Zobrazeno 1 - 10
of 112 953
pro vyhledávání: '"P. A. CAMPBELL"'
Autor:
Riemer, Matthew, Ashktorab, Zahra, Bouneffouf, Djallel, Das, Payel, Liu, Miao, Weisz, Justin D., Campbell, Murray
As the research community aims to build better AI assistants that are more dynamic and personalized to the diversity of humans that they interact with, there is increased interest in evaluating the theory of mind capabilities of large language models
Externí odkaz:
http://arxiv.org/abs/2412.19726
Autor:
Scharenberg, L., Alozy, J., Billereau, W., Brunbauer, F., Campbell, M., Carbonez, P., Flöthner, K. J., Garcia, F., Garcia-Tejedor, A., Genetay, T., Heijhoff, K., Janssens, D., Kaufmann, S., Lisowska, M., Llopart, X., Mager, M., Mehl, B., Muller, H., de Oliveira, R., Oliveri, E., Orlandini, G., Pfeiffer, D., Diaz, F. Piernas, Rodrigues, A., Ropelewski, L., Samarati, J., van Beuzekom, M., Van Stenis, M., Veenhof, R., Vicente, M.
Combining gaseous detectors with a high-granularity pixelated charge readout enables experimental applications which otherwise could not be achieved. This includes high-resolution tracking of low-energetic particles, requiring ultra-low material budg
Externí odkaz:
http://arxiv.org/abs/2412.16950
When it comes to classifying child sexual abuse images, managing similar inter-class correlations and diverse intra-class correlations poses a significant challenge. Vision transformer models, unlike conventional deep convolutional network models, le
Externí odkaz:
http://arxiv.org/abs/2412.16446
Forensic science plays a crucial role in legal investigations, and the use of advanced technologies, such as object detection based on machine learning methods, can enhance the efficiency and accuracy of forensic analysis. Human hands are unique and
Externí odkaz:
http://arxiv.org/abs/2412.16431
Autor:
Shrestha, Ajay Kumar, Barthwal, Ankur, Campbell, Molly, Shouli, Austin, Syed, Saad, Joshi, Sandhya, Vassileva, Julita
This systematic literature review investigates perceptions, concerns, and expectations of young digital citizens regarding privacy in artificial intelligence (AI) systems, focusing on social media platforms, educational technology, gaming systems, an
Externí odkaz:
http://arxiv.org/abs/2412.16369
Accurate career path prediction can support many stakeholders, like job seekers, recruiters, HR, and project managers. However, publicly available data and tools for career path prediction are scarce. In this work, we introduce KARRIEREWEGE, a compre
Externí odkaz:
http://arxiv.org/abs/2412.14612
Autor:
Soni, Sagar, Dudhane, Akshay, Debary, Hiyam, Fiaz, Mustansar, Munir, Muhammad Akhtar, Danish, Muhammad Sohail, Fraccaro, Paolo, Watson, Campbell D, Klein, Levente J, Khan, Fahad Shahbaz, Khan, Salman
Automated analysis of vast Earth observation data via interactive Vision-Language Models (VLMs) can unlock new opportunities for environmental monitoring, disaster response, and resource management. Existing generic VLMs do not perform well on Remote
Externí odkaz:
http://arxiv.org/abs/2412.15190
Autor:
Simner, Ben, Armstrong, Alasdair, Bauereiss, Thomas, Campbell, Brian, Kammar, Ohad, Pichon-Pharabod, Jean, Sewell, and Peter
To manage exceptions, software relies on a key architectural guarantee, precision: that exceptions appear to execute between instructions. However, this definition, dating back over 60 years, fundamentally assumes a sequential programmers model. Mode
