Zobrazeno 1 - 10
of 385 008
pro vyhledávání: '"Yen AS"'
Autor:
Long, Do Xuan, Yen, Duong Ngoc, Luu, Anh Tuan, Kawaguchi, Kenji, Kan, Min-Yen, Chen, Nancy F.
We present Multi-expert Prompting, a novel enhancement of ExpertPrompting (Xu et al., 2023), designed to improve the large language model (LLM) generation. Specifically, it guides an LLM to fulfill an input instruction by simulating multiple experts,
Externí odkaz:
http://arxiv.org/abs/2411.00492
Autor:
Gan, Esther, Zhao, Yiran, Cheng, Liying, Mao, Yancan, Goyal, Anirudh, Kawaguchi, Kenji, Kan, Min-Yen, Shieh, Michael
Large Language Models (LLMs) have demonstrated impressive capabilities in reasoning using Chain-of-Thought (CoT) prompting. However, CoT can be biased by users' instruction. In this work, we study the reasoning robustness of LLMs to typographical err
Externí odkaz:
http://arxiv.org/abs/2411.05345
We propose a Continuous-Time Quantum Walks (CTQW) model for one-dimensional Dirac dynamics simulation with higher-order approximation. Our model bridges CTQW with a discrete-time model called Dirac Cellular Automata (DCA) via Quantum Fourier Transfor
Externí odkaz:
http://arxiv.org/abs/2411.04540
In the context of modern life, particularly in Industry 4.0 within the online space, emotions and moods are frequently conveyed through social media posts. The trend of sharing stories, thoughts, and feelings on these platforms generates a vast and p
Externí odkaz:
http://arxiv.org/abs/2411.04532
Autor:
Chen, Bijuan, Gu, Yuhao, Wang, Dong, Shao, Dexi, Deng, Wen, Han, Xin, Jin, Meiling, Zeng, Yu, Ishii, Hirofumi, Liao, Yen-Fa, Zhang, Dongzhou, Zhang, Jianbo, Long, Youwen, Zhu, Jinlong, Yang, Liuxiang, Xiao, Hong, Nei, Jia-cai, Shi, Youguo, Jin, Changqing, Hu, Jiangping, Mao, Ho-kwang, Ding, Yang
Attaining superconducting critical temperatures (Tc) beyond the limit around 14 K observed thus far in spinel compounds AB2X4 (A, B = transition metals, X = O/chalcogen) could elucidate interaction intricacies and inform materials design. This work s
Externí odkaz:
http://arxiv.org/abs/2411.04407
Autor:
Hsieh, He-Yen, Li, Ziyun, Zhang, Sai Qian, Ting, Wei-Te Mark, Chang, Kao-Den, De Salvo, Barbara, Liu, Chiao, Kung, H. T.
We present GazeGen, a user interaction system that generates visual content (images and videos) for locations indicated by the user's eye gaze. GazeGen allows intuitive manipulation of visual content by targeting regions of interest with gaze. Using
Externí odkaz:
http://arxiv.org/abs/2411.04335
Autor:
Choi, Youngwoo, Kwon, Woojin, Pattle, Kate, Arzoumanian, Doris, Bourke, Tyler L., Hoang, Thiem, Hwang, Jihye, Koch, Patrick M., Sadavoy, Sarah, Bastien, Pierre, Furuya, Ray, Lai, Shih-Ping, Qiu, Keping, Ward-Thompson, Derek, Berry, David, Byun, Do-Young, Chen, Huei-Ru Vivien, Chen, Wen Ping, Chen, Mike, Chen, Zhiwei, Ching, Tao-Chung, Cho, Jungyeon, Choi, Minho, Choi, Yunhee, Coudé, Simon, Chrysostomou, Antonio, Chung, Eun Jung, Dai, Sophia, Debattista, Victor, Di Francesco, James, Diep, Pham Ngoc, Doi, Yasuo, Duan, Hao-Yuan, Duan, Yan, Eswaraiah, Chakali, Fanciullo, Lapo, Fiege, Jason, Fissel, Laura M., Franzmann, Erica, Friberg, Per, Friesen, Rachel, Fuller, Gary, Gledhill, Tim, Graves, Sarah, Greaves, Jane, Griffin, Matt, Gu, Qilao, Han, Ilseung, Hasegawa, Tetsuo, Houde, Martin, Hull, Charles