Titov, Ivan

Modeling Relational Data with Graph Convolutional Networks

Schlichtkrull, M., Kipf, T. N., Bloem, P., van den Berg, R., Titov, I., & Welling, M. (2018) · Lecture Notes in Computer Science

Advanced Graph Neural NetworksTopic Modeling

Cited by 5,570

Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned

Voita, E., Talbot, D., Moiseev, F., Sennrich, R., & Titov, I. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 1,146

Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling

Marcheggiani, D., & Titov, I. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 907

Information-Theoretic Probing with Minimum Description Length

Voita, E., & Titov, I. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 251

Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols

Havrylov, S., & Titov, I. (2017) · arXiv

Reinforcement Learning in RoboticsLanguage and cultural evolution

Cited by 195

Editing Factual Knowledge in Language Models

De Cao, N., Aziz, W., & Titov, I. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 180

Graph Convolutional Encoders for Syntax-aware Neural Machine Translation

Bastings, J., Titov, I., Aziz, W., Marcheggiani, D., & Simaan, K. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 97

How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking

De Cao, N., Schlichtkrull, M. S., Aziz, W., & Titov, I. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 75

Question answering by reasoning across documents with graph convolutional networks

De Cao, N., Aziz, W., & Titov, I. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

Topic ModelingAdvanced Graph Neural Networks

Cited by 54

The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives

Voita, E., Sennrich, R., & Titov, I. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 17

Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models

Qiu, Z., Huang, Z., Zheng, B., Wen, K., Wang, Z., Men, R., Titov, I., Liu, D., Zhou, J., & Lin, J. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 10

Cache & Distil: Optimising API Calls to Large Language Models

Ramírez, G., Lindemann, M., Birch, A., & Titov, I. (2023) · arXiv

Machine Learning and AlgorithmsDomain Adaptation and Few-Shot Learning

Cited by 4

Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models

Qiu, Z., Huang, Z., Zheng, B., Wen, K., Wang, Z., Men, R., Titov, I., Liu, D., Zhou, J., & Lin, J. (2025) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 0