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pro vyhledávání: '"Aggarwal P"'
Sarcasm is a type of irony, characterized by an inherent mismatch between the literal interpretation and the intended connotation. Though sarcasm detection in text has been extensively studied, there are situations in which textual input alone might
Externí odkaz:
http://arxiv.org/abs/2408.02595
Autor:
Soos, Mate, Sarkar, Uddalok, Aggarwal, Divesh, Chakraborty, Sourav, Meel, Kuldeep S., Obremski, Maciej
Model counting is a fundamental problem in many practical applications, including query evaluation in probabilistic databases and failure-probability estimation of networks. In this work, we focus on a variant of this problem where the underlying for
Externí odkaz:
http://arxiv.org/abs/2407.19946
Autor:
Chatterjee, Deep, Marx, Ethan, Benoit, William, Kumar, Ravi, Desai, Malina, Govorkova, Ekaterina, Gunny, Alec, Moreno, Eric, Omer, Rafia, Raikman, Ryan, Saleem, Muhammed, Aggarwal, Shrey, Coughlin, Michael W., Harris, Philip, Katsavounidis, Erik
We report a gravitational-wave parameter estimation algorithm, AMPLFI, based on likelihood-free inference using normalizing flows. The focus of AMPLFI is to perform real-time parameter estimation for candidates detected by machine-learning based comp
Externí odkaz:
http://arxiv.org/abs/2407.19048
Non-local operations play a crucial role in computer vision enabling the capture of long-range dependencies through weighted sums of features across the input, surpassing the constraints of traditional convolution operations that focus solely on loca
Externí odkaz:
http://arxiv.org/abs/2407.18906
Autor:
Ganesh, Swetha, Aggarwal, Vaneet
In our study, we delve into average-reward reinforcement learning with general policy parametrization. Within this domain, current guarantees either fall short with suboptimal guarantees or demand prior knowledge of mixing time. To address these issu
Externí odkaz:
http://arxiv.org/abs/2407.18878
Autor:
Belle II Collaboration, Adachi, I., Aggarwal, L., Aihara, H., Akopov, N., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, T., Aushev, V., Aversano, M., Ayad, R., Babu, V., Bae, H., Bahinipati, S., Bambade, P., Banerjee, Sw., Bansal, S., Barrett, M., Baudot, J., Bauer, M., Baur, A., Beaubien, A., Becherer, F., Becker, J., Bennett, J. V., Bernlochner, F. U., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhuyan, B., Bianchi, F., Bierwirth, L., Bilka, T., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Borah, J., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Cao, L., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Chang, P., Cheaib, R., Cheema, P., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Corona, L., Cui, J. X., Dattola, F., De La Cruz-Burelo, E., De La Motte, S. A., De Nardo, G., De Nuccio, M., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Dhamija, R., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dorigo, M., Dorner, D., Dort, K., Dossett, D., Dreyer, S., Dubey, S., Dugic, K., Dujany, G., Ecker, P., Eliachevitch, M., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Frey, A., Fulsom, B. G., Gabrielli, A., Garcia-Hernandez, M., Garg, R., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Ghumaryan, H., Giakoustidis, G., Giordano, R., Giri, A., Glazov, A., Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Granderath, S., Greenwald, D., Gruberová, Z., Gu, T., Gudkova, K., Haide, I., Halder, S., Han, Y., Hara, T., Harris, C., Hayasaka, K., Hayashii, H., Hazra, S., Hearty, C., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jackson, P., Jacobs, W. W., Jang, E. -J., Jia, S., Jin, Y., Johnson, A., Joo, K. K., Junkerkalefeld, H., Kalita, D., Kaliyar, A. B., Kandra, J., Kang, K. H., Kang, S., Karyan, G., Kawasaki, T., Keil, F., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, K. -H., Kim, Y. -K., Kindo, H., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Konno, T., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, J., Kumar, M., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Laurenza, M., Lautenbach, K., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Leo, P., Lemettais, C., Levit, D., Lewis, P. M., Li, L. K., Li, S. X., Li, Y., Li, Y. B., Libby, J., Liptak, Z., Liu, M. H., Liu, Q. Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Lyu, C., Ma, Y., Maggiora, M., Maharana, S. P., Maiti, R., Maity, S., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcantonio, D., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matvienko, D., Maurya, S. K., McKenna, J. A., Mehta, R., Meier, F., Merola, M., Metzner, F., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Mizuk, R., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mrvar, M., Mussa, R., Nakamura, I., Nakao, M., Nakazawa, Y., Charan, A. Narimani, Naruki, M., Narwal, D., Natkaniec, Z., Natochii, A., Nayak, L., Nayak, M., Nazaryan, G., Neu, M., Niiyama, M., Nishida, S., Ogawa, S., Onishchuk, Y., Ono, H., Pakhlova, G., Pardi, S., Parham, K., Park, H., Park, J., Park, S. -H., Paschen, B., Passeri, A., Patra, S., Paul, S., Pedlar, T. K., Peschke, R., Pestotnik, R., Piccolo, M., Piilonen, L. E., Angioni, G. Pinna, Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Prudiiev, I., Purwar, H., Rados, P., Raeuber, G., Raiz, S., Rauls, N., Reif, M., Reiter, S., Remnev, M., Reuter, L., Ripp-Baudot, I., Rizzo, G., Robertson, S. H., Roehrken, M., Roney, J. M., Rostomyan, A., Rout, N., Sanders, D. A., Sandilya, S., Santelj, L., Sato, Y., Savinov, V., Scavino, B., Schmitt, C., Schneider, S., Schnepf, M., Schwanda, C., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Sharma, C., Shen, C. P., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Sibidanov, A., Simon, F., Singh, J. B., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Spataro, S., Spruck, B., Starič, M., Stavroulakis, P., Stefkova, S., Stroili, R., Sumihama, M., Sumisawa, K., Sutcliffe, W., Suwonjandee, N., Svidras, H., Takahashi, M., Takizawa, M., Tamponi, U., Tanaka, S., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Tonelli, D., Torassa, E., Trabelsi, K., Uchida, M., Ueda, I., Uglov, T., Unger, K., Unno, Y., Uno, K., Uno, S., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vinokurova, A., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Vossen, A., Wach, B., Wakai, M., Wallner, S., Wang, E., Wang, M. -Z., Wang, Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yang, S. B., Yelton, J., Yin, J. H., Yook, Y. M., Yoshihara, K., Yuan, C. Z., Zani, L., Zeng, F., Zhang, B., Zhilich, V., Zhou, J. S., Zhou, Q. D., Zhou, X. Y., Zhukova, V. I., Žlebčík, R.
