Zobrazeno 1 - 10
of 578
pro vyhledávání: '"Song, Sen"'
Autor:
Shen, Xinke, Gan, Runmin, Wang, Kaixuan, Yang, Shuyi, Zhang, Qingzhu, Liu, Quanying, Zhang, Dan, Song, Sen
Electroencephalogram (EEG)-based emotion decoding can objectively quantify people's emotional state and has broad application prospects in human-computer interaction and early detection of emotional disorders. Recently emerging deep learning architec
Externí odkaz:
http://arxiv.org/abs/2411.04568
Neural representations induced by naturalistic stimuli offer insights into how humans respond to stimuli in daily life. Understanding neural mechanisms underlying naturalistic stimuli processing hinges on the precise identification and extraction of
Externí odkaz:
http://arxiv.org/abs/2402.14213
Autor:
Fang, Junjie, Tang, Likai, Bi, Hongzhe, Qin, Yujia, Sun, Si, Li, Zhenyu, Li, Haolun, Li, Yongjian, Cong, Xin, Lin, Yankai, Yan, Yukun, Shi, Xiaodong, Song, Sen, Liu, Zhiyuan, Sun, Maosong
Long-context processing is a critical ability that constrains the applicability of large language models (LLMs). Although there exist various methods devoted to enhancing the long-context processing ability of LLMs, they are developed in an isolated
Externí odkaz:
http://arxiv.org/abs/2402.03009
Replay is a powerful strategy to promote learning in artificial intelligence and the brain. However, the conditions to generate it and its functional advantages have not been fully recognized. In this study, we develop a modular reinforcement learnin
Externí odkaz:
http://arxiv.org/abs/2402.01467
Nowadays, open-source large language models like LLaMA have emerged. Recent developments have incorporated supervised fine-tuning (SFT) and reinforcement learning fine-tuning (RLFT) to align these models with human goals. However, SFT methods treat a
Externí odkaz:
http://arxiv.org/abs/2309.11235
Recurrent spiking neural networks (RSNNs) hold great potential for advancing artificial general intelligence, as they draw inspiration from the biological nervous system and show promise in modeling complex dynamics. However, the widely-used surrogat
Externí odkaz:
http://arxiv.org/abs/2305.17650
Autor:
Chen, Luyao, Chen, Zhiqiang, Jiang, Longsheng, Liu, Xiang, Xu, Linlu, Zhang, Bo, Zou, Xiaolong, Gao, Jinying, Zhu, Yu, Gong, Xizi, Yu, Shan, Song, Sen, Chen, Liangyi, Fang, Fang, Wu, Si, Liu, Jia
Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation. Despite these powerful applications, there are still
Externí odkaz:
http://arxiv.org/abs/2301.08382
Autor:
Yan, Yukun, Song, Sen
There has been a growing academic interest in the recognition of nested named entities in many domains. We tackle the task with a novel local hypergraph-based method: We first propose start token candidates and generate corresponding queries with the
Externí odkaz:
http://arxiv.org/abs/2204.11467
Autor:
Liu, Xianggen, Li, Pengyong, Meng, Fandong, Zhou, Hao, Zhong, Huasong, Zhou, Jie, Mou, Lili, Song, Sen
Publikováno v:
Neurocomputing, 465:310-324 (2021)
Optimization of discrete structures aims at generating a new structure with the better property given an existing one, which is a fundamental problem in machine learning. Different from the continuous optimization, the realistic applications of discr
Externí odkaz:
http://arxiv.org/abs/2110.01384
EEG signals have been reported to be informative and reliable for emotion recognition in recent years. However, the inter-subject variability of emotion-related EEG signals still poses a great challenge for the practical applications of EEG-based emo
Externí odkaz:
http://arxiv.org/abs/2109.09559