L. H., Inoue, Tsuyoshi, Inutsuka, Shu-ichiro, Iwasaki, Kazunari, Jeong, Il-Gyo, Johnstone, Doug, Karoly, Janik, Könyves, Vera, Kang, Ji-hyun, Lacaille, Kevin, Law, Chi-Yan, Lee, Chang Won, Lee, Hyeseung, Lee, Chin-Fei, Lee, Jeong-Eun, Lee, Sang-Sung, Li, Dalei, Li, Di, Li, Guangxing, Li, Hua-bai, Lin, Sheng-Jun, Liu, Hong-Li, Liu, Tie, Liu, Sheng-Yuan, Liu, Junhao, Longmore, Steven, Lu, Xing, Lyo, A-Ran, Mairs, Steve, Matsumura, Masafumi, Matthews, Brenda, Moriarty-Schieven, Gerald, Nagata, Tetsuya, Nakamura, Fumitaka, Nakanishi, Hiroyuki, Ngoc, Nguyen Bich, Ohashi, Nagayoshi, Onaka, Takashi, Park, Geumsook, Parsons, Harriet, Peretto, Nicolas, Priestley, Felix, Pyo, Tae-Soo, Qian, Lei, Rao, Ramprasad, Rawlings, Jonathan, Rawlings, Mark, Retter, Brendan, Richer, John, Rigby, Andrew, Saito, Hiro, Savini, Giorgio, Seta, Masumichi, Sharma, Ekta, Shimajiri, Yoshito, Shinnaga, Hiroko, Soam, Archana, Kang, Miju, Kataoka, Akimasa, Kawabata, Koji, Kemper, Francisca, Kim, Jongsoo, Kim, Shinyoung, Kim, Gwanjeong, Kim, Kyoung Hee, Kim, Mi-Ryang, Kim, Kee-Tae, Kim, Hyosung, Kirchschlager, Florian, Kirk, Jason, Kobayashi, Masato I. N., Kusune, Takayoshi, Kwon, Jungmi, Tamura, Motohide, Tang, Ya-Wen, Tang, Xindi, Tomisaka, Kohji, Tsukamoto, Yusuke, Viti, Serena, Wang, Hongchi, Wang, Jia-Wei, Wu, Jintai, Xie, Jinjin, Yang, Meng-Zhe, Yen, Hsi-Wei, Yoo, Hyunju, Yuan, Jinghua, Yun, Hyeong-Sik, Zenko, Tetsuya, Zhang, Guoyin, Zhang, Yapeng, Zhang, Chuan-Peng, Zhou, Jianjun, Zhu, Lei, de Looze, Ilse, André, Philippe, Dowell, C. Darren, Eden, David, Eyres, Stewart, Falle, Sam, Gouellec, Valentin J. M. Le, Poidevin, Frédérick, van Loo, Sven
We present 850 $\mu$m polarization observations of the IC 348 star-forming region in the Perseus molecular cloud as part of the B-fields In STar-forming Region Observation (BISTRO) survey. We study the magnetic properties of two cores (HH 211 MMS and
Externí odkaz:
http://arxiv.org/abs/2411.01960
Large vision-language models (LVLMs) suffer from hallucination, resulting in misalignment between the output textual response and the input visual content. Recent research indicates that the over-reliance on the Large Language Model (LLM) backbone, a
Externí odkaz:
http://arxiv.org/abs/2411.02712
Autor:
Chang, Matthew, Chhablani, Gunjan, Clegg, Alexander, Cote, Mikael Dallaire, Desai, Ruta, Hlavac, Michal, Karashchuk, Vladimir, Krantz, Jacob, Mottaghi, Roozbeh, Parashar, Priyam, Patki, Siddharth, Prasad, Ishita, Puig, Xavier, Rai, Akshara, Ramrakhya, Ram, Tran, Daniel, Truong, Joanne, Turner, John M., Undersander, Eric, Yang, Tsung-Yen
We present a benchmark for Planning And Reasoning Tasks in humaN-Robot collaboration (PARTNR) designed to study human-robot coordination in household activities. PARTNR tasks exhibit characteristics of everyday tasks, such as spatial, temporal, and h
Externí odkaz:
http://arxiv.org/abs/2411.00081
Bilevel optimization problems are characterized by an interactive hierarchical structure, where the upper level seeks to optimize its strategy while simultaneously considering the response of the lower level. Evolutionary algorithms are commonly used
Externí odkaz:
http://arxiv.org/abs/2410.24081