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Liao, B., Tan, S., & Monz, C. (2023). Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning. In Thirty-seventh Annual Conference on Neural Information Processing Systems OpenReview. https://openreview.net/forum?id=J8McuwS3zY -
Rodríguez, A., de Vries, F. T., Manning, P., Sebastià, M. T., & Bardgett, R. D. (2023). Soil Abiotic Properties Shape Plant Functional Diversity Across Temperate Grassland Plant Communities. Ecosystems, 26(5), 1000–1017. https://doi.org/10.1007/s10021-022-00812-2 -
Muldoon, J., & Raekstad, P. (2023). Algorithmic domination in the gig economy. European Journal of Political Theory, 22(4), 587-607. https://doi.org/10.1177/14748851221082078 -
Avanzi, R., Banik, S., Dunkelman, O., Eichlseder, M., Ghosh, S., Nageler, M., & Regazzoni, F. (2023). The QARMAv2 Family of Tweakable Block Ciphers. IACR Transactions on Symmetric Cryptology, 2023(3), 25-73. https://doi.org/10.46586/tosc.v2023.i3.25-73 -
Bénédict, G., Zhang, R., Metzler, D., Yates, A., Deffayet, R., Hager, P., & Jullien, S. (2023). Report on the 1st Workshop on Generative Information Retrieval (Gen-IR 2023) at SIGIR 2023. SIGIR Forum, 57(2), Article 13. https://doi.org/10.1145/3642979.3642995 -
Lange, K., Dominik, C., & Tielens, A. G. G. M. (2023). Turbulent processing of PAHs in protoplanetary discs: Coagulation and freeze-out leading to depletion of gas-phase PAHs. Astronomy & Astrophysics, 674, Article A200. https://doi.org/10.1051/0004-6361/202245108
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