Search results
Results: 77,485
Number of items: 77,485
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Araabi, A., Niculae, V., & Monz, C. (2023). Joint Dropout: Improving Generalizability in Low-Resource Neural Machine Translation through Phrase Pair Variables. In M. Utiyama, & R. Wang (Eds.), MTS: Machine Translation Summit 2023: September 4-8, 2023, Macau SAR, China : Proceedings of Machine Translation Summit XIX. - Vol. 1: Research Track (pp. 12-25). Asia-Pacific Association for Machine Translation. https://aclanthology.org/2023.mtsummit-research.2 -
Brook, O., Cseres, K. J., & Van Rompuy, B. (2023). Abolishing Formal Complaints? Balancing Technical Expertise and Efficiency with Democratic Accountability in the European Commission’s Decision-Making. Journal of European competition law & practice, 14(8), 497–507. https://doi.org/10.1093/jeclap/lpad056
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Geven, S., & Spörlein, C. (2023). Who benefits from school-to-work linkages in the labour market? A comparison between natives, migrants educated abroad, and those educated domestically . European Sociological Review, 39(3), 418-432. https://doi.org/10.1093/esr/jcac038
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Maric, M., Schumacher, L., Van den Noortgate, W., Bettelli, L., Engelbertink, W., & Stikkelbroek, Y. (2023). A Multilevel Meta-analysis of Single-Case Research on Interventions for Internalizing Disorders in Children and Adolescents. Clinical Child and Family Psychology Review, 26(2), 416-429. https://doi.org/10.1007/s10567-023-00432-9
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van Dijk, J., Figuière, R., Dekker, S. C., van Wezel, A. P., & Cousins, I. T. (2023). Managing PMT/vPvM substances in consumer products through the concepts of essential-use and functional substitution: a case-study for cosmetics. Environmental Science: Processes and Impacts, 25(6), 1067-1081. https://doi.org/10.1039/d3em00025g
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Lunansky, G., Hoekstra, R. H. A., & Blanken, T. F. (2023). Disentangling the Role of Affect in the Evolution of Depressive Complaints Using Complex Dynamical Networks. Collabra: Psychology, 9, Article 74841. https://doi.org/10.1525/collabra.74841
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Yanou, M. P., Ros-Tonen, M. A. F., Reed, J., Moombe, K., & Sunderland, T. (2023). Integrating local and scientific knowledge: The need for decolonising knowledge for conservation and natural resource management. Heliyon, 9(11), Article e21785. https://doi.org/10.1016/j.heliyon.2023.e21785
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Brehmer, J., Cohen, T., De Haan, P., & Lippe, P. (2023). Weakly supervised causal representation learning. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), 36th Conference on Neural Information Processing Systems (NeurIPS 2022): New Orleans, Louisiana, USA, 28 November-9 December 2022 (Vol. 50, pp. 38319-38331). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://doi.org/10.48550/arXiv.2203.16437
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Jumelet, J., Hanna, M., de Heer Kloots, M., Langedijk, A., Pouw, C., & van der Wal, O. (2023). ChapGTP, ILLC’s Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation. In A. Warstadt, A. Mueller, L. Choshen, E. Wilcox, C. Zhuang, J. Ciro, R. Mosquera, B. Paranjabe, A. Williams, T. Linzen, & R. Cotterell (Eds.), Findings of the BabyLM Challenge: Sample-efficient pretraining on developmentally plausible corpora (pp. 74-85). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.conll-babylm.6
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