Zobrazeno 1 - 10
of 17 778
pro vyhledávání: '"A. Huck"'
Autor:
Volponi, M., Zieliński, J., Rauschendorfer, T., Huck, S., Caravita, R., Auzins, M., Bergmann, B., Burian, P., Brusa, R. S., Camper, A., Castelli, F., Cerchiari, G., Ciuryło, R., Consolati, G., Doser, M., Eliaszuk, K., Giszczak, A., Glöggler, L. T., Graczykowski, Ł., Grosbart, M., Guatieri, F., Gusakova, N., Gustafsson, F., Haider, S., Janik, M. A., Januszek, T., Kasprowicz, G., Khatri, G., Kłosowski, Ł., Kornakov, G., Krumins, V., Lappo, L., Linek, A., Malamant, J., Mariazzi, S., Penasa, L., Petracek, V., Piwiński, M., Pospisil, S., Povolo, L., Prelz, F., Rangwala, S. A., Rawat, B. S., Rienäcker, B., Rodin, V., Røhne, O. M., Sandaker, H., Smolyanskiy, P., Sowiński, T., Tefelski, D., Vafeiadis, T., Welsch, C. P., Wolz, T., Zawada, M., Zurlo, N.
Publikováno v:
Rev. Sci. Instrum. 95, 085116 (2024)
Modern physics experiments are frequently very complex, relying on multiple simultaneous events to happen in order to obtain the desired result. The experiment control system plays a central role in orchestrating the measurement setup: However, its d
Externí odkaz:
http://arxiv.org/abs/2409.01058
With the strong representational power of large language models (LLMs), generative error correction (GER) for automatic speech recognition (ASR) aims to provide semantic and phonetic refinements to address ASR errors. This work explores how LLM-based
Externí odkaz:
http://arxiv.org/abs/2408.16180
Plug, Play, and Fuse: Zero-Shot Joint Decoding via Word-Level Re-ranking Across Diverse Vocabularies
Recent advancements in NLP have resulted in models with specialized strengths, such as processing multimodal inputs or excelling in specific domains. However, real-world tasks, like multimodal translation, often require a combination of these strengt
Externí odkaz:
http://arxiv.org/abs/2408.11327
Building upon the strength of modern large language models (LLMs), generative error correction (GEC) has emerged as a promising paradigm that can elevate the performance of modern automatic speech recognition (ASR) systems. One representative approac
Externí odkaz:
http://arxiv.org/abs/2407.16370
Quantum reinforcement learning utilizes quantum layers to process information within a machine learning model. However, both pure and hybrid quantum reinforcement learning face challenges such as data encoding and the use of quantum computers during
Externí odkaz:
http://arxiv.org/abs/2407.06103
Autor:
Lai, S., Utehs, J., Wilhahn, A., Fouz, M. C., Bach, O., Brianne, E., Ebrahimi, A., Gadow, K., Göttlicher, P., Hartbrich, O., Heuchel, D., Irles, A., Krüger, K., Kvasnicka, J., Lu, S., Neubüser, C., Provenza, A., Reinecke, M., Sefkow, F., Schuwalow, S., De Silva, M., Sudo, Y., Tran, H. L., Liu, L., Masuda, R., Murata, T., Ootani, W., Seino, T., Takatsu, T., Tsuji, N., Pöschl, R., Richard, F., Zerwas, D., Hummer, F., Simon, F., Boudry, V., Brient, J-C., Nanni, J., Videau, H., Buhmann, E., Garutti, E., Huck, S., Kasieczka, G., Martens, S., Rolph, J., Wellhausen, J., Bilki, B., Northacker, D., Onel, Y., Emberger, L., Graf, C.
To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to separate energy deposits from charged and neutral particles. Three publi
Externí odkaz:
http://arxiv.org/abs/2407.00178
Autor:
Williams, Jeremy J., Costea, Stefan, Malony, Allen D., Tskhakaya, David, Kos, Leon, Podolnik, Ales, Hromadka, Jakub, Huck, Kevin, Laure, Erwin, Markidis, Stefano
Particle-in-Cell Monte Carlo simulations on large-scale systems play a fundamental role in understanding the complexities of plasma dynamics in fusion devices. Efficient handling and analysis of vast datasets are essential for advancing these simulat
Externí odkaz:
http://arxiv.org/abs/2406.19058
Autor:
Berghold, M., Orsucci, D., Guatieri, F., Alfaro, S., Auzins, M., Bergmann, B., Burian, P., Brusa, R. S., Camper, A., Caravita, R., Castelli, F., Cerchiari, G., Ciuryło, R., Chehaimi, A., Consolati, G., Doser, M., Eliaszuk, K., Ferguson, R., Germann, M., Giszczak, A., Glöggler, L. T., Graczykowski, Ł., Grosbart, M., Gusakova, N., Gustafsson, F., Haider, S., Huck, S., Hugenschmidt, C., Janik, M. A., Januszek, T., Kasprowicz, G., Kempny, K., Khatri, G., Kłosowski, Ł., Kornakov, G., Krumins, V., Lappo, L., Linek, A., Mariazzi, S., Moskal, P., Nowicka, D., Pandey, P., Pęcak, D., Penasa, L., Petracek, V., Piwiński, M., Pospisil, S., Povolo, L., Prelz, F., Rangwala, S. A., Rauschendorfer, T., Rawat, B. S., Rienäcker, B., Rodin, V., Røhne, O. M., Sandaker, H., Sharma, S., Smolyanskiy, P., Sowiński, T., Tefelski, D., Vafeiadis, T., Volponi, M., Welsch, C. P., Zawada, M., Zielinski, J., Zurlo, N.
The primary goal of the AEgIS experiment is to precisely measure the free fall of antihydrogen within Earth's gravitational field. To this end, a cold ~50K antihydrogen beam has to pass through two grids forming a moir\'e deflectometer before annihil
Externí odkaz:
http://arxiv.org/abs/2406.16044
Large language models (LLMs) have enhanced the capacity of vision-language models to caption visual text. This generative approach to image caption enrichment further makes textual captions more descriptive, improving alignment with the visual contex
Externí odkaz:
http://arxiv.org/abs/2406.13912
While large language models (LLMs) pre-trained on massive amounts of unpaired language data have reached the state-of-the-art in machine translation (MT) of general domain texts, post-editing (PE) is still required to correct errors and to enhance te
Externí odkaz:
http://arxiv.org/abs/2406.02267