Zobrazeno 1 - 10
of 15
pro vyhledávání: '"ChaI, Linzheng"'
Autor:
Yang, Liqun, Yang, Jian, Wei, Chaoren, Niu, Guanglin, Zhang, Ge, Wang, Yunli, ChaI, Linzheng, Xia, Wanxu, Guo, Hongcheng, Zhang, Shun, Liu, Jiaheng, Yin, Yuwei, Peng, Junran, Ma, Jiaxin, Sun, Liang, Li, Zhoujun
Fuzzing is an important dynamic program analysis technique designed for finding vulnerabilities in complex software. Fuzzing involves presenting a target program with crafted malicious input to cause crashes, buffer overflows, memory errors, and exce
Externí odkaz:
http://arxiv.org/abs/2409.01944
Autor:
Wu, Xianjie, Yang, Jian, Chai, Linzheng, Zhang, Ge, Liu, Jiaheng, Du, Xinrun, Liang, Di, Shu, Daixin, Cheng, Xianfu, Sun, Tianzhen, Niu, Guanglin, Li, Tongliang, Li, Zhoujun
Recent advancements in Large Language Models (LLMs) have markedly enhanced the interpretation and processing of tabular data, introducing previously unimaginable capabilities. Despite these achievements, LLMs still encounter significant challenges wh
Externí odkaz:
http://arxiv.org/abs/2408.09174
Raw Text is All you Need: Knowledge-intensive Multi-turn Instruction Tuning for Large Language Model
Autor:
Hou, Xia, Li, Qifeng, Yang, Jian, Li, Tongliang, Chai, Linzheng, Wu, Xianjie, Ji, Hangyuan, Li, Zhoujun, Nie, Jixuan, Dun, Jingbo, Song, Wenfeng
Instruction tuning as an effective technique aligns the outputs of large language models (LLMs) with human preference. But how to generate the seasonal multi-turn dialogues from raw documents for instruction tuning still requires further exploration.
Externí odkaz:
http://arxiv.org/abs/2407.03040
Autor:
Sun, Tao, Chai, Linzheng, Yang, Jian, Yin, Yuwei, Guo, Hongcheng, Liu, Jiaheng, Wang, Bing, Yang, Liqun, Li, Zhoujun
Intermediate reasoning or acting steps have successfully improved large language models (LLMs) for handling various downstream natural language processing (NLP) tasks. When applying LLMs for code generation, recent works mainly focus on directing the
Externí odkaz:
http://arxiv.org/abs/2406.16441
Autor:
Chai, Linzheng, Liu, Shukai, Yang, Jian, Yin, Yuwei, Jin, Ke, Liu, Jiaheng, Sun, Tao, Zhang, Ge, Ren, Changyu, Guo, Hongcheng, Wang, Zekun, Wang, Boyang, Wu, Xianjie, Wang, Bing, Li, Tongliang, Yang, Liqun, Duan, Sufeng, Li, Zhoujun
Code large language models (LLMs) have shown remarkable advances in code understanding, completion, and generation tasks. Programming benchmarks, comprised of a selection of code challenges and corresponding test cases, serve as a standard to evaluat
Externí odkaz:
http://arxiv.org/abs/2406.07436
Autor:
Ji, Hangyuan, Yang, Jian, Chai, Linzheng, Wei, Chaoren, Yang, Liqun, Duan, Yunlong, Wang, Yunli, Sun, Tianzhen, Guo, Hongcheng, Li, Tongliang, Ren, Changyu, Li, Zhoujun
To address the increasing complexity and frequency of cybersecurity incidents emphasized by the recent cybersecurity threat reports with over 10 billion instances, cyber threat intelligence (CTI) plays a critical role in the modern cybersecurity land
Externí odkaz:
http://arxiv.org/abs/2405.03446
Autor:
Wang, Bing, Ren, Changyu, Yang, Jian, Liang, Xinnian, Bai, Jiaqi, Chai, Linzheng, Yan, Zhao, Zhang, Qian-Wen, Yin, Di, Sun, Xing, Li, Zhoujun
Recent LLM-based Text-to-SQL methods usually suffer from significant performance degradation on "huge" databases and complex user questions that require multi-step reasoning. Moreover, most existing methods neglect the crucial significance of LLMs ut
Externí odkaz:
http://arxiv.org/abs/2312.11242
Autor:
Guo, Hongcheng, Yang, Jian, Liu, Jiaheng, Yang, Liqun, Chai, Linzheng, Bai, Jiaqi, Peng, Junran, Hu, Xiaorong, Chen, Chao, Zhang, Dongfeng, Shi, Xu, Zheng, Tieqiao, Zheng, Liangfan, Zhang, Bo, Xu, Ke, Li, Zhoujun
With the rapid development of IT operations, it has become increasingly crucial to efficiently manage and analyze large volumes of data for practical applications. The techniques of Natural Language Processing (NLP) have shown remarkable capabilities
Externí odkaz:
http://arxiv.org/abs/2309.09298
Autor:
Li, Tongliang, Wang, Zixiang, Chai, Linzheng, Yang, Jian, Bai, Jiaqi, Yin, Yuwei, Liu, Jiaheng, Guo, Hongcheng, Yang, Liqun, el-abidine, Hebboul Zine, Li, Zhoujun
Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages. Previous work uses a shared cross-lingual pre-trained model to handle the different languages but underuses the potential of the
Externí odkaz:
http://arxiv.org/abs/2308.06552
Autor:
Chai, Linzheng, Xiao, Dongling, Yang, Jian, Yang, Liqun, Zhang, Qian-Wen, Cao, Yunbo, Li, Zhoujun, Yan, Zhao
Context-dependent Text-to-SQL aims to translate multi-turn natural language questions into SQL queries. Despite various methods have exploited context-dependence information implicitly for contextual SQL parsing, there are few attempts to explicitly
Externí odkaz:
http://arxiv.org/abs/2305.06655