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Dr. I.A. (Ivan) Titov

Faculteit der Natuurwetenschappen, Wiskunde en Informatica
ILLC

Bezoekadres
  • Science Park 105
  • Kamernummer: F2.03
Postadres
  • Postbus 94242
    1090 GE Amsterdam
Contactgegevens
  • Publicaties

    2020

    2019

    • Bastings, J., Aziz, W., & Titov, I. (2019). Interpretable Neural Predictions with Differentiable Binary Variables. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 2963-2977). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1284 [details]
    • Chen, X., Lyu, C., & Titov, I. (2019). Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 5415–5425). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1544 [details]
    • Corro, C., & Titov, I. (2019). Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder. In ICLR 2019: International Conference on Learning Representations : New Orleans, Louisiana, United States, May 6-May 9, 2019 OpenReview. https://openreview.net/forum?id=BJlgNh0qKQ [details]
    • Corro, C., & Titov, I. (2019). Learning Latent Trees with Stochastic Perturbations and Differentiable Dynamic Programming. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 5508–5521). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1551 [details]
    • De Cao, N., Aziz, W., & Titov, I. (2019). Question answering by reasoning across documents with graph convolutional networks. In J. Burstein, C. Doran, & T. Solorio (Eds.), The 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL HLT 2019 : proceedings of the conference : June 2-June 7, 2019 (Vol. 1, pp. 2306-2317). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/N19-1240 [details]
    • De Cao, N., Ferreira Aziz, W., & Titov, I. A. (2019). Block Neural Autoregressive Flow. In Proceedings of the the 35th Uncertainty in Artificial Intelligence Conference AUAI Press.
    • Le, P., & Titov, I. (2019). Boosting Entity Linking Performance by Leveraging Unlabeled Documents. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 1935-1945). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1187 [details]
    • Le, P., & Titov, I. (2019). Distant Learning for Entity Linking with Automatic Noise Detection. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 4081-4090). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1400 [details]
    • Liu, Y., Titov, I., & Lapata, M. (2019). Single Document Summarization as Tree Induction. In J. Burstein, C. Doran, & T. Solorio (Eds.), The 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL HLT 2019 : proceedings of the conference : June 2-June 7, 2019 (Vol. 1, pp. 1745-1755). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/N19-1173 [details]
    • Lyu, C., Cohen, S. B., & Titov, I. (2019). Semantic Role Labeling with Iterative Structure Refinement. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 1071-1082). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1099 [details]
    • Voita, E., Sennrich, R., & Titov, I. (2019). Context-Aware Monolingual Repair for Neural Machine Translation. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 877-886). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1081 [details]
    • Voita, E., Sennrich, R., & Titov, I. (2019). The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 4396-4406). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1448 [details]
    • Voita, E., Sennrich, R., & Titov, I. (2019). When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 1198-1212). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1116 [details]
    • Voita, E., Talbot, D., Moiseev, F., Sennrich, R., & Titov, I. (2019). Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 5797–5808). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1580 [details]
    • Wang, B., Titov, I., & Lapata, M. (2019). Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 3774-3785). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1391 [details]
    • Zhang, B., Titov, I., & Sennrich, R. (2019). Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 898-909). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1083 [details]

