1 code implementation • Findings (NAACL) 2022 • Xiang Chen, Ningyu Zhang, Lei LI, Yunzhi Yao, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen
Multimodal named entity recognition and relation extraction (MNER and MRE) is a fundamental and crucial branch in information extraction.
1 code implementation • 21 Mar 2024 • Mengru Wang, Ningyu Zhang, Ziwen Xu, Zekun Xi, Shumin Deng, Yunzhi Yao, Qishen Zhang, Linyi Yang, Jindong Wang, Huajun Chen
This paper investigates using knowledge editing techniques to detoxify Large Language Models (LLMs).
no code implementations • 21 Mar 2024 • Zhihao Wang, Yulin Zhou, Ningyu Zhang, Xiaosong Yang, Jun Xiao, Zhao Wang
We believe our work could provide a novel perspective to consider the uncertainty quality for the general motion prediction task and encourage the studies in this field.
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 • 25 Feb 2024 • Ningyu Zhang, Bozhong Tian, Siyuan Cheng, Xiaozhuan Liang, Yi Hu, Kouying Xue, Yanjie Gou, Xi Chen, Huajun Chen
Knowledge editing for large language models can offer an efficient solution to alter a model's behavior without negatively impacting the overall performance.
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).
1 code implementation • 13 Feb 2024 • Yin Fang, Kangwei Liu, Ningyu Zhang, Xinle Deng, Penghui Yang, Zhuo Chen, Xiangru Tang, Mark Gerstein, Xiaohui Fan, Huajun Chen
As Large Language Models (LLMs) rapidly evolve, their influence in science is becoming increasingly prominent.
6 code implementations • 8 Feb 2024 • Zhuo Chen, Yichi Zhang, Yin Fang, Yuxia Geng, Lingbing Guo, Xiang Chen, Qian Li, Wen Zhang, Jiaoyan Chen, Yushan Zhu, Jiaqi Li, Xiaoze Liu, Jeff Z. Pan, Ningyu Zhang, Huajun Chen
In this survey, we carefully review over 300 articles, focusing on KG-aware research in two principal aspects: KG-driven Multi-Modal (KG4MM) learning, where KGs support multi-modal tasks, and Multi-Modal Knowledge Graph (MM4KG), which extends KG studies into the MMKG realm.
3 code implementations • 5 Feb 2024 • Yixin Ou, Ningyu Zhang, Honghao Gui, Ziwen Xu, Shuofei Qiao, Yida Xue, Runnan Fang, Kangwei Liu, Lei LI, Zhen Bi, Guozhou Zheng, Huajun Chen
In recent years, instruction tuning has gained increasing attention and emerged as a crucial technique to enhance the capabilities of Large Language Models (LLMs).
1 code implementation • 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 • 3 Feb 2024 • Long Ma, Jiajia Zhang, Hongping Deng, Ningyu Zhang, Yong Liao, Haiyang Yu
The escalating quality of video generated by advanced video generation methods leads to new security challenges in society, which makes generated video detection an urgent research priority.
1 code implementation • 31 Jan 2024 • Jun-Yu Ma, Jia-Chen Gu, Ningyu Zhang, Zhen-Hua Ling
Despite their exceptional capabilities, large language models (LLMs) are prone to generating unintended text due to false or outdated knowledge.
no code implementations • 30 Jan 2024 • Tiannan Wang, Jiamin Chen, Qingrui Jia, Shuai Wang, Ruoyu Fang, Huilin Wang, Zhaowei Gao, Chunzhao Xie, Chuou Xu, Jihong Dai, Yibin Liu, Jialong Wu, Shengwei Ding, Long Li, Zhiwei Huang, Xinle Deng, Teng Yu, Gangan Ma, Han Xiao, Zixin Chen, Danjun Xiang, Yunxia Wang, Yuanyuan Zhu, Yi Xiao, Jing Wang, Yiru Wang, Siran Ding, Jiayang Huang, Jiayi Xu, Yilihamu Tayier, Zhenyu Hu, Yuan Gao, Chengfeng Zheng, Yueshu Ye, Yihang Li, Lei Wan, Xinyue Jiang, Yujie Wang, Siyu Cheng, Zhule Song, Xiangru Tang, Xiaohua Xu, Ningyu Zhang, Huajun Chen, Yuchen Eleanor Jiang, Wangchunshu Zhou
Weaver is pre-trained on a carefully selected corpus that focuses on improving the writing capabilities of large language models.
