (Proc. VLDB Endow., 2013)

Learning Bilingual Word Representations by Marginalizing Alignments. - Tomás Kociský; Karl Moritz Hermann; Phil Blunsom (ACL (2), 2014)

Teaching Machines to Read and Comprehend. - Karl Moritz Hermann; Tomás Kociský; Edward Grefenstette; Lasse Espeholt; Will Kay; Mustafa Suleyman; Phil Blunsom (NIPS, 2015)

Latent Predictor Networks for Code Generation. - Wang Ling; Phil Blunsom; Edward Grefenstette; Karl Moritz Hermann; Tomás Kociský; Fumin Wang; Andrew W. Senior (ACL (1), 2016)

Semantic Parsing with Semi-Supervised Sequential Autoencoders. - Tomás Kociský; Gábor Melis; Edward Grefenstette; Chris Dyer; Wang Ling; Phil Blunsom; Karl Moritz Hermann (EMNLP, 2016)

Optimizing Performance of Recurrent Neural Networks on GPUs. - Jeremy Appleyard; Tomás Kociský; Phil Blunsom (CoRR, 2016)

Reasoning about Entailment with Neural Attention. - Tim Rocktäschel; Edward Grefenstette; Karl Moritz Hermann; Tomás Kociský; Phil Blunsom (ICLR (Poster), 2016)

The Neural Noisy Channel. - Lei Yu 008; Phil Blunsom; Chris Dyer; Edward Grefenstette; Tomás Kociský (ICLR (Poster), 2017)

Deep learning for reading and understanding language. - Tomás Kociský (2017)

Pushing the bounds of dropout. - Gábor Melis; Charles Blundell; Tomás Kociský; Karl Moritz Hermann; Chris Dyer; Phil Blunsom (CoRR, 2018)

Encoding Spatial Relations from Natural Language. - Tiago Ramalho; Tomás Kociský; Frederic Besse; S. M. Ali Eslami; Gábor Melis; Fabio Viola; Phil Blunsom; Karl Moritz Hermann (CoRR, 2018)

The NarrativeQA Reading Comprehension Challenge. - Tomás Kociský; Jonathan Schwarz; Phil Blunsom; Chris Dyer; Karl Moritz Hermann; Gábor Melis; Edward Grefenstette (Trans. Assoc. Comput. Linguistics, 2018)

Learning and Evaluating General Linguistic Intelligence. - Dani Yogatama; Cyprien de Masson d'Autume; Jerome T. Connor; Tomás Kociský; Mike Chrzanowski; Lingpeng Kong; Angeliki Lazaridou; Wang Ling; Lei Yu 008; Chris Dyer; Phil Blunsom (CoRR, 2019)

Mogrifier LSTM. - Gábor Melis; Tomás Kociský; Phil Blunsom (ICLR, 2020)

Mind the Gap: Assessing Temporal Generalization in Neural Language Models. - Angeliki Lazaridou; Adhiguna Kuncoro; Elena Gribovskaya; Devang Agrawal; Adam Liska; Tayfun Terzi; Mai Gimenez; Cyprien de Masson d'Autume; Tomás Kociský; Sebastian Ruder; Dani Yogatama; Kris Cao; et al. (NeurIPS, 2021)

Pitfalls of Static Language Modelling. - Angeliki Lazaridou; Adhiguna Kuncoro; Elena Gribovskaya; Devang Agrawal; Adam Liska; Tayfun Terzi; Mai Gimenez; Cyprien de Masson d'Autume; Sebastian Ruder; Dani Yogatama; Kris Cao; Tomás Kociský; et al. (CoRR, 2021)

StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models. - Adam Liska; Tomás Kociský; Elena Gribovskaya; Tayfun Terzi; Eren Sezener; Devang Agrawal; Cyprien de Masson d'Autume; Tim Scholtes; Manzil Zaheer; Susannah Young; Ellen Gilsenan-McMahon; Sophia Austin; et al. (ICML, 2022)

Towards Coherent and Consistent Use of Entities in Narrative Generation. - Pinelopi Papalampidi; Kris Cao; Tomás Kociský (ICML, 2022)