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pro vyhledávání: '"Zhang, Hanchong"'
Autor:
Cao, Ruisheng, Lei, Fangyu, Wu, Haoyuan, Chen, Jixuan, Fu, Yeqiao, Gao, Hongcheng, Xiong, Xinzhuang, Zhang, Hanchong, Mao, Yuchen, Hu, Wenjing, Xie, Tianbao, Xu, Hongshen, Zhang, Danyang, Wang, Sida, Sun, Ruoxi, Yin, Pengcheng, Xiong, Caiming, Ni, Ansong, Liu, Qian, Zhong, Victor, Chen, Lu, Yu, Kai, Yu, Tao
Data science and engineering workflows often span multiple stages, from warehousing to orchestration, using tools like BigQuery, dbt, and Airbyte. As vision language models (VLMs) advance in multimodal understanding and code generation, VLM-based age
Externí odkaz:
http://arxiv.org/abs/2407.10956
Autor:
Feng, Peiyuan, He, Yichen, Huang, Guanhua, Lin, Yuan, Zhang, Hanchong, Zhang, Yuchen, Li, Hang
We introduce a novel framework of LLM agents named AGILE (AGent that Interacts and Learns from Environments) designed to perform complex conversational tasks with users, leveraging LLMs, memory, tools, and interactions with experts. The agent's abili
Externí odkaz:
http://arxiv.org/abs/2405.14751
Recently, Large Language Models (LLMs) have been demonstrated to possess impressive capabilities in a variety of domains and tasks. We investigate the issue of prompt design in the multi-turn text-to-SQL task and attempt to enhance the LLMs' reasonin
Externí odkaz:
http://arxiv.org/abs/2405.02712
Previous work on spoken language understanding (SLU) mainly focuses on single-intent settings, where each input utterance merely contains one user intent. This configuration significantly limits the surface form of user utterances and the capacity of
Externí odkaz:
http://arxiv.org/abs/2402.18258
Text-to-SQL aims to generate an executable SQL program given the user utterance and the corresponding database schema. To ensure the well-formedness of output SQLs, one prominent approach adopts a grammar-based recurrent decoder to produce the equiva
Externí odkaz:
http://arxiv.org/abs/2310.18662
Recently Large Language Models (LLMs) have been proven to have strong abilities in various domains and tasks. We study the problem of prompt designing in the text-to-SQL task and attempt to improve the LLMs' reasoning ability when generating SQL quer
Externí odkaz:
http://arxiv.org/abs/2310.17342
Autor:
Zhang, Hanchong, Li, Jieyu, Chen, Lu, Cao, Ruisheng, Zhang, Yunyan, Huang, Yu, Zheng, Yefeng, Yu, Kai
The cross-domain text-to-SQL task aims to build a system that can parse user questions into SQL on complete unseen databases, and the single-domain text-to-SQL task evaluates the performance on identical databases. Both of these setups confront unavo
Externí odkaz:
http://arxiv.org/abs/2305.15891
Autor:
Li, Jieyu, Chen, Lu, Cao, Ruisheng, Zhu, Su, Xu, Hongshen, Chen, Zhi, Zhang, Hanchong, Yu, Kai
Exploring the generalization of a text-to-SQL parser is essential for a system to automatically adapt the real-world databases. Previous works provided investigations focusing on lexical diversity, including the influence of the synonym and perturbat
Externí odkaz:
http://arxiv.org/abs/2301.04790
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Akademický článek
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