1 code implementation • 10 Jan 2024 • Shuofei Qiao, Ningyu Zhang, Runnan Fang, Yujie Luo, Wangchunshu Zhou, Yuchen Eleanor Jiang, Chengfei Lv, Huajun Chen
Further analysis demonstrates the effectiveness of the division-of-labor strategy, with the trajectory quality generated by AutoAct significantly outperforming that of others.
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 • 15 Nov 2023 • Shumin Deng, Ningyu Zhang, Nay Oo, Bryan Hooi
Large Language Models (LLMs) employing Chain-of-Thought (CoT) prompting have broadened the scope for improving multi-step reasoning capabilities.
1 code implementation • 18 Oct 2023 • Xiang Chen, Duanzheng Song, Honghao Gui, Chenxi Wang, Ningyu Zhang, Jiang Yong, Fei Huang, Chengfei Lv, Dan Zhang, Huajun Chen
Despite their impressive generative capabilities, LLMs are hindered by fact-conflicting hallucinations in real-world applications.
1 code implementation • 12 Oct 2023 • Siyuan Cheng, Bozhong Tian, Qingbin Liu, Xi Chen, Yongheng Wang, Huajun Chen, Ningyu Zhang
In this paper, we focus on editing Multimodal Large Language Models (MLLMs).
1 code implementation • 3 Oct 2023 • Jintian Zhang, Xin Xu, Ningyu Zhang, Ruibo Liu, Bryan Hooi, Shumin Deng
This paper probes the collaboration mechanisms among contemporary NLP systems by melding practical experiments with theoretical insights.
1 code implementation • 3 Oct 2023 • Shengyu Mao, Xiaohan Wang, Mengru Wang, Yong Jiang, Pengjun Xie, Fei Huang, Ningyu Zhang
This task seeks to adjust the models' responses to opinion-related questions on specified topics since an individual's personality often manifests in the form of their expressed opinions, thereby showcasing different personality traits.
1 code implementation • 3 Oct 2023 • Zhoubo Li, Ningyu Zhang, Yunzhi Yao, Mengru Wang, Xi Chen, Huajun Chen
This paper pioneers the investigation into the potential pitfalls associated with knowledge editing for LLMs.
1 code implementation • 3 Oct 2023 • Zhen Bi, Ningyu Zhang, Yida Xue, Yixin Ou, Daxiong Ji, Guozhou Zheng, Huajun Chen
Ocean science, which delves into the oceans that are reservoirs of life and biodiversity, is of great significance given that oceans cover over 70% of our planet's surface.
1 code implementation • 2 Oct 2023 • Lei LI, Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian, Ningyu Zhang, Hua Wu
We validate our approach across a wide range of domains, incorporating seven distinct external tools.
1 code implementation • 14 Sep 2023 • Wangchunshu Zhou, Yuchen Eleanor Jiang, Long Li, Jialong Wu, Tiannan Wang, Shi Qiu, Jintian Zhang, Jing Chen, Ruipu Wu, Shuai Wang, Shiding Zhu, Jiyu Chen, Wentao Zhang, Xiangru Tang, Ningyu Zhang, Huajun Chen, Peng Cui, Mrinmaya Sachan
Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language interfaces.
1 code implementation • 29 Aug 2023 • Zhen Bi, Ningyu Zhang, Yinuo Jiang, Shumin Deng, Guozhou Zheng, Huajun Chen
Although there are effective methods like program-of-thought prompting for LLMs which uses programming language to tackle complex reasoning tasks, the specific impact of code data on the improvement of reasoning capabilities remains under-explored.
1 code implementation • 21 Aug 2023 • Tianyu Yu, Chengyue Jiang, Chao Lou, Shen Huang, Xiaobin Wang, Wei Liu, Jiong Cai, Yangning Li, Yinghui Li, Kewei Tu, Hai-Tao Zheng, Ningyu Zhang, Pengjun Xie, Fei Huang, Yong Jiang
However, LLMs are sometimes too footloose for natural language understanding (NLU) tasks which always have restricted output and input format.
