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pro vyhledávání: '"LI, YONGXIANG"'
There have been a plethora of research on multi-level memory devices, where the resistive random-access memory (RRAM) is a prominent example. Although it is easy to write an RRAM device into multiple (even quasi-continuous) states, it suffers from th
Externí odkaz:
http://arxiv.org/abs/2410.20332
The locate-then-edit paradigm has shown significant promise for knowledge editing (KE) in Large Language Models (LLMs). While previous methods perform well on single-hop fact recall tasks, they consistently struggle with multi-hop factual recall task
Externí odkaz:
http://arxiv.org/abs/2410.06331
Autor:
Ma, Kaijing, Fang, Han, Zang, Xianghao, Ban, Chao, Zhou, Lanxiang, He, Zhongjiang, Li, Yongxiang, Sun, Hao, Feng, Zerun, Hou, Xingsong
Video Moment Retrieval, which aims to locate in-context video moments according to a natural language query, is an essential task for cross-modal grounding. Existing methods focus on enhancing the cross-modal interactions between all moments and the
Externí odkaz:
http://arxiv.org/abs/2408.07600
Autor:
Li, Xiang, Yao, Yiqun, Jiang, Xin, Fang, Xuezhi, Wang, Chao, Liu, Xinzhang, Wang, Zihan, Zhao, Yu, Wang, Xin, Huang, Yuyao, Song, Shuangyong, Li, Yongxiang, Zhang, Zheng, Zhao, Bo, Sun, Aixin, Wang, Yequan, He, Zhongjiang, Wang, Zhongyuan, Li, Xuelong, Huang, Tiejun
Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence. As scaling laws underscore the potential of increasing model sizes, the academic community has intensified its investigations into LLMs with capacitie
Externí odkaz:
http://arxiv.org/abs/2407.02783
Autor:
Li, Xiang, Yao, Yiqun, Jiang, Xin, Fang, Xuezhi, Wang, Chao, Liu, Xinzhang, Wang, Zihan, Zhao, Yu, Wang, Xin, Huang, Yuyao, Song, Shuangyong, Li, Yongxiang, Zhang, Zheng, Zhao, Bo, Sun, Aixin, Wang, Yequan, He, Zhongjiang, Wang, Zhongyuan, Li, Xuelong, Huang, Tiejun
Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications. However, there is a notable paucity of detailed, open-sourced methodologies on efficiently scaling
Externí odkaz:
http://arxiv.org/abs/2404.16645
Autor:
Fang, Han, Zang, Xianghao, Ban, Chao, Feng, Zerun, Zhou, Lanxiang, He, Zhongjiang, Li, Yongxiang, Sun, Hao
Text-video retrieval aims to find the most relevant cross-modal samples for a given query. Recent methods focus on modeling the whole spatial-temporal relations. However, since video clips contain more diverse content than captions, the model alignin
Externí odkaz:
http://arxiv.org/abs/2404.12216
Autor:
Wang, Zihan, Xiao, Jiayu, Li, Mengxiang, He, Zhongjiang, Li, Yongxiang, Wang, Chao, Song, Shuangyong
In our dynamic world where data arrives in a continuous stream, continual learning enables us to incrementally add new tasks/domains without the need to retrain from scratch. A major challenge in continual learning of language model is catastrophic f
Externí odkaz:
http://arxiv.org/abs/2403.10894
Autor:
He, Zhongjiang, Wang, Zihan, Liu, Xinzhang, Liu, Shixuan, Yao, Yitong, Huang, Yuyao, Li, Xuelong, Li, Yongxiang, Che, Zhonghao, Zhang, Zhaoxi, Wang, Yan, Wang, Xin, Pu, Luwen, Xu, Huinan, Fang, Ruiyu, Zhao, Yu, Zhang, Jie, Huang, Xiaomeng, Lu, Zhilong, Peng, Jiaxin, Zheng, Wenjun, Wang, Shiquan, Yang, Bingkai, he, Xuewei, Jiang, Zhuoru, Xie, Qiyi, Zhang, Yanhan, Li, Zhongqiu, Shi, Lingling, Fu, Weiwei, Zhang, Yin, Huang, Zilu, Xiong, Sishi, Zhang, Yuxiang, Wang, Chao, Song, Shuangyong
In this technical report, we present TeleChat, a collection of large language models (LLMs) with parameters of 3 billion, 7 billion and 12 billion. It includes pretrained language models as well as fine-tuned chat models that is aligned with human pr
Externí odkaz:
http://arxiv.org/abs/2401.03804
Autor:
Abidi, Irfan H., Giridhar, Sindhu Priya, Tollerud, Jonathan O., Limb, Jake, Mazumder, Aishani, Mayes, Edwin LH, Murdoch, Billy J., Xu, Chenglong, Bhoriya, Ankit, Ranjan, Abhishek, Ahmed, Taimur, Li, Yongxiang, Davis, Jeffrey A., Bentley, Cameron L., Russo, Salvy P., Della Gaspera, Enrico, Walia, Sumeet
Defects in atomically thin materials can drive new functionalities and expand applications to multifunctional systems that are monolithically integrated. An ability to control formation of defects during the synthesis process is an important capabili
Externí odkaz:
http://arxiv.org/abs/2311.07984