Modeling relational data with graph convolutional networks M Schlichtkrull, TN Kipf, P Bloem, R Van Den Berg, I Titov, M Welling The semantic web: 15th international conference, ESWC 2018, Heraklion, Crete …, 2018 | 5182 | 2018 |
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned E Voita, D Talbot, F Moiseev, R Sennrich, I Titov ACL, 2019 | 1101 | 2019 |
Modeling online reviews with multi-grain topic models I Titov, R McDonald 17th International conference on World Wide Web (WWW), 111-120, 2008 | 1043 | 2008 |
Encoding sentences with graph convolutional networks for semantic role labeling D Marcheggiani, I Titov EMNLP, 2017 | 1002 | 2017 |
A joint model of text and aspect ratings for sentiment summarization I Titov, R McDonald ACL, 308-316, 2008 | 875 | 2008 |
Graph convolutional encoders for syntax-aware neural machine translation J Bastings, I Titov, W Aziz, D Marcheggiani, K Sima'an EMNLP, 2017 | 622 | 2017 |
Translating video content to natural language descriptions M Rohrbach, W Qiu, I Titov, S Thater, M Pinkal, B Schiele ICCV, 433-440, 2013 | 462 | 2013 |
Inducing Crosslingual Distributed Representations of Words A Klementiev, I Titov, B Bhattarai COLING, 2012 | 454 | 2012 |
Context-aware neural machine translation learns anaphora resolution E Voita, P Serdyukov, R Sennrich, I Titov ACL, 2018 | 334 | 2018 |
Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation B Zhang, P Williams, I Titov, R Sennrich ACL 2020, 2020 | 320 | 2020 |
Emergence of language with multi-agent games: Learning to communicate with sequences of symbols S Havrylov, I Titov NeurIPS, 2149-2159, 2017 | 315 | 2017 |
Editing Factual Knowledge in Language Models N De Cao, W Aziz, I Titov EMNLP, 2021 | 297 | 2021 |
Question answering by reasoning across documents with graph convolutional networks N De Cao, W Aziz, I Titov NAACL, 2019 | 279 | 2019 |
Improving entity linking by modeling latent relations between mentions P Le, I Titov ACL, 2018 | 250 | 2018 |
Information-Theoretic Probing with Minimum Description Length E Voita, I Titov EMNLP 2020, 2020 | 246 | 2020 |
Exploiting semantics in neural machine translation with graph convolutional networks D Marcheggiani, J Bastings, I Titov NAACL, 2018 | 241 | 2018 |
When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion E Voita, R Sennrich, I Titov ACL, 2019 | 233 | 2019 |
Interpreting graph neural networks for nlp with differentiable edge masking MS Schlichtkrull, N De Cao, I Titov ICLR 2021, 2020 | 228 | 2020 |
Interpretable Neural Predictions with Differentiable Binary Variables J Bastings, W Aziz, I Titov ACL, 2019 | 228 | 2019 |
The bottom-up evolution of representations in the transformer: A study with machine translation and language modeling objectives E Voita, R Sennrich, I Titov EMNLP 2019, 2019 | 171 | 2019 |