2 code implementations • 14 Aug 2023 • Peng Wang, Ningyu Zhang, Bozhong Tian, Zekun Xi, Yunzhi Yao, Ziwen Xu, Mengru Wang, Shengyu Mao, Xiaohan Wang, Siyuan Cheng, Kangwei Liu, Yuansheng Ni, Guozhou Zheng, Huajun Chen
Large Language Models (LLMs) usually suffer from knowledge cutoff or fallacy issues, which means they are unaware of unseen events or generate text with incorrect facts owing to outdated/noisy data.
1 code implementation • 13 Jun 2023 • Yin Fang, Xiaozhuan Liang, Ningyu Zhang, Kangwei Liu, Rui Huang, Zhuo Chen, Xiaohui Fan, Huajun Chen
Large Language Models (LLMs), with their remarkable task-handling capabilities and innovative outputs, have catalyzed significant advancements across a spectrum of fields.
Catalytic activity prediction Chemical-Disease Interaction Extraction +14
1 code implementation • 24 May 2023 • Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun, Yixuan Lai, Qiang Zhang, Huajun Chen
Reasoning system dynamics is one of the most important analytical approaches for many scientific studies.
1 code implementation • 23 May 2023 • Shumin Deng, Shengyu Mao, Ningyu Zhang, Bryan Hooi
Event-centric structured prediction involves predicting structured outputs of events.
1 code implementation • 22 May 2023 • Shuofei Qiao, Honghao Gui, Chengfei Lv, Qianghuai Jia, Huajun Chen, Ningyu Zhang
To meet this need, we propose Tool leaRning wIth exeCution fEedback (TRICE), a two-stage end-to-end framework that enables the model to continually learn through feedback derived from tool execution, thereby learning when and how to use tools effectively.
3 code implementations • 22 May 2023 • Yunzhi Yao, Peng Wang, Bozhong Tian, Siyuan Cheng, Zhoubo Li, Shumin Deng, Huajun Chen, Ningyu Zhang
Our objective is to provide valuable insights into the effectiveness and feasibility of each editing technique, thereby assisting the community in making informed decisions on the selection of the most appropriate method for a specific task or context.
1 code implementation • 22 May 2023 • Yuqi Zhu, Xiaohan Wang, Jing Chen, Shuofei Qiao, Yixin Ou, Yunzhi Yao, Shumin Deng, Huajun Chen, Ningyu Zhang
We engage in experiments across eight diverse datasets, focusing on four representative tasks encompassing entity and relation extraction, event extraction, link prediction, and question-answering, thereby thoroughly exploring LLMs' performance in the domain of construction and inference.
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
Large language models can perform well on general natural language tasks, but their effectiveness is still not optimal for information extraction.
1 code implementation • 15 May 2023 • Xiang Chen, Ningyu Zhang, Jintian Zhang, Xiaohan Wang, Tongtong Wu, Xi Chen, Yongheng Wang, Huajun Chen
Multimodal Knowledge Graph Construction (MKGC) involves creating structured representations of entities and relations using multiple modalities, such as text and images.
1 code implementation • 15 May 2023 • Hongbin Ye, Honghao Gui, Xin Xu, Xi Chen, Huajun Chen, Ningyu Zhang
This necessitates a system that can handle evolving schema automatically to extract information for KGC.
1 code implementation • 15 May 2023 • Yunzhi Yao, Peng Wang, Shengyu Mao, Chuanqi Tan, Fei Huang, Huajun Chen, Ningyu Zhang
Previous studies have revealed that vanilla pre-trained language models (PLMs) lack the capacity to handle knowledge-intensive NLP tasks alone; thus, several works have attempted to integrate external knowledge into PLMs.
2 code implementations • 2 May 2023 • Xin Xu, Yuqi Zhu, Xiaohan Wang, Ningyu Zhang
Scaling language models have revolutionized widespread NLP tasks, yet little comprehensively explored few-shot relation extraction with large language models.