    2018

    • Bražinskas, A., Havrylov, S., & Titov, I. (2018). Embedding Words as Distributions with a Bayesian Skip-gram Model. In E. M. Bender, L. Derczynski, & P. Isabelle (Eds.), The 27th International Conference on Computational Linguistics: COLING 2018 : proceedings of the conference : August 20-26, 2018, Santa Fe, New Mexico, USA (pp. 1775-1789). Association for Computational Linguistics. https://www.aclweb.org/anthology/C18-1151/ [details]
    • Marcheggiani, D., Bastings, J., & Titov, I. (2018). Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks. In M. Walker, H. Ji, & A. Stent (Eds.), NAACL-HLT 2018 : The 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: proceedings of the conference : June 1-June 6, 2018, New Orleans, Louisiana (Vol. 2, pp. 486–492). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/N18-2078 [details]
    • Schlichtkrull, M., Kipf, T. N., Bloem, P., van den Berg, R., Titov, I., & Welling, M. (2018). Modeling Relational Data with Graph Convolutional Networks. In A. Gangemi, R. Navigli, M-E. Vidal, P. Hitzler, R. Troncy, L. Hollink, A. Tordai, & M. Alam (Eds.), The Semantic Web: 15th International Conference, ESWC 2018, Heraklion, Crete, Greece, June 3–7, 2018 : proceedings (pp. 593-607). (Lecture Notes in Computer Science; Vol. 10843). Springer. https://doi.org/10.1007/978-3-319-93417-4_38 [details]

    2017

    • Bastings, J., Titov, I., Aziz, W., Marcheggiani, D., & Sima'an, K. (2017). Graph Convolutional Encoders for Syntax-aware Neural Machine Translation. In M. Palmer, R. Hwa, & S. Riedel (Eds.), Conference on Empirical Methods in Natural Language Processing: emnlp20017 : Copenhagen, Denmark, September 7-11, 2017 : conference proceedings: September 9-11, 2017, Copenhagen, Denmark (pp. 1957-1967). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/D17-1209 [details]

    2016

    • Šuster, S., Titov, I., & van Noord, G. (2016). Bilingual learning of multi-sense embeddings with discrete autoencoders. In K. Knight, A. Nenkova, & O. Rambow (Eds.), NAACL HLT 2016 : The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Proceedings of the Conference : June 12-17, 2016, San Diego, California, USA (pp. 1346-1356). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/N16-1160 [details]

    2015

    • Titov, I., & Khoddam, E. (2015). Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework. In R. Mihalcea, J. Chai, & A. Sarkar (Eds.), NAACL HLT 2015: The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Proceedings of the Conference : May 31-June 5, 2015, Denver, Colorado, USA (pp. 1-10). Stroudsburg, PA: The Association for Computational Linguistics. [details]
    • Zhai, F., Szymanik, J., & Titov, I. (2015). Toward probabilistic natural logic for syllogistic reasoning. In T. Brochhagen, F. Roelofsen, & N. Theiler (Eds.), Proceedings of the 20th Amsterdam Colloquium (pp. 468-477). Institute for Logic, Language and Computation, University of Amsterdam. https://semanticsarchive.net/Archive/mVkOTk2N/AC2015-proceedings.pdf [details]

    2014

    • Frermann, L., Titov, I., & Pinkal, M. (2014). A Hierarchical Bayesian Model for Unsupervised Induction of Script Knowledge. In S. Wintner, S. Goldwater, & S. Riezler (Eds.), EACL 2014: 14th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference: April 26-30, 2014, Gothenburg, Sweden (pp. 49-57). Stroudsburg, PA: Association for Computational Linguistics. [details]
    • Kozhevnikov, M., & Titov, I. (2014). Cross-lingual Model Transfer Using Feature Representation Projection. In K. Toutanova, & H. Wu (Eds.), The 52nd Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : ACL 2014 : June 22-27, Baltimore (Vol. 2, pp. 579-585). Stroudsburg, PA: Association for Computational Linguistics. [details]
    • Li, L., Titov, I., & Sporleder, C. (2014). Improved Estimation of Entropy for Evaluation of Word Sense Induction. Computational Linguistics, 40(3), 671-685. https://doi.org/10.1162/COLI_a_00196 [details]
    • Modi, A., & Titov, I. (2014). Inducing Neural Models of Script Knowledge. In R. Morante, & SW. Yih (Eds.), CoNNL-2014 : Eighteenth Conference on Computational Natural Language Learning: proceedings of the conference : June 26-27, 2014, Baltimore, Maryland, USA (pp. 49-57). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.3115/v1/W14-1606 [details]
    • Modi, A., & Titov, I. (2014). Learning Semantic Script Knowledge with Event Embeddings. In Workshop proceedings: papers accepted to the International Conference on Learning Representations (ICLR) 2014 Ithaca, NY: arXiv.org. [details]

