Zobrazeno 1 - 10
of 333 177
pro vyhledávání: '"Tu, AT"'
Autor:
Zhao, C. C., Wang, L. S., Xia, W., Yin, Q. W., Deng, H. B., Liu, G. W., Liu, J. J., Zhang, X., Ni, J. M., Huang, Y. Y., Tu, C. P., Tao, Z. C., Tu, Z. J., Gong, C. S., Wang, Z. W., Lei, H. C., Guo, Y. F., Yang, X. F., Yin, J. X., Li, S. Y.
Publikováno v:
Chinese Physics Letters 41, 127303 (2024)
The V-based kagome superconductors $A$V$_3$Sb$_5$ ($A$ = K, Rb, and Cs) host charge density wave (CDW) and a topological nontrivial band structure, thereby provide a great platform to study the interplay of superconductivity (SC), CDW, frustration, a
Externí odkaz:
http://arxiv.org/abs/2412.18446
Autor:
Tu, Zhengkai, Choure, Sourabh J., Fong, Mun Hong, Roh, Jihye, Levin, Itai, Yu, Kevin, Joung, Joonyoung F., Morgan, Nathan, Li, Shih-Cheng, Sun, Xiaoqi, Lin, Huiqian, Murnin, Mark, Liles, Jordan P., Struble, Thomas J., Fortunato, Michael E., Liu, Mengjie, Green, William H., Jensen, Klavs F., Coley, Connor W.
The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. Here, we detail the newest version of AS
Externí odkaz:
http://arxiv.org/abs/2501.01835
Despite significant advancements in video generation, inserting a given object into videos remains a challenging task. The difficulty lies in preserving the appearance details of the reference object and accurately modeling coherent motions at the sa
Externí odkaz:
http://arxiv.org/abs/2501.01427
In this paper, we establish the modified concavity inequality for complex Hessian equations under the semi-convexity assumption inspired by Lu \cite{Lu23} and Zhang \cite{Z24} for real case. Then second order estimates for admissible solutions of com
Externí odkaz:
http://arxiv.org/abs/2501.01017
Autor:
Kang, Yipeng, Wang, Junqi, Li, Yexin, Zhong, Fangwei, Feng, Xue, Wang, Mengmeng, Tu, Wenming, Wang, Quansen, Li, Hengli, Zheng, Zilong
As large language models (LLMs) become increasingly integrated into critical applications, aligning their behavior with human values presents significant challenges. Current methods, such as Reinforcement Learning from Human Feedback (RLHF), often fo
Externí odkaz:
http://arxiv.org/abs/2501.00581
Knowledge Graphs (KGs) provide a structured representation of knowledge but often suffer from challenges of incompleteness. To address this, link prediction or knowledge graph completion (KGC) aims to infer missing new facts based on existing facts i
Externí odkaz:
http://arxiv.org/abs/2501.00397
Autor:
Chen, Xingyu, Xu, Jiahao, Liang, Tian, He, Zhiwei, Pang, Jianhui, Yu, Dian, Song, Linfeng, Liu, Qiuzhi, Zhou, Mengfei, Zhang, Zhuosheng, Wang, Rui, Tu, Zhaopeng, Mi, Haitao, Yu, Dong
The remarkable performance of models like the OpenAI o1 can be attributed to their ability to emulate human-like long-time thinking during inference. These models employ extended chain-of-thought (CoT) processes, exploring multiple strategies to enha
Externí odkaz:
http://arxiv.org/abs/2412.21187
With the rapid development of large language models (LLMs) and the growing demand for personalized content, recommendation systems have become critical in enhancing user experience and driving engagement. Collaborative filtering algorithms, being cor
Externí odkaz:
http://arxiv.org/abs/2412.18715
Autor:
Li, Haonan, Han, Xudong, Zhai, Zenan, Mu, Honglin, Wang, Hao, Zhang, Zhenxuan, Geng, Yilin, Lin, Shom, Wang, Renxi, Shelmanov, Artem, Qi, Xiangyu, Wang, Yuxia, Hong, Donghai, Yuan, Youliang, Chen, Meng, Tu, Haoqin, Koto, Fajri, Kuribayashi, Tatsuki, Zeng, Cong, Bhardwaj, Rishabh, Zhao, Bingchen, Duan, Yawen, Liu, Yi, Alghamdi, Emad A., Yang, Yaodong, Dong, Yinpeng, Poria, Soujanya, Liu, Pengfei, Liu, Zhengzhong, Ren, Xuguang, Hovy, Eduard, Gurevych, Iryna, Nakov, Preslav, Choudhury, Monojit, Baldwin, Timothy
To address this gap, we introduce Libra-Leaderboard, a comprehensive framework designed to rank LLMs through a balanced evaluation of performance and safety. Combining a dynamic leaderboard with an interactive LLM arena, Libra-Leaderboard encourages
Externí odkaz:
http://arxiv.org/abs/2412.18551
Autor:
Fu, Yi-Fu, Tu, Yu-Chieh, Cheng, Tzu-Ling, Lin, Cheng-Yu, Yang, Yi-Ting, Liu, Heng-Yi, Liao, Keng-Te, Juan, Da-Cheng, Lin, Shou-De
In this paper, we explore the foundational mechanisms of memorization and generalization in Large Language Models (LLMs), inspired by the functional specialization observed in the human brain. Our investigation serves as a case study leveraging speci
Externí odkaz:
http://arxiv.org/abs/2412.18497