2 code implementations • 18 Apr 2023 • Zhen Bi, Jing Chen, Yinuo Jiang, Feiyu Xiong, Wei Guo, Huajun Chen, Ningyu Zhang
However, large generative language model trained on structured data such as code has demonstrated impressive capability in understanding natural language for structural prediction and reasoning tasks.
1 code implementation • 18 Apr 2023 • Lei LI, Jing Chen, Bozhong Tian, Ningyu Zhang
Pre-trained Language Models (PLMs), as parametric-based eager learners, have become the de-facto choice for current paradigms of Natural Language Processing (NLP).
1 code implementation • 26 Jan 2023 • Yin Fang, Ningyu Zhang, Zhuo Chen, Lingbing Guo, Xiaohui Fan, Huajun Chen
The generation of molecules with desired properties has become increasingly popular, revolutionizing the way scientists design molecular structures and providing valuable support for chemical and drug design.
2 code implementations • 25 Jan 2023 • Siyuan Cheng, Ningyu Zhang, Bozhong Tian, Xi Chen, Qingbing Liu, Huajun Chen
To address this issue, we propose a new task of editing language model-based KG embeddings in this paper.
2 code implementations • 25 Jan 2023 • Xiang Chen, Lei LI, Shuofei Qiao, Ningyu Zhang, Chuanqi Tan, Yong Jiang, Fei Huang, Huajun Chen
Previous typical solutions mainly obtain a NER model by pre-trained language models (PLMs) with data from a rich-resource domain and adapt it to the target domain.
no code implementations • 2 Jan 2023 • Yacheng He, Qianghuai Jia, Lin Yuan, Ruopeng Li, Yixin Ou, Ningyu Zhang
This paper illustrates the technologies of user next intent prediction with a concept knowledge graph.
2 code implementations • 19 Dec 2022 • Shuofei Qiao, Yixin Ou, Ningyu Zhang, Xiang Chen, Yunzhi Yao, Shumin Deng, Chuanqi Tan, Fei Huang, Huajun Chen
Reasoning, as an essential ability for complex problem-solving, can provide back-end support for various real-world applications, such as medical diagnosis, negotiation, etc.
2 code implementations • 14 Nov 2022 • Lei LI, Xiang Chen, Shuofei Qiao, Feiyu Xiong, Huajun Chen, Ningyu Zhang
Multimodal relation extraction is an essential task for knowledge graph construction.
1 code implementation • 23 Oct 2022 • Hongbin Ye, Ningyu Zhang, Hui Chen, Huajun Chen
Our contributions are threefold: (1) We present a detailed, complete taxonomy for the generative KGC methods; (2) We provide a theoretical and empirical analysis of the generative KGC methods; (3) We propose several research directions that can be developed in the future.
2 code implementations • 19 Oct 2022 • Xin Xu, Xiang Chen, Ningyu Zhang, Xin Xie, Xi Chen, Huajun Chen
This paper presents an empirical study to build relation extraction systems in low-resource settings.
1 code implementation • 19 Oct 2022 • Yunzhi Yao, Shengyu Mao, Ningyu Zhang, Xiang Chen, Shumin Deng, Xi Chen, Huajun Chen
With the development of pre-trained language models, many prompt-based approaches to data-efficient knowledge graph construction have been proposed and achieved impressive performance.
2 code implementations • 1 Oct 2022 • Xin Xie, Zhoubo Li, Xiaohan Wang, Zekun Xi, Ningyu Zhang
Knowledge Graphs (KGs) often have two characteristics: heterogeneous graph structure and text-rich entity/relation information.
2 code implementations • 1 Oct 2022 • Ningyu Zhang, Lei LI, Xiang Chen, Xiaozhuan Liang, Shumin Deng, Huajun Chen
Analogical reasoning is fundamental to human cognition and holds an important place in various fields.
1 code implementation • 30 Sep 2022 • Shumin Deng, Chengming Wang, Zhoubo Li, Ningyu Zhang, Zelin Dai, Hehong Chen, Feiyu Xiong, Ming Yan, Qiang Chen, Mosha Chen, Jiaoyan Chen, Jeff Z. Pan, Bryan Hooi, Huajun Chen
We release all the open resources (OpenBG benchmarks) derived from it for the community and report experimental results of KG-centric tasks.
