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pro vyhledávání: '"He, Junqing"'
Long-term memory is so important for chatbots and dialogue systems (DS) that researchers have developed numerous memory-augmented DS. However, their evaluation methods are different from the real situation in human conversation. They only measured th
Externí odkaz:
http://arxiv.org/abs/2409.15240
Benefiting from diverse instruction datasets, contemporary Large Language Models (LLMs) perform effectively as AI assistants in collaborating with humans. However, LLMs still struggle to generate natural and colloquial responses in real-world applica
Externí odkaz:
http://arxiv.org/abs/2408.09330
Large Language Models (LLMs) with chain-of-thought (COT) prompting have demonstrated impressive abilities on simple nature language inference tasks. However, they tend to perform poorly on Multi-hop Question Answering (MHQA) tasks due to several chal
Externí odkaz:
http://arxiv.org/abs/2407.02964
Autor:
He, Junqing, Pan, Kunhao, Dong, Xiaoqun, Song, Zhuoyang, Liu, Yibo, Sun, Qianguo, Liang, Yuxin, Wang, Hao, Zhang, Enming, Zhang, Jiaxing
While large language models (LLMs) are equipped with longer text input capabilities than before, they are struggling to seek correct information in long contexts. The "lost in the middle" problem challenges most LLMs, referring to the dramatic declin
Externí odkaz:
http://arxiv.org/abs/2311.09198
Autor:
Gan, Ruyi, Wu, Ziwei, Sun, Renliang, Lu, Junyu, Wu, Xiaojun, Zhang, Dixiang, Pan, Kunhao, He, Junqing, Tian, Yuanhe, Yang, Ping, Yang, Qi, Wang, Hao, Zhang, Jiaxing, Song, Yan
Various large language models (LLMs) have been proposed in recent years, including closed- and open-source ones, continually setting new records on multiple benchmarks. However, the development of LLMs still faces several issues, such as high cost of
Externí odkaz:
http://arxiv.org/abs/2311.03301
Autor:
Chen, Nuo, Li, Hongguang, He, Junqing, Bao, Yinan, Lin, Xinshi, Yang, Qi, Liu, Jianfeng, Gan, Ruyi, Zhang, Jiaxing, Wang, Baoyuan, Li, Jia
Publikováno v:
EMNLP 2023
The conversational machine reading comprehension (CMRC) task aims to answer questions in conversations, which has been a hot research topic in recent years because of its wide applications. However, existing CMRC benchmarks in which each conversation
Externí odkaz:
http://arxiv.org/abs/2302.13619
Autor:
Zhang, Jiaxing, Gan, Ruyi, Wang, Junjie, Zhang, Yuxiang, Zhang, Lin, Yang, Ping, Gao, Xinyu, Wu, Ziwei, Dong, Xiaoqun, He, Junqing, Zhuo, Jianheng, Yang, Qi, Huang, Yongfeng, Li, Xiayu, Wu, Yanghan, Lu, Junyu, Zhu, Xinyu, Chen, Weifeng, Han, Ting, Pan, Kunhao, Wang, Rui, Wang, Hao, Wu, Xiaojun, Zeng, Zhongshen, Chen, Chongpei
Nowadays, foundation models become one of fundamental infrastructures in artificial intelligence, paving ways to the general intelligence. However, the reality presents two urgent challenges: existing foundation models are dominated by the English-la
Externí odkaz:
http://arxiv.org/abs/2209.02970
Autor:
Wu, Yunpeng, Yang, Rong, He, Junqing, Chen, Hanlin, Lin, Xiubin, Shi, Xuhua, An, Kaixuan, Li, Chunyang, Gao, Shibao, Chen, Yaguang
Publikováno v:
In Geomorphology 15 November 2023 441
Publikováno v:
In Journal of Asian Earth Sciences 1 August 2022 233
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