Zobrazeno 1 - 10
of 22 120
pro vyhledávání: '"An, Zhifang"'
Autor:
Fang, Qian, Wang, Liming, Chang, Kai, Yang, Hongxin, Yan, Pu, Cao, Kecheng, Li, Mian, Chai, Zhifang, Huang, Qing
Two-dimensional (2D) magnetic semiconductors are a key focus in developing next-generation information storage technologies. MXenes, as emerging 2D early transition metal carbides and nitrides, offer versatile compositions and tunable chemical struct
Externí odkaz:
http://arxiv.org/abs/2410.18337
Autor:
Wang, Xiaochen, He, Junqing, Chen, Liang, Yang, Reza Haf Zhe, Wang, Yiru, Meng, Xiangdi, Pan, Kunhao, Sui, Zhifang
Large Language Models with chain-of-thought prompting, such as OpenAI-o1, have shown impressive capabilities in natural language inference tasks. However, Multi-hop Question Answering (MHQA) remains challenging for many existing models due to issues
Externí odkaz:
http://arxiv.org/abs/2410.17021
The rapid development in the performance of large language models (LLMs) is accompanied by the escalation of model size, leading to the increasing cost of model training and inference. Previous research has discovered that certain layers in LLMs exhi
Externí odkaz:
http://arxiv.org/abs/2410.06541
Through alignment with human preferences, Large Language Models (LLMs) have advanced significantly in generating honest, harmless, and helpful responses. However, collecting high-quality preference data is a resource-intensive and creativity-demandin
Externí odkaz:
http://arxiv.org/abs/2410.06961
Autor:
Yuan, Xu, Zhao, Xiaoshu, Wen, Jiquan, Zheng, Hongxia, Li, Xiao, Chen, Huajin, Ng, Jack, Lin, Zhifang
Understanding how the structured incident light interacts with the inherent properties of the manipulated particle and governs the optical force/torque exerted is a cornerstone in the design of optical manipulation techniques, apart from its theoreti
Externí odkaz:
http://arxiv.org/abs/2410.04006
Building upon advancements in Large Language Models (LLMs), the field of audio processing has seen increased interest in training audio generation tasks with discrete audio token sequences. However, directly discretizing audio by neural audio codecs
Externí odkaz:
http://arxiv.org/abs/2409.19283
Autor:
Wen, Jiquan, Chen, Huajin, Zheng, Hongxia, Xu, Xiaohao, Yan, Shaohui, Yao, Baoli, Lin, Zhifang
Owing to the ubiquity and easy-to-shape property of optical intensity, the intensity gradient force of light has been most spectacularly exploited in optical manipulation of small particles. Manifesting the intensity gradient as an optical torque to
Externí odkaz:
http://arxiv.org/abs/2409.11924
Autor:
Gao, Bofei, Song, Feifan, Miao, Yibo, Cai, Zefan, Yang, Zhe, Chen, Liang, Hu, Helan, Xu, Runxin, Dong, Qingxiu, Zheng, Ce, Quan, Shanghaoran, Xiao, Wen, Zhang, Ge, Zan, Daoguang, Lu, Keming, Yu, Bowen, Liu, Dayiheng, Cui, Zeyu, Yang, Jian, Sha, Lei, Wang, Houfeng, Sui, Zhifang, Wang, Peiyi, Liu, Tianyu, Chang, Baobao
Large Language Models (LLMs) exhibit remarkably powerful capabilities. One of the crucial factors to achieve success is aligning the LLM's output with human preferences. This alignment process often requires only a small amount of data to efficiently
Externí odkaz:
http://arxiv.org/abs/2409.02795
Recent advances have been witnessed in audio-language joint learning, such as CLAP, that shows much success in multi-modal understanding tasks. These models usually aggregate uni-modal local representations, namely frame or word features, into global
Externí odkaz:
http://arxiv.org/abs/2408.07919
Autor:
Chu, Yunfei, Xu, Jin, Yang, Qian, Wei, Haojie, Wei, Xipin, Guo, Zhifang, Leng, Yichong, Lv, Yuanjun, He, Jinzheng, Lin, Junyang, Zhou, Chang, Zhou, Jingren
We introduce the latest progress of Qwen-Audio, a large-scale audio-language model called Qwen2-Audio, which is capable of accepting various audio signal inputs and performing audio analysis or direct textual responses with regard to speech instructi
Externí odkaz:
http://arxiv.org/abs/2407.10759