1 code implementation • 7 Sep 2022 • Ruijie Hou, Yanran Li, Ningyu Zhang, Yulin Zhou, Xiaosong Yang, Zhao Wang
Our module can work seamlessly with the existing action classification model.
1 code implementation • 26 Jul 2022 • Zhuo Chen, Yufeng Huang, Jiaoyan Chen, Yuxia Geng, Yin Fang, Jeff Pan, Ningyu Zhang, Wen Zhang
Visual question answering (VQA) often requires an understanding of visual concepts and language semantics, which relies on external knowledge.
Ranked #21 on Visual Question Answering (VQA) on OK-VQA
2 code implementations • 29 May 2022 • Xiang Chen, Lei LI, Ningyu Zhang, Xiaozhuan Liang, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen
Specifically, vanilla prompt learning may struggle to utilize atypical instances by rote during fully-supervised training or overfit shallow patterns with low-shot data.
no code implementations • 27 May 2022 • Siyuan Cheng, Xiaozhuan Liang, Zhen Bi, Huajun Chen, Ningyu Zhang
Existing data-centric methods for protein science generally cannot sufficiently capture and leverage biology knowledge, which may be crucial for many protein tasks.
1 code implementation • 22 May 2022 • Yincen Qu, Ningyu Zhang, Hui Chen, Zelin Dai, Zezhong Xu, Chengming Wang, Xiaoyu Wang, Qiang Chen, Huajun Chen
In addition to formulating the new task, we also release a new Benchmark dataset of Salience Evaluation in E-commerce (BSEE) and hope to promote related research on commonsense knowledge salience evaluation.
1 code implementation • 22 May 2022 • Zhen Bi, Siyuan Cheng, Jing Chen, Xiaozhuan Liang, Feiyu Xiong, Ningyu Zhang
To this end, we propose a new variant of Transformer for knowledge graph representations dubbed Relphormer.
Ranked #3 on Link Prediction on FB15k-237
1 code implementation • 7 May 2022 • Xiang Chen, Ningyu Zhang, Lei LI, Yunzhi Yao, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen
To deal with these issues, we propose a novel Hierarchical Visual Prefix fusion NeTwork (HVPNeT) for visual-enhanced entity and relation extraction, aiming to achieve more effective and robust performance.
1 code implementation • 4 May 2022 • Xiang Chen, Lei LI, Ningyu Zhang, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen
Note that the previous parametric learning paradigm can be viewed as memorization regarding training data as a book and inference as the close-book test.
1 code implementation • 4 May 2022 • Xiang Chen, Ningyu Zhang, Lei LI, Shumin Deng, Chuanqi Tan, Changliang Xu, Fei Huang, Luo Si, Huajun Chen
Since most MKGs are far from complete, extensive knowledge graph completion studies have been proposed focusing on the multimodal entity, relation extraction and link prediction.
1 code implementation • 9 Apr 2022 • Xiaozhuan Liang, Ningyu Zhang, Siyuan Cheng, Zhenru Zhang, Chuanqi Tan, Huajun Chen
Pretrained language models can be effectively stimulated by textual prompts or demonstrations, especially in low-data scenarios.
1 code implementation • 25 Feb 2022 • Wen Zhang, Xiangnan Chen, Zhen Yao, Mingyang Chen, Yushan Zhu, Hongtao Yu, Yufeng Huang, Zezhong Xu, Yajing Xu, Ningyu Zhang, Zonggang Yuan, Feiyu Xiong, Huajun Chen
NeuralKG is an open-source Python-based library for diverse representation learning of knowledge graphs.
no code implementations • 17 Feb 2022 • Yin Fang, Zhuo Chen, Xiaohui Fan, Ningyu Zhang
To enhance the generation and decipherability of purely data-driven models, scholars have integrated biochemical domain knowledge into these molecular study models.
2 code implementations • 16 Feb 2022 • Shumin Deng, Yubo Ma, Ningyu Zhang, Yixin Cao, Bryan Hooi
Information Extraction (IE) seeks to derive structured information from unstructured texts, often facing challenges in low-resource scenarios due to data scarcity and unseen classes.
