CB$^2$O: Consensus-Based Bi-Level Optimization

Autor: Trillos, Nicolás García, Li, Sixu, Riedl, Konstantin, Zhu, Yuhua

Bi-level optimization problems, where one wishes to find the global minimizer of an upper-level objective function over the globally optimal solution set of a lower-level objective, arise in a variety of scenarios throughout science and engineering,

Externí odkaz: http://arxiv.org/abs/2411.13394

When Randomness Beats Redundancy: Insights into the Diffusion of Complex Contagions

Autor: Wan, Allison, Riedl, Christoph, Lazer, David

How does social network structure amplify or stifle behavior diffusion? Existing theory suggests that when social reinforcement makes the adoption of behavior more likely, it should spread more -- both farther and faster -- on clustered networks with

Externí odkaz: http://arxiv.org/abs/2411.07907

Multiplicities of positive and negative pions, kaons and unidentified hadrons from deep-inelastic scattering of muons off a liquid hydrogen target

Autor: Alexeev, G. D., Alexeev, M. G., Alice, C., Amoroso, A., Andrieux, V., Anosov, V., Augsten, K., Augustyniak, W., Azevedo, C. D. R., Badelek, B., Barth, J., Beck, R., Beckers, J., Bedfer, Y., Bernhard, J., Bodlak, M., Bradamante, F., Bressan, A., Chang, W. -C., Chatterjee, C., Chiosso, M., Chung, S. -U., Cicuttin, A., Correia, P. M. M., Crespo, M. L., D'Ago, D., Torre, S. Dalla, Dasgupta, S. S., Dasgupta, S., Delcarro, F., Denisenko, I., Denisov, O. Yu., Donskov, S. V., Doshita, N., Dreisbach, Ch., Dünnweber, W., Dusaev, R. R., Ecker, D., Eremeev, D., Faccioli, P., Faessler, M., Finger, M., Finger jr., M., Fischer, H., Flöthner, K. J., Florian, W., Friedrich, J. M., Frolov, V., Ordòñez, L. G. Garcia, Gavrichtchouk, O. P., Gerassimov, S., Giarra, J., Giordano, D., Grasso, A., Gridin, A., Perdekamp, M. Grosse, Grube, B., Grüner, M., Guskov, A., Haas, P., von Harrach, D., Hoffmann, M., d'Hose, N., Hsieh, C. -Y., Ishimoto, S., Ivanov, A., Iwata, T., Jary, V., Joosten, R., Kabuß, E., Kaspar, F., Kerbizi, A., Ketzer, B., Khatun, A., Khaustov, G. V., Klein, F., Koivuniemi, J. H., Kolosov, V. N., Horikawa, K. Kondo, Konorov, I., Korzenev, A. Yu., Kotzinian, A. M., Kouznetsov, O. M., Koval, A., Kral, Z., Kunne, F., Kurek, K., Kurjata, R. P., Lavickova, K., Levorato, S., Lian, Y. -S., Lichtenstadt, J., Lin, P. -J., Longo, R., Lyubovitskij, V. E., Maggiora, A., Makke, N., Mallot, G. K., Maltsev, A., Martin, A., Marzec, J., Matoušek, J., Matsuda, T., Pires, C. Menezes, Metzger, F., Meyer, W., Mikhailov, Yu. V., Mikhasenko, M., Mitrofanov, E., Miura, D., Miyachi, Y., Molina, R., Moretti, A., Nagaytsev, A., Neyret, D., Niemiec, M., Nový, J., Nowak, W. -D., Nukazuka, G., Olshevsky, A. G., Ostrick, M., Panzieri, D., Parsamyan, B., Paul, S., Pekeler, H., Peng, J. -C., Pešek, M., Peshekhonov, D. V., Pešková, M., Platchkov, S., Pochodzalla, J., Polyakov, V. A., Quintans, C., Reicherz, G., Riedl, C., Ryabchikov, D. I., Rychter, A., Rymbekova, A., Samoylenko, V. D., Sandacz, A., Sarkar, S., Savin, I. A., Sbrizzai, G., Schmieden, H., Selyunin, A., Sinha, L., Spülbeck, D., Srnka, A., Stolarski, M., Sulc, M., Suzuki, H., Tessaro, S., Tessarotto, F., Thiel, A., Tosello, F., Townsend, A., Triloki, T., Tskhay, V., Valinoti, B., Veit, B. M., Veloso, J. F. C. A., Vijayakumar, A., Virius, M., Wagner, M., Wallner, S., Zaremba, K., Zavertyaev, M., Zemko, M., Zemlyanichkina, E., Ziembicki, M.

The multiplicities of positive and negative pions, kaons and unidentified hadrons produced in deep-inelastic scattering are measured in bins of the Bjorken scaling variable $x$, the relative virtual-photon energy $y$ and the fraction of the virtual-p

Externí odkaz: http://arxiv.org/abs/2410.12005

Recognizing Lawyers as AI Creators and Intermediaries in Contestability

Autor: Mansi, Gennie, Riedl, Mark

Laws play a key role in the complex socio-technical system impacting contestability: they create the regulations shaping the way AI systems are designed, evaluated, and used. Despite their role in the AI value chain, lawyers' impact on contestability

Externí odkaz: http://arxiv.org/abs/2409.17626

Making Large Language Models into World Models with Precondition and Effect Knowledge

Autor: Xie, Kaige, Yang, Ian, Gunerli, John, Riedl, Mark

World models, which encapsulate the dynamics of how actions affect environments, are foundational to the functioning of intelligent agents. In this work, we explore the potential of Large Language Models (LLMs) to operate as world models. Although LL

Externí odkaz: http://arxiv.org/abs/2409.12278