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Abdalla, Adam, Abe, Mahiro, Abend, Sven, Abidi, Mouine, Aidelsburger, Monika, Alibabaei, Ashkan, Allard, Baptiste, Antoniadis, John, Arduini, Gianluigi, Augst, Nadja, Balamatsias, Philippos, Balaz, Antun, Banks, Hannah, Barcklay, Rachel L., Barone, Michele, Barsanti, Michele, Bason, Mark G., Bassi, Angelo, Bayle, Jean-Baptiste, Baynham, Charles F. A., Beaufils, Quentin, Beldjoudi, Slyan, Belic, Aleksandar, Bennetts, Shayne, Bernabeu, Jose, Bertoldi, Andrea, Bigard, Clara, Bigelow, N. 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J., de Rham, Claudia, De Roeck, Albert, Derr, Daniel, Dey, Soumyodeep, Di Pumpo, Fabio, Djordjevic, Goran S., Doebrich, Babette, Dornan, Peter, Doser, Michael, Drougakis, Giannis, Dunningham, Jacob, Duspayev, Alisher, Easo, Sajan, Eby, Joshua, Efremov, Maxim, Elertas, Gedminas, Ellis, John, Entin, Nicholas, Fairhurst, Stephen, Fani, Mattia, Fassi, Farida, Fayet, Pierre, Felea, Daniel, Feng, Jie, Flack, Robert, Foot, Chris, Freegarde, Tim, Fuchs, Elina, Gaaloul, Naceur, Gao, Dongfeng, Gardner, Susan, Garraway, Barry M., Alzar, Carlos L. Garrido, Gauguet, Alexandre, Giese, Enno, Gill, Patrick, Giudice, Gian F., Glasbrenner, Eric P., Glick, Jonah, Graham, Peter W., Granados, Eduardo, Griffin, Paul F., Gue, Jordan, Guellati-Khelifa, Saida, Gupta, Subhadeep, Gupta, Vishu, Hackermueller, Lucia, Haehnelt, Martin, Hakulinen, Timo, Hammerer, Klemens, Hanimeli, Ekim T., Harte, Tiffany, Hartmann, Sabrina, Hawkins, Leonie, Hees, Aurelien, Herbst, Alexander, Hird, Thomas M., Hobson, Richard, Hogan, Jason, Holst, Bodil, Holynski, Michael, Hosten, Onur, Hsu, Chung Chuan, Huang, Wayne Cheng-Wei, Hughes, Kenneth M., Hussain, Kamran, Huetsi, Gert, Iovino, Antonio, Isfan, Maria-Catalina, Janson, Gregor, Jeglic, Peter, Jetzer, Philippe, Jiang, Yijun, Juzeliunas, Gediminas, Kaenders, Wilhelm, Kalliokoski, Matti, Kehagias, Alex, Kilian, Eva, Klempt, Carsten, Knight, Peter, Koley, Soumen, Konrad, Bernd, Kovachy, Tim, Krutzik, Markus, Kumar, Mukesh, Kumar, Pradeep, Labiad, Hamza, Lan, Shau-Yu, Landragin, Arnaud, Landsberg, Greg, Langlois, Mehdi, Lanigan, Bryony, Poncin-Lafitte, Christophe Le, Lellouch, Samuel, Leone, Bruno, Lewicki, Marek, Lien, Yu-Hung, Lombriser, Lucas, Asamar, Elias Lopez, Lopez-Gonzalez, J. 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This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at C
Externí odkaz:
http://arxiv.org/abs/2412.14960
Autor:
Liu, Yunchao, Dong, Ha, Wang, Xin, Moretti, Rocco, Wang, Yu, Su, Zhaoqian, Gu, Jiawei, Bodenheimer, Bobby, Weaver, Charles David, Meiler, Jens, Derr, Tyler
While deep learning has revolutionized computer-aided drug discovery, the AI community has predominantly focused on model innovation and placed less emphasis on establishing best benchmarking practices. We posit that without a sound model evaluation
Externí odkaz:
http://arxiv.org/abs/2411.09820
Autor:
Zhang, Zhehao, Rossi, Ryan A., Kveton, Branislav, Shao, Yijia, Yang, Diyi, Zamani, Hamed, Dernoncourt, Franck, Barrow, Joe, Yu, Tong, Kim, Sungchul, Zhang, Ruiyi, Gu, Jiuxiang, Derr, Tyler, Chen, Hongjie, Wu, Junda, Chen, Xiang, Wang, Zichao, Mitra, Subrata, Lipka, Nedim, Ahmed, Nesreen, Wang, Yu
Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications. Despite the importance and recent progress, most existing works on personalized LLMs have focused either entirely on (a) per
Externí odkaz:
http://arxiv.org/abs/2411.00027
The rapid growth of online social networks has underscored the importance of understanding the intensity of user relationships, referred to as "tie strength." Over the past few decades, extensive efforts have been made to assess tie strength in netwo
Externí odkaz:
http://arxiv.org/abs/2410.19214
Autor:
Töpfer, Sebastian, Tovar, Sergio, Torres, Josué R. León, Derr, Daniel, Giese, Enno, Fuenzalida, Jorge, Gräfe, Markus
Utilizing nonlinear interferometers for sensing with undetected light enables new sensing and imaging techniques in spectral ranges that are difficult to detect. To enhance this method for future applications, it is advantageous to extract both ampli
Externí odkaz:
http://arxiv.org/abs/2410.17239
Large Language Model-based Augmentation for Imbalanced Node Classification on Text-Attributed Graphs
Node classification on graphs frequently encounters the challenge of class imbalance, leading to biased performance and posing significant risks in real-world applications. Although several data-centric solutions have been proposed, none of them focu
Externí odkaz:
http://arxiv.org/abs/2410.16882
Recently, Knowledge Graphs (KGs) have been successfully coupled with Large Language Models (LLMs) to mitigate their hallucinations and enhance their reasoning capability, such as in KG-based retrieval-augmented frameworks. However, current KG-LLM fra
Externí odkaz:
http://arxiv.org/abs/2410.08985
We study games in which a leader makes a single commitment, and then multiple followers (each with a different utility function) respond. In particular, we study ambiguous commitment strategies in these games, in which the leader may commit to a set
Externí odkaz:
http://arxiv.org/abs/2409.05608
Autor:
Anton, O., Bröckel, I., Derr, D., Fieguth, A., Franzke, M., Gärtner, M., Giese, E., Haase, J. S., Hamann, J., Heidt, A., Kanthak, S., Klempt, C., Kruse, J., Krutzik, M., Kubitza, S., Lotz, C., Müller, K., Pahl, J., Rasel, E. M., Schiemangk, M., Schleich, W. P., Schwertfeger, S., Wicht, A., Wörner, L.
The INTENTAS project aims to develop an atomic sensor utilizing entangled Bose-Einstein condensates (BECs) in a microgravity environment. This key achievement is necessary to advance the capability for measurements that benefit from both entanglement
Externí odkaz:
http://arxiv.org/abs/2409.01051
As one of the most representative DL techniques, Transformer architecture has empowered numerous advanced models, especially the large language models (LLMs) that comprise billions of parameters, becoming a cornerstone in deep learning. Despite the i
Externí odkaz:
http://arxiv.org/abs/2408.01129