1 code implementation • 4 Feb 2022 • Xin Xie, Ningyu Zhang, Zhoubo Li, Shumin Deng, Hui Chen, Feiyu Xiong, Mosha Chen, Huajun Chen
Knowledge graph completion aims to address the problem of extending a KG with missing triples.
Ranked #49 on Link Prediction on FB15k-237
no code implementations • 27 Jan 2022 • Hongbin Ye, Ningyu Zhang, Shumin Deng, Xiang Chen, Hui Chen, Feiyu Xiong, Xi Chen, Huajun Chen
Specifically, we develop the ontology transformation based on the external knowledge graph to address the knowledge missing issue, which fulfills and converts structure knowledge to text.
1 code implementation • ICLR 2022 • Ningyu Zhang, Zhen Bi, Xiaozhuan Liang, Siyuan Cheng, Haosen Hong, Shumin Deng, Jiazhang Lian, Qiang Zhang, Huajun Chen
We construct a novel large-scale knowledge graph that consists of GO and its related proteins, and gene annotation texts or protein sequences describe all nodes in the graph.
1 code implementation • 15 Jan 2022 • Yunzhi Yao, Shaohan Huang, Li Dong, Furu Wei, Huajun Chen, Ningyu Zhang
In this work, we propose a simple model, Kformer, which takes advantage of the knowledge stored in PTMs and external knowledge via knowledge injection in Transformer FFN layers.
1 code implementation • 14 Jan 2022 • Peng Wang, Xin Xie, Xiaohan Wang, Ningyu Zhang
Previous knowledge graph embedding approaches usually map entities to representations and utilize score functions to predict the target entities, yet they typically struggle to reason rare or emerging unseen entities.
Ranked #1 on Link Prediction on FB15k-237-ind
1 code implementation • 10 Jan 2022 • Ningyu Zhang, Xin Xu, Liankuan Tao, Haiyang Yu, Hongbin Ye, Shuofei Qiao, Xin Xie, Xiang Chen, Zhoubo Li, Lei LI, Xiaozhuan Liang, Yunzhi Yao, Shumin Deng, Peng Wang, Wen Zhang, Zhenru Zhang, Chuanqi Tan, Qiang Chen, Feiyu Xiong, Fei Huang, Guozhou Zheng, Huajun Chen
We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population.
no code implementations • 2 Dec 2021 • Shumin Deng, Jiacheng Yang, Hongbin Ye, Chuanqi Tan, Mosha Chen, Songfang Huang, Fei Huang, Huajun Chen, Ningyu Zhang
Previous works leverage logical forms to facilitate logical knowledge-conditioned text generation.
no code implementations • 1 Oct 2021 • Hongbin Ye, Ningyu Zhang, Zhen Bi, Shumin Deng, Chuanqi Tan, Hui Chen, Fei Huang, Huajun Chen
Event argument extraction (EAE) is an important task for information extraction to discover specific argument roles.
no code implementations • 17 Sep 2021 • Chengxi Li, Feiyu Gao, Jiajun Bu, Lu Xu, Xiang Chen, Yu Gu, Zirui Shao, Qi Zheng, Ningyu Zhang, Yongpan Wang, Zhi Yu
We inject sentiment knowledge regarding aspects, opinions, and polarities into prompt and explicitly model term relations via constructing consistency and polarity judgment templates from the ground truth triplets.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3
1 code implementation • COLING 2022 • Xiang Chen, Lei LI, Shumin Deng, Chuanqi Tan, Changliang Xu, Fei Huang, Luo Si, Huajun Chen, Ningyu Zhang
Most NER methods rely on extensive labeled data for model training, which struggles in the low-resource scenarios with limited training data.
4 code implementations • ICLR 2022 • Ningyu Zhang, Luoqiu Li, Xiang Chen, Shumin Deng, Zhen Bi, Chuanqi Tan, Fei Huang, Huajun Chen
Large-scale pre-trained language models have contributed significantly to natural language processing by demonstrating remarkable abilities as few-shot learners.