We present a measurement of $|V_{ub}|$ from a simultaneous study of the charmless semileptonic decays $B^0\to\pi^- \ell^+ \nu_{\ell}$ and $B^+\to\rho^0 \ell^+\nu_{\ell}$, where $\ell = e, \mu$. This measurement uses a data sample of 387 million $B\ov
Externí odkaz:
http://arxiv.org/abs/2407.17403
Autor:
Miller, Andrew L., Aggarwal, Nancy, Clesse, Sebastien, De Lillo, Federico, Sachdev, Surabhi, Astone, Pia, Palomba, Cristiano, Piccinni, Ornella J., Pierini, Lorenzo
Gravitational waves from sub-solar mass primordial black holes could be detected in LIGO, Virgo and KAGRA data. Here, we apply a method originally designed to look for rapidly spinning-down neutron stars, the generalized frequency-Hough transform, to
Externí odkaz:
http://arxiv.org/abs/2407.17052
Apps and their integrated third party libraries often collect a variety of data from people to show them personalized ads. This practice is often privacy-invasive. Since 2013, Google has therefore allowed users to limit ad tracking on Android via sys
Externí odkaz:
http://arxiv.org/abs/2407.14938
Autor:
Carter, A. L., May, E. M., Espinoza, N., Welbanks, L., Ahrer, E., Alderson, L., Brahm, R., Feinstein, A. D., Grant, D., Line, M., Morello, G., O'Steen, R., Radica, M., Rustamkulov, Z., Stevenson, K. B., Turner, J. D., Alam, M. K., Anderson, D. R., Batalha, N. M., Battley, M. P., Bayliss, D., Bean, J. L., Benneke, B., Berta-Thompson, Z. K., Brande, J., Bryant, E. M., Burleigh, M. R., Coulombe, L., Crossfield, I. J. M., Damiano, M., Désert, J. -M., Flagg, L., Gill, S., Inglis, J., Kirk, J., Knutson, H., Kreidberg, L., Morales, M. López, Mansfield, M., Moran, S. E., Murray, C. A., Nixon, M. C., de la Roche, D. J. M. Petit dit, Rackham, B. V., Schlawin, E., Sing, D. K., Wakeford, H. R., Wallack, N. L., Wheatley, P. J., Zieba, S., Aggarwal, K., Barstow, J. K., Bell, T. J., Blecic, J., Caceres, C., Crouzet, N., Cubillos, P. E., Daylan, T., de Val-Borro, M., Decin, L., Fortney, J. J., Gibson, N. P., Heng, K., Hu, R., Kempton, E M. -R., Lagage, P., Lothringer, J. D., Lustig-Yaeger, J., Mancini, L., Mayne, N. J., Mayorga, L. C., Molaverdikhani, K., Nasedkin, E., Ohno, K., Parmentier, V., Powell, D., Redfield, S., Roy, P., Taylor, J., Zhang, X.
Observing exoplanets through transmission spectroscopy supplies detailed information on their atmospheric composition, physics, and chemistry. Prior to JWST, these observations were limited to a narrow wavelength range across the near-ultraviolet to
Externí odkaz:
http://arxiv.org/abs/2407.13893
Autor:
Ahuja, Sanchit, Tanmay, Kumar, Chauhan, Hardik Hansrajbhai, Patra, Barun, Aggarwal, Kriti, Del Corro, Luciano, Mitra, Arindam, Dhamecha, Tejas Indulal, Awadallah, Ahmed, Choudhary, Monojit, Chaudhary, Vishrav, Sitaram, Sunayana
Despite the remarkable success of LLMs in English, there is a significant gap in performance in non-English languages. In order to address this, we introduce a novel recipe for creating a multilingual synthetic instruction tuning dataset, sPhinX, whi
Externí odkaz:
http://arxiv.org/abs/2407.09879