Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence

Autor: O'Driscoll, Ross, Hagen, Claudia, Bater, Joe, Adams, James M.

Cyber-attacks pose a security threat to military command and control networks, Intelligence, Surveillance, and Reconnaissance (ISR) systems, and civilian critical national infrastructure. The use of artificial intelligence and autonomous agents in th

Externí odkaz: http://arxiv.org/abs/2411.17585

Lightning IR: Straightforward Fine-tuning and Inference of Transformer-based Language Models for Information Retrieval

Autor: Schlatt, Ferdinand, Fröbe, Maik, Hagen, Matthias

A wide range of transformer-based language models have been proposed for information retrieval tasks. However, fine-tuning and inference of these models is often complex and requires substantial engineering effort. This paper introduces Lightning IR,

Externí odkaz: http://arxiv.org/abs/2411.04677

A wiggling filamentary jet at the origin of the blazar multi-wavelength behaviour

Autor: Raiteri, C. M., Villata, M., Carnerero, M. I., Kurtanidze, S. O., Mirzaqulov, D. O., Benítez, E., Bonnoli, G., Carosati, D., Acosta-Pulido, J. A., Agudo, I., Andreeva, T. S., Apolonio, G., Bachev, R., Borman, G. A., Bozhilov, V., Brown, L. F., Carbonell, W., Casadio, C., Chen, W. P., Damljanovic, G., Ehgamberdiev, S. A., Elsaesser, D., Escudero, J., Feige, M., Fuentes, A., Gabellini, D., Gazeas, K., Giroletti, M., Grishina, T. S., Gupta, A. C., Gurwell, M. A., Hagen-Thorn, V. A., Hamed, G. M., Hiriart, D., Hodges, M., ivanidze, R. Z., Ivanov, D. V., Joner, M. D., Jorstad, S. G., Jovanovic, M. D., Kiehlmann, S., Kimeridze, G. N., Kopatskaya, E. N., Kovalev, Yu. A., Kovalev, Y. Y., Kurtanidze, O. M., Kurtenkov, A., Larionova, E. G., Lessing, A., Lin, H. C., López, J. M., Lorey, C., Ludwig, J., Marchili, N., Marchini, A., Marscher, A. P., Matsumoto, K., Max-Moerbeck, W., Mihov, B., Minev, M., Mingaliev, M. G., Modaressi, A., Morozova, D. A., Mortari, F., Mufakharov, T. V., Myserlis, I., Nikolashvili, M. G., Pearson, T. J., Popkov, A. V., Rahimov, I. A., Readhead, A. C. S., Reinhart, D., Reeves, R., Righini, S., Romanov, F. D., Savchenko, S. S., Semkov, E., Shishkina, E. V., Sigua, L. A., Slavcheva-Mihova, L., Sotnikova, Yu. V., Steineke, R., Stojanovic, M., Strigachev, A., Takey, A., Traianou, E., Troitskaya, Yu. V., Troitskiy, I. S., Tsai, A. L., Valcheva, A., Vasilyev, A. A., Verna, G., Vince, O., Vrontaki, K., Weaver, Z. R., Webb, J., Yuldoshev, Q. X., Zaharieva, E., Zhovtan, A. V.

Blazars are beamed active galactic nuclei known for their strong multi-wavelength variability on timescales from years down to minutes. We aim to investigate the suitability of the twisting jet model presented in previous works to explain the multi-w

