1 code implementation • 11 Nov 2024 • Zhiqiang Liu, Mingyang Chen, Yin Hua, Zhuo Chen, Ziqi Liu, Lei Liang, Huajun Chen, Wen Zhang
Experimental results across 7 datasets from 3 types of KGs demonstrate that our UniHR outperforms baselines designed for one specific kind of KG, indicating strong generalization capability of HiDR form and the effectiveness of HiSL module.
1 code implementation • 10 Sep 2024 • Lei Liang, Mengshu Sun, Zhengke Gui, Zhongshu Zhu, Zhouyu Jiang, Ling Zhong, Yuan Qu, Peilong Zhao, Zhongpu Bo, Jin Yang, Huaidong Xiong, Lin Yuan, Jun Xu, Zaoyang Wang, Zhiqiang Zhang, Wen Zhang, Huajun Chen, WenGuang Chen, Jun Zhou
The recently developed retrieval-augmented generation (RAG) technology has enabled the efficient construction of domain-specific applications.
1 code implementation • 9 Sep 2024 • Ningyu Zhang, Zekun Xi, Yujie Luo, Peng Wang, Bozhong Tian, Yunzhi Yao, Jintian Zhang, Shumin Deng, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen
Knowledge representation has been a central aim of AI since its inception.
1 code implementation • 8 Sep 2024 • Jintian Zhang, Cheng Peng, Mengshu Sun, Xiang Chen, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen, Ningyu Zhang
This paper introduces a novel and efficient One-pass Generation and retrieval framework (OneGen), designed to improve LLMs' performance on tasks that require both generation and retrieval.
no code implementations • 22 Aug 2024 • Xiaohan Wang, Xiaoyan Yang, Yuqi Zhu, Yue Shen, Jian Wang, Peng Wei, Lei Liang, Jinjie Gu, Huajun Chen, Ningyu Zhang
Large Language Models (LLMs) like GPT-4, MedPaLM-2, and Med-Gemini achieve performance competitively with human experts across various medical benchmarks.
no code implementations • 18 Jul 2024 • Zhouyu Jiang, Mengshu Sun, Lei Liang, Zhiqiang Zhang
Multi-hop question answering is a challenging task with distinct industrial relevance, and Retrieval-Augmented Generation (RAG) methods based on large language models (LLMs) have become a popular approach to tackle this task.
no code implementations • 3 Jul 2024 • Yushan Zhu, Wen Zhang, Zhiqiang Liu, Mingyang Chen, Lei Liang, Huajun Chen
Knowledge Graph Embedding (KGE) is a common method for Knowledge Graphs (KGs) to serve various artificial intelligence tasks.
no code implementations • 27 Jun 2024 • Wen Zhang, Long Jin, Yushan Zhu, Jiaoyan Chen, Zhiwei Huang, Junjie Wang, Yin Hua, Lei Liang, Huajun Chen
In this paper, we propose UnifiedTQA, a trustful QA framework that can simultaneously support multiple types of structured data in a unified way.
no code implementations • 30 May 2024 • Chunjing Gan, Dan Yang, Binbin Hu, Hanxiao Zhang, Siyuan Li, Ziqi Liu, Yue Shen, Lin Ju, Zhiqiang Zhang, Jinjie Gu, Lei Liang, Jun Zhou
In recent years, large language models (LLMs) have made remarkable achievements in various domains.
1 code implementation • 21 May 2024 • Yichi Zhang, Binbin Hu, Zhuo Chen, Lingbing Guo, Ziqi Liu, Zhiqiang Zhang, Lei Liang, Huajun Chen, Wen Zhang
In response to the lack of open-source benchmarks, we constructed a new multi-domain KGP benchmark called KPI with two large-scale KGs and six different sub-domain tasks to evaluate our method and open-sourced it for subsequent research.
no code implementations • 15 Apr 2024 • Siyuan Li, Youshao Xiao, Fanzhuang Meng, Lin Ju, Lei Liang, Lin Wang, Jun Zhou
Offline batch inference is a common task in the industry for deep learning applications, but it can be challenging to ensure stability and performance when dealing with large amounts of data and complicated inference pipelines.
no code implementations • 15 Apr 2024 • Youshao Xiao, Lin Ju, Zhenglei Zhou, Siyuan Li, ZhaoXin Huan, Dalong Zhang, Rujie Jiang, Lin Wang, Xiaolu Zhang, Lei Liang, Jun Zhou
Previous works only address part of the stragglers and could not adaptively solve various stragglers in practice.
no code implementations • 19 Mar 2024 • Zezhong Xu, Peng Ye, Lei Liang, Huajun Chen, Wen Zhang
Answering logical queries on knowledge graphs (KG) poses a significant challenge for machine reasoning.
no code implementations • 19 Mar 2024 • Zezhong Xu, Yincen Qu, Wen Zhang, Lei Liang, Huajun Chen
This homogenization limits the precise exploitation of knowledge graph data and interest connectivity.
