Laplante, S., Lee, T.J., Szegedy, M. (2005) The quantum adversary method and classical formula size lower bounds.

In Proceedings 20th annual conference on computational complexity (pp 76-90). IEEE.

Larooij, M., Kamps, J., Marx, M. (2023) Openbaarheid van bestuur kan vrijwel kosteloos beter.

Economisch-Statistische Berichten, Vol. 108 (pp 36-39)

Article | https://esb.nu/openbaarheid-van-bestuur-kan-vrijwel-kosteloos-beter/ | UvA-DARE

Laurent, M., Piovesan, T. (2015) Conic approach to quantum graph parameters using linear optimization over the completely positive semidefinite cone.

SIAM Journal on Optimization, Vol. 25 (pp 2461-2493)

Article | https://doi.org/10.1137/14097865X | UvA-DARE

Lauridsen, F.M., Ilin, J., Bezhanishvili, G., Harding, J. (2018) MacNeille transferability for finite lattices.

In Proceedings of the conference Logic, Algebra and Truth Degrees (pp 24-26). University of Bern.

Lauridsen, F.M. (2017) Intermediate logics admitting structural hypersequent calculi.

Abstract | http://www.cs.cas.cz/tacl2017/abstracts/TACL_2017_paper_53.pdf | UvA-DARE

Lauridsen, F.M. (2019) Cuts and completions: Algebraic aspects of structural proof theory.

Thesis, fully internal | UvA-DARE

Lauridsen, F.M. (2019) Intermediate logics admitting a structural hypersequent calculus.

Studia Logica, Vol. 107 (pp 247–282)

Article | https://doi.org/10.1007/s11225-018-9791-y | UvA-DARE

Lavi, Dor, Medentsiy, V., Graus, David (2021) conSultantBERT: Fine-tuned siamese sentence-BERT for matching jobs and job seekers.

In Kaya, Mesut Bogers, Toine Graus, David Verbert, Katrien Gutiérrez, Francisco (Eds.), The Workshop on Recommender Systems for Human Resources (RecSys in HR 2021) (CEUR Workshop Proceedings, Vol. 2967)

Lazaridou, A., Chrupała, G., Fernández, R., Baroni, M. (2016) Multimodal Semantic Learning from Child-Directed Input.

In Knight, K. Nenkova, A. Rambow, O. (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 387-392). The Association for Computational Linguistics.

Lazaridou, A., Titov, I., Sporleder, C. (2013) A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations.

In Fung, P. Poesio, M. (Eds.), ACL 2013 : 51st Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : August 4-9, 2013, Sofia, Bulgaria (pp 1630-1639). Association for Computational Linguistics.

Lazzari, G., Colavizza, G., Bortoluzzi, F., Drago, D., Erboso, A., Zugno, F., Kaplan, F., Salathé, M. (2020) A digital reconstruction of the 1630–1631 large plague outbreak in Venice.

Scientific Reports, Vol. 10

Article | https://doi.org/10.1038/s41598-020-74775-6 | UvA-DARE

Le, P., Titov, I. (2017) Optimizing differentiable relaxations of coreference evaluation metrics.

In Levy, R. Specia, L. (Eds.), The 21st Conference on Computational Natural Language Learning: Proceedings of the Conference : CoNNL 2017 : August 2-august 4, 2017, Vancouver, Canada (pp 390-399). Association for Computational Linguistics.

Le, P., Titov, I. (2018) Improving entity linking by modeling latent relations between mentions.

In Gurevych, I. Miyao, Y. (Eds.), ACL 2018 : The 56th Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : July 15-20, 2018, Melbourne, Australia (pp 1595-1604). The Association for Computational Linguistics.

Le, P., Titov, I. (2019) Distant Learning for Entity Linking with Automatic Noise Detection.

In Korhonen, A. Traum, D. Màrquez, L. (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). The Association for Computational Linguistics.

Le, P., Titov, I. (2019) Boosting Entity Linking Performance by Leveraging Unlabeled Documents.

In Korhonen, A. Traum, D. Màrquez, L. (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). The Association for Computational Linguistics.

Le, P., Zuidema, W., Scha, R. (2013) Learning from errors: Using vector-based compositional semantics for parse reranking.

In Allauzen, A. Larochelle, H. Manning, C. Socher, R. (Eds.), 51st Annual Meeting of the Association for Computational Linguistics : ACL 2013 : Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality: August 9, 2013, Sofia, Bulgaria (pp 11-19). The Association for Computational Linguistics.

Le, P., Zuidema, W. (2012) Learning compositional semantics for open domain semantic parsing.

In Kay, M. Boitet, C. (Eds.), 24th International Conference on Computational Linguistics: proceedings of COLING 2012: technical papers: 8-15 December 2012, Mumbai, India (pp 1535-1551). Indian Institute of Technology Bombay.

Le, P., Zuidema, W. (2014) The Inside-Outside Recursive Neural Network model for Dependency Parsing.

In Moschitti, A. Pang, B. Daelemans, W. (Eds.), EMNLP 2014: the 2014 Conference on Empirical Methods in Natural Language Processing: proceedings of the conference: October 25-29, 2014, Doha, Qatar (pp 729-739). Association for Computational Linguistics.

Le, P., Zuidema, W. (2014) Inside-Outside Semantics: A Framework for Neural Models of Semantic Composition.

Paper | UvA-DARE

Le, P., Zuidema, W. (2015) The Forest Convolutional Network: Compositional Distributional Semantics with a Neural Chart and without Binarization.

In Márquez, L. Callison-Burch, C. Su, J. (Eds.), EMNLP 2015 Lisbon : conference proceedings: September 17-21 : Conference on Empirical Methods in Natural Language Processing (pp 1155-1164). The Association for Computational Linguistics.