Externí odkaz: http://arxiv.org/abs/2410.22319

A Two-Week $IXPE$ Monitoring Campaign on Mrk 421

Autor: Maksym, W. Peter, Liodakis, Ioannis, Saade, M. Lynne, Kim, Dawoon E., Middei, Riccardo, Di Gesu, Laura, Kiehlmann, Sebastian, Matzeu, Gabriele, Agudo, Iván, Marscher, Alan P., Ehlert, Steven R., Jorstad, Svetlana G., Kaaret, Philip, Marshall, Herman L., Pacciani, Luigi, Perri, Matteo, Puccetti, Simonetta, Kouch, Pouya M., Lindfors, Elina, Aceituno, Francisco José, Bonnoli, Giacomo, Casanova, Víctor, Escudero, Juan, Agís-González, Beatriz, Husillos, César, Morcuende, Daniel, Otero-Santos, Jorge, Sota, Alfredo, Piirola, Vilppu, Imazawa, Ryo, Sasada, Mahito, Fukazawa, Yasushi, Kawabata, Koji S., Uemura, Makoto, Mizuno, Tsunefumi, Nakaoka, Tatsuya, Akitaya, Hiroshi, McCall, Callum, Jermak, Helen E., Steele, Iain A., Borman, George A., Grishina, Tatiana S., Hagen-Thorn, Vladimir A., Kopatskaya, Evgenia N., Larionova, Elena G., Morozova, Daria A., Savchenko, Sergey S., Shishkina, Ekaterina V., Troitskiy, Ivan S., Troitskaya, Yulia V., Vasilyev, Andrey A., Zhovtan, Alexey V., Myserlis, Ioannis, Gurwell, Mark, Keating, Garrett, Rao, Ramprasad, Pauley, Colt, Angelakis, Emmanouil, Kraus, Alexander, Berdyugin, Andrei V., Kagitani, Masato, Kravtsov, Vadim, Poutanen, Juri, Sakanoi, Takeshi, Kang, Sincheol, Lee, Sang-Sung, Kim, Sang-Hyun, Cheong, Whee Yeon, Jeong, Hyeon-Woo, Song, Chanwoo, Blinov, Dmitry, Shablovinskaya, Elena, Antonelli, Lucio Angelo, Bachetti, Matteo, Baldini, Luca, Baumgartner, Wayne H., Bellazzini, Ronaldo, Bianchi, Stefano, Bongiorno, Stephen D., Bonino, Raffaella, Brez, Alessandro, Bucciantini, Niccoló, Capitanio, Fiamma, Castellano, Simone, Cavazzuti, Elisabetta, Chen, Chien-Ting, Ciprini, Stefano, Costa, Enrico, De Rosa, Alessandra, Del Monte, Ettore, Di Lalla, Niccoló, Di Marco, Alessandro, Donnarumma, Immacolata, Doroshenko, Victor, Dovčiak, Michal, Enoto, Teruaki, Evangelista, Yuri, Fabiani, Sergio, Ferrazzoli, Riccardo, Garcia, Javier A., Gunji, Shuichi, Hayashida, Kiyoshi, Heyl, Jeremy, Iwakiri, Wataru, Karas, Vladimir, Kislat, Fabian, Kitaguchi, Takao, Kolodziejczak, Jeffery J., Krawczynski, Henric, La Monaca, Fabio, Latronico, Luca, Maldera, Simone, Manfreda, Alberto, Marin, Frédéric, Marinucci, Andrea, Massaro, Francesco, Matt, Giorgio, Mitsuishi, Ikuyuki, Muleri, Fabio, Negro, Michela, Ng, C. -Y., O'Dell, Stephen L., Omodei, Nicola, Oppedisano, Chiara, Papitto, Alessandro, Pavlov, George G., Peirson, Abel Lawrence, Pesce-Rollins, Melissa, Petrucci, Pierre-Olivier, Pilia, Maura, Possenti, Andrea, Ramsey, Brian D., Rankin, John, Ratheesh, Ajay, Roberts, Oliver J., Romani, Roger W., Sgró, Carmelo, Slane, Patrick, Soffitta, Paolo, Spandre, Gloria, Swartz, Douglas A., Tamagawa, Toru, Tavecchio, Fabrizio, Taverna, Roberto, Tawara, Yuzuru, Tennant, Allyn F., Thomas, Nicholas E., Tombesi, Francesco, Trois, Alessio, Tsygankov, Sergey S., Turolla, Roberto, Vink, Jacco, Weisskopf, Martin C., Wu, Kinwah, Xie, Fei, Zane, Silvia

X-ray polarization is a unique new probe of the particle acceleration in astrophysical jets made possible through the Imaging X-ray Polarimetry Explorer. Here we report on the first dense X-ray polarization monitoring campaign on the blazar Mrk 421.

Externí odkaz: http://arxiv.org/abs/2410.19983

SYNOSIS: Image synthesis pipeline for machine vision in metal surface inspection

Autor: Fulir, Juraj, Jeziorski, Natascha, Bosnar, Lovro, Hagen, Hans, Redenbach, Claudia, Gospodnetić, Petra, Herrfurth, Tobias, Trost, Marcus, Gischkat, Thomas

The use of machine learning (ML) methods for development of robust and flexible visual inspection system has shown promising. However their performance is highly dependent on the amount and diversity of training data. This is often restricted not onl

Externí odkaz: http://arxiv.org/abs/2410.14844