    2013

    • Engonopoulos, N., Villalba, M., Titov, I., & Koller, A. (2013). Predicting the Resolution of Referring Expressions from User Behavior. In D. Yarowsky, T. Baldwin, A. Korhonen, K. Livescu, & S. Bethard (Eds.), EMNLP 2013 : 2013 Conference on Empirical Methods in Natural Language Processing: proceedings of the conference : 18-21 October 2013, Grand Hyatt Seattle, Seattle, Washington, USA (pp. 1354-1359). Stroudsburg, PA: The Association for Computational Linguistics. [details]
    • Henderson, J., Merlo, P., Titov, I., & Musillo, G. (2013). Multilingual Joint Parsing of Syntactic and Semantic Dependencies with a Latent Variable Model. Computational Linguistics, 39(4), 949-998. https://doi.org/10.1162/COLI_a_00158 [details]
    • Kozhevnikov, M., & Titov, I. (2013). Bootstrapping Semantic Role Labelers from Parallel Data. In Second Joint Conference on Lexical and Computational Semantics : *SEM. - Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity : Atlanta, Georgia, June 13-14, 2013 (pp. 317-327). Sroudsburg, PA: Association for Computational Linguistics. [details]
    • Kozhevnikov, M., & Titov, I. (2013). Cross-lingual Transfer of Semantic Role Labeling Models. In P. Fung, & M. Poesio (Eds.), ACL 2013 : 51st Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : August 4-9, 2013, Sofia, Bulgaria (Vol. 1, pp. 1190-1200). Stroudsburg, PA: Association for Computational Linguistics. [details]
    • Lazaridou, A., Titov, I., & Sporleder, C. (2013). A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations. In P. Fung, & M. Poesio (Eds.), ACL 2013 : 51st Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : August 4-9, 2013, Sofia, Bulgaria (Vol. 1, pp. 1630-1639). Stroudsburg, PA: Association for Computational Linguistics. [details]
    • Rohrbach, M., Qiu, W., Titov, I., Thater, S., Pinkal, M., & Schiele, B. (2013). Translating Video Content to Natural Language Descriptions. In 2013 IEEE International Conference on Computer Vision: ICCV 2013 : proceedings: 1-8 December 2013, Sydney, NSW, Australia (pp. 433-440). Los Alamitos, California: IEEE Computer Society. https://doi.org/10.1109/ICCV.2013.61 [details]

    2017

    • Vaquero Patricio, C., Titov, I., & Honing, H. (2017). What score markings can say of the synergy between expressive timing and loudness. Abstract from European Society for Cognitive Sciences Of Music Conference, Ghent, Belgium.

    2016

    • Bražinskas, A., Havrylov, S., & Titov, I. A. (2016). Embedding Words as Distributions with a Bayesian Skip-gram Model. Paper presented at Bayesian Deep Learning Workshop NIPS 2016, Barcelona, Spain.

    2021

    • Schlichtkrull, M. S. (2021). Incorporating structure into neural models for language processing. Institute for Logic, Language and Computation. [details]

    2020

    • Bastings, J. (2020). A tale of two sequences: Interpretable and linguistically-informed deep learning for natural language processing. Institute for Logic, Language and Computation. [details]
    • Kipf, T. N. (2020). Deep learning with graph-structured representations. [details]

    2019

    • Vaquero Patricio, C. (2019). What makes a perfomer unique? Idiosyncrasies and commonalities in expressive music performance. Amsterdam: Institute for Logic, Language and Computation. [details]

    2017

    • Hoàng, C. (2017). Latent domain models for statistical machine translation. [details]
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
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