Ranked #1 on Few-Shot Learning on CR
1 code implementation • 20 Aug 2021 • Yushan Zhu, Huaixiao Tou, Wen Zhang, Ganqiang Ye, Hui Chen, Ningyu Zhang, Huajun Chen
In this paper, we address multi-modal pretraining of product data in the field of E-commerce.
1 code implementation • ACL 2021 • Hengyi Zheng, Rui Wen, Xi Chen, Yifan Yang, Yunyan Zhang, Ziheng Zhang, Ningyu Zhang, Bin Qin, Ming Xu, Yefeng Zheng
Joint extraction of entities and relations from unstructured texts is a crucial task in information extraction.
2 code implementations • ACL 2022 • Ningyu Zhang, Mosha Chen, Zhen Bi, Xiaozhuan Liang, Lei LI, Xin Shang, Kangping Yin, Chuanqi Tan, Jian Xu, Fei Huang, Luo Si, Yuan Ni, Guotong Xie, Zhifang Sui, Baobao Chang, Hui Zong, Zheng Yuan, Linfeng Li, Jun Yan, Hongying Zan, Kunli Zhang, Buzhou Tang, Qingcai Chen
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice.
Ranked #1 on Semantic Similarity on CHIP-STS
2 code implementations • 7 Jun 2021 • Ningyu Zhang, Xiang Chen, Xin Xie, Shumin Deng, Chuanqi Tan, Mosha Chen, Fei Huang, Luo Si, Huajun Chen
Specifically, we leverage an encoder module to capture the context information of entities and a U-shaped segmentation module over the image-style feature map to capture global interdependency among triples.
Ranked #4 on Relation Extraction on GDA
1 code implementation • 3 Jun 2021 • Ningyu Zhang, Qianghuai Jia, Shumin Deng, Xiang Chen, Hongbin Ye, Hui Chen, Huaixiao Tou, Gang Huang, Zhao Wang, Nengwei Hua, Huajun Chen
Conceptual graphs, which is a particular type of Knowledge Graphs, play an essential role in semantic search.
no code implementations • NAACL 2021 • Junjie Luo, Xi Chen, Jichao Sun, Yuejia Xiang, Ningyu Zhang, Xiang Wan
Word representations empowered with additional linguistic information have been widely studied and proved to outperform traditional embeddings.
1 code implementation • ACL 2021 • Shumin Deng, Ningyu Zhang, Luoqiu Li, Hui Chen, Huaixiao Tou, Mosha Chen, Fei Huang, Huajun Chen
Most of current methods to ED rely heavily on training instances, and almost ignore the correlation of event types.
1 code implementation • ACL 2021 • Dongfang Lou, Zhilin Liao, Shumin Deng, Ningyu Zhang, Huajun Chen
We consider the problem of collectively detecting multiple events, particularly in cross-sentence settings.
1 code implementation • 12 May 2021 • Zhiyuan Qi, Ziheng Zhang, Jiaoyan Chen, Xi Chen, Yuejia Xiang, Ningyu Zhang, Yefeng Zheng
Knowledge Graph (KG) alignment is to discover the mappings (i. e., equivalent entities, relations, and others) between two KGs.
no code implementations • 20 Apr 2021 • Zhen Bi, Ningyu Zhang, Ganqiang Ye, Haiyang Yu, Xi Chen, Huajun Chen
Recent neural-based aspect-based sentiment analysis approaches, though achieving promising improvement on benchmark datasets, have reported suffering from poor robustness when encountering confounder such as non-target aspects.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)
1 code implementation • 15 Apr 2021 • Xiang Chen, Ningyu Zhang, Xin Xie, Shumin Deng, Yunzhi Yao, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen
To this end, we focus on incorporating knowledge among relation labels into prompt-tuning for relation extraction and propose a Knowledge-aware Prompt-tuning approach with synergistic optimization (KnowPrompt).