Externí odkaz:
http://arxiv.org/abs/2412.15140
Autor:
Longpre, Shayne, Singh, Nikhil, Cherep, Manuel, Tiwary, Kushagra, Materzynska, Joanna, Brannon, William, Mahari, Robert, Dey, Manan, Hamdy, Mohammed, Saxena, Nayan, Anis, Ahmad Mustafa, Alghamdi, Emad A., Chien, Vu Minh, Obeng-Marnu, Naana, Yin, Da, Qian, Kun, Li, Yizhi, Liang, Minnie, Dinh, An, Mohanty, Shrestha, Mataciunas, Deividas, South, Tobin, Zhang, Jianguo, Lee, Ariel N., Lund, Campbell S., Klamm, Christopher, Sileo, Damien, Misra, Diganta, Shippole, Enrico, Klyman, Kevin, Miranda, Lester JV, Muennighoff, Niklas, Ye, Seonghyeon, Kim, Seungone, Gupta, Vipul, Sharma, Vivek, Zhou, Xuhui, Xiong, Caiming, Villa, Luis, Biderman, Stella, Pentland, Alex, Hooker, Sara, Kabbara, Jad
Progress in AI is driven largely by the scale and quality of training data. Despite this, there is a deficit of empirical analysis examining the attributes of well-established datasets beyond text. In this work we conduct the largest and first-of-its
Externí odkaz:
http://arxiv.org/abs/2412.17847
Autor:
The H1 collaboration, Andreev, V., Arratia, M., Baghdasaryan, A., Baty, A., Begzsuren, K., Bolz, A., Boudry, V., Brandt, G., Britzger, D., Buniatyan, A., Bystritskaya, L., Campbell, A. J., Avila, K. B. Cantun, Cerny, K., Chekelian, V., Chen, Z., Contreras, J. G., Cvach, J., Dainton, J. B., Daum, K., Deshpande, A., Diaconu, C., Drees, A., Eckerlin, G., Egli, S., Elsen, E., Favart, L., Fedotov, A., Feltesse, J., Fleischer, M., Fomenko, A., Gal, C., Gayler, J., Goerlich, L., Gogitidze, N., Gouzevitch, M., Grab, C., Greenshaw, T., Grindhammer, G., Haidt, D., Henderson, R. C. W., Hessler, J., Hladký, J., Hoffmann, D., Horisberger, R., Hreus, T., Huber, F., Jacobs, P. M., Jacquet, M., Janssen, T., Jung, A. W., Katzy, J., Kiesling, C., Klein, M., Kleinwort, C., Klest, H. T., Kogler, R., Kostka, P., Kretzschmar, J., Krücker, D., Krüger, K., Landon, M. P. J., Lange, W., Laycock, P., Lee, S. H., Levonian, S., Li, W., Lin, J., Lipka, K., List, B., List, J., Lobodzinski, B., Long, O. R., Malinovski, E., Martyn, H. -U., Maxfield, S. J., Mehta, A., Meyer, A. B., Meyer, J., Mikocki, S., Mikuni, V. M., Mondal, M. M., Müller, K., Nachman, B., Naumann, Th., Newman, P. R., Niebuhr, C., Nowak, G., Olsson, J. E., Ozerov, D., Park, S., Pascaud, C., Patel, G. D., Perez, E., Petrukhin, A., Picuric, I., Pitzl, D., Radescu, V., Raicevic, N., Ravdandorj, T., Reichelt, D., Reimer, P., Rizvi, E., Robmann, P., Roosen, R., Rostovtsev, A., Rotaru, M., Sankey, D. P. C., Sauter, M., Sauvan, E., Schmitt, S., Schmookler, B. A., Schnell, G., Schoeffel, L., Schöning, A., Sefkow, F., Shushkevich, S., Soloviev, Y., Sopicki, P., South, D., Specka, A., Steder, M., Stella, B., Straumann, U., Sun, C., Sykora, T., Thompson, P. D., Acosta, F. Torales, Traynor, D., Tseepeldorj, B., Tu, Z., Tustin, G., Valkárová, A., Vallée, C., Van Mechelen, P., Wegener, D., Wünsch, E., Žáček, J., Zhang, J., Zhang, Z., Žlebčík, R., Zohrabyan, H., Zomer, F.
In deep-inelastic positron-proton scattering, the lepton-jet azimuthal angular asymmetry is measured using data collected with the H1 detector at HERA. When the average transverse momentum of the lepton-jet system, $\lvert \vec{P}_\perp \rvert $, is
Externí odkaz:
http://arxiv.org/abs/2412.14092