Zobrazeno 1 - 10
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pro vyhledávání: '"Xu., Yue"'
The cold start problem in recommender systems remains a critical challenge. Current solutions often train hybrid models on auxiliary data for both cold and warm users/items, potentially degrading the experience for the latter. This drawback limits th
Externí odkaz:
http://arxiv.org/abs/2410.14241
Autor:
FASER collaboration, Abraham, Roshan Mammen, Ai, Xiaocong, Anders, John, Antel, Claire, Ariga, Akitaka, Ariga, Tomoko, Atkinson, Jeremy, Bernlochner, Florian U., Bianchi, Emma, Boeckh, Tobias, Boyd, Jamie, Brenner, Lydia, Burger, Angela, Cadoux, Franck, Cardella, Roberto, Casper, David W., Cavanagh, Charlotte, Chen, Xin, Cho, Eunhyung, Chouhan, Dhruv, Coccaro, Andrea, Débieux, Stephane, D'Onofrio, Monica, Desai, Ansh, Dmitrievsky, Sergey, Dobre, Radu, Eley, Sinead, Favre, Yannick, Fellers, Deion, Feng, Jonathan L., Fenoglio, Carlo Alberto, Ferrere, Didier, Fieg, Max, Filali, Wissal, Firu, Elena, Garabaglu, Ali, Gibson, Stephen, Gonzalez-Sevilla, Sergio, Gornushkin, Yuri, Gwilliam, Carl, Hayakawa, Daiki, Holzbock, Michael, Hsu, Shih-Chieh, Hu, Zhen, Iacobucci, Giuseppe, Inada, Tomohiro, Iodice, Luca, Jakobsen, Sune, Joos, Hans, Kajomovitz, Enrique, Kawahara, Hiroaki, Keyken, Alex, Kling, Felix, Köck, Daniela, Kontaxakis, Pantelis, Kose, Umut, Kotitsa, Rafaella, Kuehn, Susanne, Kugathasan, Thanushan, Levinson, Lorne, Li, Ke, Liu, Jinfeng, Liu, Yi, Lutz, Margaret S., MacDonald, Jack, Magliocca, Chiara, Mäkelä, Toni, McCoy, Lawson, McFayden, Josh, Medina, Andrea Pizarro, Milanesio, Matteo, Moretti, Théo, Nakamura, Mitsuhiro, Nakano, Toshiyuki, Nevay, Laurie, Ohashi, Ken, Otono, Hidetoshi, Paolozzi, Lorenzo, Petersen, Brian, Preda, Titi, Prim, Markus, Queitsch-Maitland, Michaela, Rokujo, Hiroki, Rubbia, André, Sabater-Iglesias, Jorge, Sato, Osamu, Scampoli, Paola, Schmieden, Kristof, Schott, Matthias, Sfyrla, Anna, Sgalaberna, Davide, Shamim, Mansoora, Shively, Savannah, Takubo, Yosuke, Tarannum, Noshin, Theiner, Ondrej, Torrence, Eric, Martinez, Oscar Ivan Valdes, Vasina, Svetlana, Vormwald, Benedikt, Wang, Di, Wang, Yuxiao, Welch, Eli, Xu, Yue, Zahorec, Samuel, Zambito, Stefano, Zhang, Shunliang
The first FASER search for a light, long-lived particle decaying into a pair of photons is reported. The search uses LHC proton-proton collision data at $\sqrt{s}=13.6~\text{TeV}$ collected in 2022 and 2023, corresponding to an integrated luminosity
Externí odkaz:
http://arxiv.org/abs/2410.10363
Autor:
Wen, Junyan, Xu, Yue, Wang, Gang, He, Ze-Xu, Chen, Yang, Wang, Ningning, Lu, Tenglong, Ma, Xiaoli, Jin, Feng, Chen, Liucheng, Liu, Miao, Fan, Jing-Wei, Liu, Xiaobing, Pan, Xin-Yu, Liu, Gang-Qin, Cheng, Jinguang, Yu, Xiaohui
Recent reports on the signatures of high-temperature superconductivity with a critical temperature Tc close to 80 K have triggered great research interest and extensive follow-up studies. Although zero-resistance state has been successfully achieved
Externí odkaz:
http://arxiv.org/abs/2410.10275
Autor:
Velmurugan, Mythreyi, Ouyang, Chun, Xu, Yue, Sindhgatta, Renuka, Wickramanayake, Bemali, Moreira, Catarina
Explainable Artificial Intelligence (XAI) techniques are used to provide transparency to complex, opaque predictive models. However, these techniques are often designed for image and text data, and it is unclear how fit-for-purpose they are when appl
Externí odkaz:
http://arxiv.org/abs/2410.12803
As deep learning advances, Large Language Models (LLMs) and their multimodal counterparts, Multimodal Large Language Models (MLLMs), have shown exceptional performance in many real-world tasks. However, MLLMs face significant security challenges, suc
Externí odkaz:
http://arxiv.org/abs/2408.08464
Multimodal Large Language Models (MLLMs) extend the capacity of LLMs to understand multimodal information comprehensively, achieving remarkable performance in many vision-centric tasks. Despite that, recent studies have shown that these models are su
Externí odkaz:
http://arxiv.org/abs/2407.21659
Visual reasoning, as a prominent research area, plays a crucial role in AI by facilitating concept formation and interaction with the world. However, current works are usually carried out separately on small datasets thus lacking generalization abili
Externí odkaz:
http://arxiv.org/abs/2407.19666
Autor:
Wu, Ruidong, Guo, Ruihan, Wang, Rui, Luo, Shitong, Xu, Yue, Li, Jiahan, Ma, Jianzhu, Liu, Qiang, Luo, Yunan, Peng, Jian
Despite the striking success of general protein folding models such as AlphaFold2(AF2, Jumper et al. (2021)), the accurate computational modeling of antibody-antigen complexes remains a challenging task. In this paper, we first analyze AF2's primary
Externí odkaz:
http://arxiv.org/abs/2407.01649
Autor:
Liu, Runze, Zhu, Dongchen, Zhang, Guanghui, Xu, Yue, Shi, Wenjun, Zhang, Xiaolin, Wang, Lei, Li, Jiamao
Unsupervised monocular depth estimation has received widespread attention because of its capability to train without ground truth. In real-world scenarios, the images may be blurry or noisy due to the influence of weather conditions and inherent limi
Externí odkaz:
http://arxiv.org/abs/2406.09782
3D visual grounding is an emerging research area dedicated to making connections between the 3D physical world and natural language, which is crucial for achieving embodied intelligence. In this paper, we propose DASANet, a Dual Attribute-Spatial rel
Externí odkaz:
http://arxiv.org/abs/2406.08907