Zobrazeno 1 - 10
of 24 986
pro vyhledávání: '"Backes, A"'
Machine learning has revolutionized numerous domains, playing a crucial role in driving advancements and enabling data-centric processes. The significance of data in training models and shaping their performance cannot be overstated. Recent research
Externí odkaz:
http://arxiv.org/abs/2409.03741
Adapting Large Language Models (LLMs) to specific tasks introduces concerns about computational efficiency, prompting an exploration of efficient methods such as In-Context Learning (ICL). However, the vulnerability of ICL to privacy attacks under re
Externí odkaz:
http://arxiv.org/abs/2409.01380
Text-to-image models, such as Stable Diffusion (SD), undergo iterative updates to improve image quality and address concerns such as safety. Improvements in image quality are straightforward to assess. However, how model updates resolve existing conc
Externí odkaz:
http://arxiv.org/abs/2408.17285
Autor:
Nilsson, K., Ramazani, V. Fallah, Lindfors, E., Goldoni, P., González, J. Becerra, Pulido, J. A. Acosta, Clavero, R., Otero-Santos, J., Pursimo, T., Pita, S., Kouch, P. M., Boisson, C., Backes, M., Cotter, G., D'Ammando, F., Kasai, E.
Direct redshift determination of BL Lac objects is highly challenging as the emission in the optical and near-infrared (NIR) bands is largely dominated by the non-thermal emission from the relativistic jet that points very close to our line of sight.
Externí odkaz:
http://arxiv.org/abs/2408.14854
Autor:
Backes, K. M., Elgee, P. K., LeBlanc, K. -J., Fancher, C. T., Meyer, D. H., Kunz, P. D., Malvania, N., Nicolich, K. M., Hill, J. C., Marlow, B. L. Schmittberger, Cox, K. C.
Rydberg atom electric field sensors are tunable quantum sensors that can perform sensitive radio frequency (RF) measurements. Their qualities have piqued interest at longer wavelengths where their small size compares favorably to impedance-matched an
Externí odkaz:
http://arxiv.org/abs/2408.14704
Despite being prevalent in the general field of Natural Language Processing (NLP), pre-trained language models inherently carry privacy and copyright concerns due to their nature of training on large-scale web-scraped data. In this paper, we pioneer
Externí odkaz:
http://arxiv.org/abs/2408.11046
The increasing cost of training machine learning (ML) models has led to the inclusion of new parties to the training pipeline, such as users who contribute training data and companies that provide computing resources. This involvement of such new par
Externí odkaz:
http://arxiv.org/abs/2408.00129
Autor:
Zhang, Boyang, Tan, Yicong, Shen, Yun, Salem, Ahmed, Backes, Michael, Zannettou, Savvas, Zhang, Yang
Recently, autonomous agents built on large language models (LLMs) have experienced significant development and are being deployed in real-world applications. These agents can extend the base LLM's capabilities in multiple ways. For example, a well-bu
Externí odkaz:
http://arxiv.org/abs/2407.20859
We establish three variational principles for the upper metric mean dimension with potential of level sets of continuous maps in terms of the entropy of partitions and Katok's entropy of the underlying system. Our results hold for dynamical systems e
Externí odkaz:
http://arxiv.org/abs/2407.16548
Autor:
Aharonian, F., Benkhali, F. Ait, Aschersleben, J., Ashkar, H., Backes, M., Martins, V. Barbosa, Batzofin, R., Becherini, Y., Berge, D., Bernlöhr, K., Böttcher, M., Bolmont, J., de Lavergne, M. de Bony, Borowska, J., Brose, R., Brown, A., Brun, F., Bruno, B., Burger-Scheidlin, C., Casanova, S., Celic, J., Cerruti, M., Chand, T., Chandra, S., Chen, A., Chibueze, J., Chibueze, O., Cotter, G., Cristofari, P., Devin, J., Djannati-Ataï, A., Djuvsland, J., Dmytriiev, A., Egberts, K., Einecke, S., Feijen, K., Filipovic, M., Fontaine, G., Funk, S., Gabici, S., Gallant, Y. A., Glicenstein, J. F., Glombitza, J., Grolleron, G., Haerer, L., Heß, B., Hinton, J. A., Hofmann, W., Holch, T. L., Horns, D., Huang, Zhiqiu, Jamrozy, M., Jankowsky, F., Jung-Richardt, I., Kasai, E., Katarzyński, K., Khatoon, R., Khélifi, B., Kluźniak, W., Komin, Nu., Kosack, K., Kostunin, D., Kundu, A., Lang, R. G., Stum, S. Le, Lemière, A., Lemoine-Goumard, M., Lenain, J. -P., Leuschner, F., Mackey, J., Marandon, V., Martí-Devesa, G., Marx, R., Mehta, A., Mitchell, A., Moderski, R., Moghadam, M. O., Mohrmann, L., Montanari, A., Moulin, E., de Naurois, M., Niemiec, J., Ohm, S., Olivera-Nieto, L., Wilhelmi, E. de Ona, Ostrowski, M., Panny, S., Pensec, U., Peron, G., Pühlhofer, G., Quirrenbach, A., Ravikularaman, S., Regeard, M., Reimer, A., Reimer, O., Ren, H., Renaud, M., Reville, B., Rieger, F., Rowell, G., Rudak, B., Ruiz-Velasco, E., Sabri, K., Sahakian, V., Salzmann, H., Santangelo, A., Sasaki, M., Schäfer, J., Schüssler, F., Schutte, H. M., Sol, H., Spencer, S., Stawarz, Ł., Steinmassl, S., Steppa, C., Streil, K., Sushch, I., Taylor, A. M., Terrier, R., Tsirou, M., Tsuji, N., van Eldik, C., Vecchi, M., Venter, C., Vink, J., Wagner, S. J., White, R., Wierzcholska, A., Zacharias, M., Zdziarski, A. A., Zech, A., Żywucka, N.
Publikováno v:
Astrophysical Journal Letters 970, L21 (2024)
The Tarantula Nebula in the Large Magellanic Cloud is known for its high star formation activity. At its center lies the young massive star cluster R136, providing a significant amount of the energy that makes the nebula shine so brightly at many wav
Externí odkaz:
http://arxiv.org/abs/2407.16219