1 code implementation • 10 Mar 2024 • Xiaohan Wang, Shengyu Mao, Ningyu Zhang, Shumin Deng, Yunzhi Yao, Yue Shen, Lei Liang, Jinjie Gu, Huajun Chen
Recently, there has been a growing interest in knowledge editing for Large Language Models (LLMs).
1 code implementation • 5 Mar 2024 • Yuqi Zhu, Shuofei Qiao, Yixin Ou, Shumin Deng, Ningyu Zhang, Shiwei Lyu, Yue Shen, Lei Liang, Jinjie Gu, Huajun Chen
Large Language Models (LLMs) have demonstrated great potential in complex reasoning tasks, yet they fall short when tackling more sophisticated challenges, especially when interacting with environments through generating executable actions.
1 code implementation • 22 Feb 2024 • Yichi Zhang, Zhuo Chen, Lei Liang, Huajun Chen, Wen Zhang
To address the mentioned problems, we propose Adaptive Multi-modal Fusion and Modality Adversarial Training (AdaMF-MAT) to unleash the power of imbalanced modality information for MMKGC.
1 code implementation • 22 Feb 2024 • Honghao Gui, Lin Yuan, Hongbin Ye, Ningyu Zhang, Mengshu Sun, Lei Liang, Huajun Chen
Large Language Models (LLMs) demonstrate remarkable potential across various domains; however, they exhibit a significant performance gap in Information Extraction (IE).
2 code implementations • 5 Feb 2024 • Xiang Chen, Chenxi Wang, Yida Xue, Ningyu Zhang, Xiaoyan Yang, Qiang Li, Yue Shen, Lei Liang, Jinjie Gu, Huajun Chen
Despite significant strides in multimodal tasks, Multimodal Large Language Models (MLLMs) are plagued by the critical issue of hallucination.
no code implementations • 6 Jan 2024 • Zhongshu Zhu, Bin Jing, Xiaopei Wan, Zhizhen Liu, Lei Liang, Jun Zhou
As a powerful tool for modeling graph data, Graph Neural Networks (GNNs) have received increasing attention in both academia and industry.
2 code implementations • 2 Jan 2024 • Ningyu Zhang, Yunzhi Yao, Bozhong Tian, Peng Wang, Shumin Deng, Mengru Wang, Zekun Xi, Shengyu Mao, Jintian Zhang, Yuansheng Ni, Siyuan Cheng, Ziwen Xu, Xin Xu, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen
In this paper, we first define the knowledge editing problem and then provide a comprehensive review of cutting-edge approaches.
Ranked #1 on knowledge editing on zsRE (using extra training data)
no code implementations • 19 Dec 2023 • Youshao Xiao, Zhenglei Zhou, Fagui Mao, Weichang Wu, Shangchun Zhao, Lin Ju, Lei Liang, Xiaolu Zhang, Jun Zhou
To address these issues, we propose a flexible model placement framework that offers two general and agile model placement strategies.
no code implementations • 9 Oct 2023 • Chan Wu, Hanxiao Zhang, Lin Ju, Jinjing Huang, Youshao Xiao, ZhaoXin Huan, Siyuan Li, Fanzhuang Meng, Lei Liang, Xiaolu Zhang, Jun Zhou
In this paper, we rethink the impact of memory consumption and communication costs on the training speed of large language models, and propose a memory-communication balanced strategy set Partial Redundancy Optimizer (PaRO).
3 code implementations • 19 May 2023 • Honghao Gui, Shuofei Qiao, Jintian Zhang, Hongbin Ye, Mengshu Sun, Lei Liang, Jeff Z. Pan, Huajun Chen, Ningyu Zhang
Experimental results demonstrate that large language models trained with InstructIE can not only obtain better IE capabilities but also enhance zero-shot performance compared with baselines.
no code implementations • 12 Jun 2021 • Lei Liang, Xuan Zhang, Hongbin Sun
Besides, in the Virtual Power Plant (VPP) system, the demand response of clustered GHP systems can improve the operating flexibility of the power grid.
no code implementations • 26 Apr 2020 • Keyu Yang, Yunjun Gao, Lei Liang, Song Bian, Lu Chen, Baihua Zheng
We propose Crowd-based neural networks for Text Sentiment Classification (CrowdTSC for short).