Search Results for author: Haofen Wang

Found 22 papers, 9 papers with code

KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model

1 code implementation2 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.

OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System

1 code implementation28 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.).

RaSeRec: Retrieval-Augmented Sequential Recommendation

1 code implementation24 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.

Retrieval +2

Few-shot Open Relation Extraction with Gaussian Prototype and Adaptive Margin

no code implementations27 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.

Contrastive Learning Meta-Learning +3

Modular RAG: Transforming RAG Systems into LEGO-like Reconfigurable Frameworks

no code implementations26 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.

RAG Scheduling

Large Language Model Enhanced Knowledge Representation Learning: A Survey

no code implementations1 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.

Language Modeling Language Modelling +3

Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model

no code implementations3 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.

Knowledge Graphs Language Modeling +2

A User-Friendly Framework for Generating Model-Preferred Prompts in Text-to-Image Synthesis

1 code implementation20 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.

Image Generation Prompt Engineering +1

KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation

1 code implementation16 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.

Denoising

Retrieval-Augmented Generation for Large Language Models: A Survey

4 code implementations18 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.

Hallucination RAG +2

Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System

no code implementations25 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.

In-Context Learning Recommendation Systems

ReCo: A Dataset for Residential Community Layout Planning

1 code implementation8 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.

Generative Adversarial Network Layout Design

Prompt-based Generative Approach towards Multi-Hierarchical Medical Dialogue State Tracking

no code implementations18 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.

Dialogue State Tracking

Revealing Secrets in SPARQL Session Level

1 code implementation13 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.

Knowledge Graphs

SMR: Medical Knowledge Graph Embedding for Safe Medicine Recommendation

no code implementations16 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.

Knowledge Graph Embedding Knowledge Graphs +2

A Graph Traversal Based Approach to Answer Non-Aggregation Questions Over DBpedia

no code implementations16 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).

Question Answering

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