no code implementations • 22 May 2024 • Wei zhang, Xianfu Cheng, Yi Zhang, Jian Yang, Hongcheng Guo, Zhoujun Li, Xiaolin Yin, Xiangyuan Guan, Xu Shi, Liangfan Zheng, Bo Zhang
These challenges are two-fold: 1) massive log templates: The performance and efficiency of most existing parsers will be significantly reduced when logs of growing quantities and different lengths; 2) Complex and changeable semantics: Traditional template-matching algorithms cannot accurately match the log templates of complicated industrial logs because they cannot utilize cross-language logs with similar semantics.
no code implementations • 26 Mar 2024 • Jian Yang, Hongcheng Guo, Yuwei Yin, Jiaqi Bai, Bing Wang, Jiaheng Liu, Xinnian Liang, Linzheng Cahi, Liqun Yang, Zhoujun Li
Our method aims to minimize the representation distance of different languages by regarding the image as a central language.
1 code implementation • 28 Feb 2024 • Wei zhang, Hongcheng Guo, Anjie Le, Jian Yang, Jiaheng Liu, Zhoujun Li, Tieqiao Zheng, Shi Xu, Runqiang Zang, Liangfan Zheng, Bo Zhang
Log parsing, which entails transforming raw log messages into structured templates, constitutes a critical phase in the automation of log analytics.
no code implementations • 15 Jan 2024 • Runqiang Zang, Hongcheng Guo, Jian Yang, Jiaheng Liu, Zhoujun Li, Tieqiao Zheng, Xu Shi, Liangfan Zheng, Bo Zhang
In spite of the rapid advancements in unsupervised log anomaly detection techniques, the current mainstream models still necessitate specific training for individual system datasets, resulting in costly procedures and limited scalability due to dataset size, thereby leading to performance bottlenecks.
no code implementations • 13 Jan 2024 • Linzheng Chai, Jian Yang, Tao Sun, Hongcheng Guo, Jiaheng Liu, Bing Wang, Xiannian Liang, Jiaqi Bai, Tongliang Li, Qiyao Peng, Zhoujun Li
To bridge the gap among different languages, we propose a cross-lingual instruction fine-tuning framework (xCOT) to transfer knowledge from high-resource languages to low-resource languages.
1 code implementation • 9 Jan 2024 • Hongcheng Guo, Jian Yang, Jiaheng Liu, Jiaqi Bai, Boyang Wang, Zhoujun Li, Tieqiao Zheng, Bo Zhang, Junran Peng, Qi Tian
Log anomaly detection is a key component in the field of artificial intelligence for IT operations (AIOps).
1 code implementation • 26 Oct 2023 • Hongcheng Guo, Boyang Wang, Jiaqi Bai, Jiaheng Liu, Jian Yang, Zhoujun Li
In other words, the Multimodal Manga Complement (M2C) task has not been investigated, which aims to handle the aforementioned issues by providing a shared semantic space for vision and language understanding.
1 code implementation • 1 Oct 2023 • Zekun Moore Wang, Zhongyuan Peng, Haoran Que, Jiaheng Liu, Wangchunshu Zhou, Yuhan Wu, Hongcheng Guo, Ruitong Gan, Zehao Ni, Jian Yang, Man Zhang, Zhaoxiang Zhang, Wanli Ouyang, Ke Xu, Stephen W. Huang, Jie Fu, Junran Peng
The advent of Large Language Models (LLMs) has paved the way for complex tasks such as role-playing, which enhances user interactions by enabling models to imitate various characters.
no code implementations • 17 Sep 2023 • Hongcheng Guo, Jian Yang, Jiaheng Liu, Liqun Yang, Linzheng Chai, Jiaqi Bai, Junran Peng, Xiaorong Hu, Chao Chen, Dongfeng Zhang, Xu Shi, Tieqiao Zheng, Liangfan Zheng, Bo Zhang, Ke Xu, Zhoujun Li
However, there is a lack of specialized LLMs for IT operations.
2 code implementations • 12 Aug 2023 • Tongliang Li, Zixiang Wang, Linzheng Chai, Jian Yang, Jiaqi Bai, Yuwei Yin, Jiaheng Liu, Hongcheng Guo, Liqun Yang, Hebboul Zine el-abidine, Zhoujun Li
Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages.
1 code implementation • 27 Jun 2023 • Jiaqi Bai, Zhao Yan, Jian Yang, Xinnian Liang, Hongcheng Guo, Zhoujun Li
We propose Knowledgeable Prefix Tuning (KnowPrefix-Tuning), a two-stage tuning framework, bypassing the retrieval process in a knowledge-grounded conversation system by injecting prior knowledge into the lightweight knowledge prefix.
no code implementations • 29 May 2023 • Jiaqi Bai, Hongcheng Guo, Jiaheng Liu, Jian Yang, Xinnian Liang, Zhao Yan, Zhoujun Li
However, the retrieved passages are not ideal for guiding answer generation because of the discrepancy between retrieval and generation, i. e., the candidate passages are all treated equally during the retrieval procedure without considering their potential to generate a proper answer.
no code implementations • 17 Jan 2023 • Jian Yang, Yuwei Yin, Shuming Ma, Liqun Yang, Hongcheng Guo, Haoyang Huang, Dongdong Zhang, Yutao Zeng, Zhoujun Li, Furu Wei
Context-aware neural machine translation aims to use the document-level context to improve translation quality.
no code implementations • 17 Nov 2022 • Jiaheng Liu, Tong He, Honghui Yang, Rui Su, Jiayi Tian, Junran Wu, Hongcheng Guo, Ke Xu, Wanli Ouyang
Previous top-performing methods for 3D instance segmentation often maintain inter-task dependencies and the tendency towards a lack of robustness.
no code implementations • 19 Oct 2022 • Hongcheng Guo, Jiaheng Liu, Haoyang Huang, Jian Yang, Zhoujun Li, Dongdong Zhang, Zheng Cui, Furu Wei
To this end, we first propose the Multilingual MMT task by establishing two new Multilingual MMT benchmark datasets covering seven languages.
1 code implementation • 13 Oct 2022 • Jian Yang, Shaohan Huang, Shuming Ma, Yuwei Yin, Li Dong, Dongdong Zhang, Hongcheng Guo, Zhoujun Li, Furu Wei
Specifically, the target sequence is first translated into the source language and then tagged by a source NER model.
no code implementations • 23 Aug 2022 • Hongcheng Guo, Yuhui Guo, Renjie Chen, Jian Yang, Jiaheng Liu, Zhoujun Li, Tieqiao Zheng, Weichao Hou, Liangfan Zheng, Bo Zhang
Experiments on five benchmarks validate the effectiveness of LogLG for detecting anomalies on unlabeled log data and demonstrate that LogLG, as the state-of-the-art weakly supervised method, achieves significant performance improvements compared to existing methods.
1 code implementation • 11 Jul 2022 • Jian Yang, Yuwei Yin, Shuming Ma, Dongdong Zhang, Shuangzhi Wu, Hongcheng Guo, Zhoujun Li, Furu Wei
Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable.
no code implementations • 31 Dec 2021 • Hongcheng Guo, Xingyu Lin, Jian Yang, Yi Zhuang, Jiaqi Bai, Tieqiao Zheng, Bo Zhang, Zhoujun Li
Therefore, we propose a unified Transformer-based framework for log anomaly detection (\ourmethod{}), which is comprised of the pretraining and adapter-based tuning stage.