1 code implementation • 2 Jan 2025 • Xinshuo Hu, Zifei Shan, Xinping Zhao, Zetian Sun, Zhenyu Liu, Dongfang Li, Shaolin Ye, Xinyuan Wei, Qian Chen, Baotian Hu, Haofen Wang, Jun Yu, Min Zhang
As retrieval-augmented generation prevails in large language models, embedding models are becoming increasingly crucial.
1 code implementation • 28 Dec 2024 • Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Ningyu Zhang, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, Haofen Wang, Huajun Chen
We introduce OneKE, a dockerized schema-guided knowledge extraction system, which can extract knowledge from the Web and raw PDF Books, and support various domains (science, news, etc.).
1 code implementation • 24 Dec 2024 • Xinping Zhao, Baotian Hu, Yan Zhong, Shouzheng Huang, Zihao Zheng, Meng Wang, Haofen Wang, Min Zhang
Although prevailing supervised and self-supervised learning (SSL)-augmented sequential recommendation (SeRec) models have achieved improved performance with powerful neural network architectures, we argue that they still suffer from two limitations: (1) Preference Drift, where models trained on past data can hardly accommodate evolving user preference; and (2) Implicit Memory, where head patterns dominate parametric learning, making it harder to recall long tails.
Ranked #2 on
Sequential Recommendation
on Amazon-Sports
1 code implementation • 24 Nov 2024 • Siqi Wang, Chao Liang, Yunfan Gao, Yang Liu, Jing Li, Haofen Wang
Industrial parks are critical to urban economic growth.
no code implementations • 27 Oct 2024 • Tianlin Guo, Lingling Zhang, Jiaxin Wang, Yuokuo Lei, Yifei Li, Haofen Wang, Jun Liu
FsRE with NOTA is more challenging than the conventional few-shot relation extraction task, since the boundaries of unknown classes are complex and difficult to learn.
no code implementations • 26 Jul 2024 • Yunfan Gao, Yun Xiong, Meng Wang, Haofen Wang
Retrieval-augmented Generation (RAG) has markedly enhanced the capabilities of Large Language Models (LLMs) in tackling knowledge-intensive tasks.
no code implementations • 1 Jul 2024 • Xin Wang, Zirui Chen, Haofen Wang, Leong Hou U, Zhao Li, Wenbin Guo
The integration of Large Language Models (LLM) with Knowledge Representation Learning (KRL) signifies a significant advancement in the field of artificial intelligence (AI), enhancing the ability to capture and utilize both structure and textual information.
no code implementations • 24 Jun 2024 • Mianxin Liu, Jinru Ding, Jie Xu, Weiguo Hu, Xiaoyang Li, Lifeng Zhu, Zhian Bai, Xiaoming Shi, Benyou Wang, Haitao Song, PengFei Liu, Xiaofan Zhang, Shanshan Wang, Kang Li, Haofen Wang, Tong Ruan, Xuanjing Huang, Xin Sun, Shaoting Zhang
In this work, we introduce "MedBench", a comprehensive, standardized, and reliable benchmarking system for Chinese medical LLM.
no code implementations • 20 Jun 2024 • Huifang Du, Shuqin Li, Minghao Wu, Xuejing Feng, Yuan-Fang Li, Haofen Wang
Reinforcement learning (RL) is a powerful approach to enhance task-oriented dialogue (TOD) systems.
no code implementations • 3 Apr 2024 • Yanpeng Ye, Jie Ren, Shaozhou Wang, Yuwei Wan, Haofen Wang, Imran Razzak, Bram Hoex, Tong Xie, Wenjie Zhang
By implementing network-based algorithms, MKG not only facilitates efficient link prediction but also significantly reduces reliance on traditional experimental methods.
1 code implementation • 20 Feb 2024 • Nailei Hei, Qianyu Guo, ZiHao Wang, Yan Wang, Haofen Wang, Wenqiang Zhang
To bridge the distribution gap between user input behavior and model training datasets, we first construct a novel Coarse-Fine Granularity Prompts dataset (CFP) and propose a novel User-Friendly Fine-Grained Text Generation framework (UF-FGTG) for automated prompt optimization.
1 code implementation • 16 Jan 2024 • Wei Tao, Yucheng Zhou, Yanlin Wang, Hongyu Zhang, Haofen Wang, Wenqiang Zhang
However, previous methods are trained on the entire dataset without considering the fact that a portion of commit messages adhere to good practice (i. e., good-practice commits), while the rest do not.
4 code implementations • 18 Dec 2023 • Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Meng Wang, Haofen Wang
Large Language Models (LLMs) showcase impressive capabilities but encounter challenges like hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes.
no code implementations • 14 Oct 2023 • Qianyu Guo, Huifang Du, Xing Jia, Shuyong Gao, Yan Teng, Haofen Wang, Wenqiang Zhang
Finally, the generated features and prototypes are together to train a more generalized classifier.
no code implementations • 25 Mar 2023 • Yunfan Gao, Tao Sheng, Youlin Xiang, Yun Xiong, Haofen Wang, Jiawei Zhang
Large language models (LLMs) have demonstrated their significant potential to be applied for addressing various application tasks.
1 code implementation • 8 Jun 2022 • Xi Chen, Yun Xiong, Siqi Wang, Haofen Wang, Tao Sheng, Yao Zhang, Yu Ye
In order to address the issues and advance a benchmark dataset for various intelligent spatial design and analysis applications in the development of smart city, we introduce Residential Community Layout Planning (ReCo) Dataset, which is the first and largest open-source vector dataset related to real-world community to date.
no code implementations • 18 Mar 2022 • Jun Liu, Tong Ruan, Haofen Wang, Huanhuan Zhang
The dialogue state tracking (DST) module in the medical dialogue system which interprets utterances into the machine-readable structure for downstream tasks is particularly challenging.
1 code implementation • 13 Sep 2020 • Xinyue Zhang, Meng Wang, Muhammad Saleem, Axel-Cyrille Ngonga Ngomo, Guilin Qi, Haofen Wang
Based on Semantic Web technologies, knowledge graphs help users to discover information of interest by using live SPARQL services.
no code implementations • 16 Jan 2018 • YaoSheng Yang, Meishan Zhang, Wenliang Chen, Wei zhang, Haofen Wang, Min Zhang
To quickly obtain new labeled data, we can choose crowdsourcing as an alternative way at lower cost in a short time.
Chinese Named Entity Recognition
named-entity-recognition
+2
no code implementations • 16 Oct 2017 • Fang Gong, Meng Wang, Haofen Wang, Sen Wang, Mengyue Liu
To our best knowledge, SMR is the first to learn embeddings of a patient-disease-medicine graph for medicine recommendation in the world.
no code implementations • 16 Oct 2015 • Chenhao Zhu, Kan Ren, Xuan Liu, Haofen Wang, Yiding Tian, Yong Yu
We present a question answering system over DBpedia, filling the gap between user information needs expressed in natural language and a structured query interface expressed in SPARQL over the underlying knowledge base (KB).