Ranked #5 on Dialog Relation Extraction on DialogRE (F1 (v1) metric)
1 code implementation • 11 Apr 2021 • Xiang Chen, Xin Xie, Zhen Bi, Hongbin Ye, Shumin Deng, Ningyu Zhang, Huajun Chen
Although the self-supervised pre-training of transformer models has resulted in the revolutionizing of natural language processing (NLP) applications and the achievement of state-of-the-art results with regard to various benchmarks, this process is still vulnerable to small and imperceptible permutations originating from legitimate inputs.
1 code implementation • NAACL 2021 • Kun Liu, Yao Fu, Chuanqi Tan, Mosha Chen, Ningyu Zhang, Songfang Huang, Sheng Gao
This work studies NER under a noisy labeled setting with calibrated confidence estimation.
1 code implementation • 1 Apr 2021 • Luoqiu Li, Xiang Chen, Zhen Bi, Xin Xie, Shumin Deng, Ningyu Zhang, Chuanqi Tan, Mosha Chen, Huajun Chen
Recent neural-based relation extraction approaches, though achieving promising improvement on benchmark datasets, have reported their vulnerability towards adversarial attacks.
1 code implementation • SEMEVAL 2021 • Xin Xie, Xiangnan Chen, Xiang Chen, Yong Wang, Ningyu Zhang, Shumin Deng, Huajun Chen
This paper presents our systems for the three Subtasks of SemEval Task4: Reading Comprehension of Abstract Meaning (ReCAM).
Ranked #1 on Reading Comprehension on ReCAM (using extra training data)
no code implementations • 1 Jan 2021 • Ningyu Zhang, Xiang Chen, Xin Xie, Shumin Deng, Yantao Jia, Zonggang Yuan, Huajun Chen
Although the self-supervised pre-training of transformer models has resulted in the revolutionizing of natural language processing (NLP) applications and the achievement of state-of-the-art results with regard to various benchmarks, this process is still vulnerable to small and imperceptible permutations originating from legitimate inputs.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Ningyu Zhang, Shumin Deng, Juan Li, Xi Chen, Wei zhang, Huajun Chen
It is desirable to generate answer summaries for online search engines, particularly summaries that can reveal direct answers to questions.
no code implementations • COLING 2020 • Juan Li, Ruoxu Wang, Ningyu Zhang, Wen Zhang, Fan Yang, Huajun Chen
To recognize unseen relations at test time, we explore the problem of zero-shot relation classification.
no code implementations • COLING 2020 • Haiyang Yu, Ningyu Zhang, Shumin Deng, Hongbin Ye, Wei zhang, Huajun Chen
Current supervised relational triple extraction approaches require huge amounts of labeled data and thus suffer from poor performance in few-shot settings.
1 code implementation • EMNLP 2020 • Ningyu Zhang, Shumin Deng, Zhen Bi, Haiyang Yu, Jiacheng Yang, Mosha Chen, Fei Huang, Wei zhang, Huajun Chen
We introduce a prototype model and provide an open-source and extensible toolkit called OpenUE for various extraction tasks.
Ranked #3 on Joint Entity and Relation Extraction on WebNLG
no code implementations • COLING 2022 • Zifeng Wang, Rui Wen, Xi Chen, Shao-Lun Huang, Ningyu Zhang, Yefeng Zheng
Distant supervision (DS) is a strong way to expand the datasets for enhancing relation extraction (RE) models but often suffers from high label noise.
1 code implementation • 15 Sep 2020 • Haiyang Yu, Ningyu Zhang, Shumin Deng, Zonggang Yuan, Yantao Jia, Huajun Chen
Long-tailed relation classification is a challenging problem as the head classes may dominate the training phase, thereby leading to the deterioration of the tail performance.
no code implementations • 14 Sep 2020 • Hongbin Ye, Ningyu Zhang, Shumin Deng, Mosha Chen, Chuanqi Tan, Fei Huang, Huajun Chen
In this paper, we revisit the end-to-end triple extraction task for sequence generation.
Ranked #9 on Relation Extraction on WebNLG
1 code implementation • 14 Sep 2020 • Luoqiu Li, Xiang Chen, Hongbin Ye, Zhen Bi, Shumin Deng, Ningyu Zhang, Huajun Chen
Fine-tuning pre-trained models have achieved impressive performance on standard natural language processing benchmarks.
1 code implementation • 25 Aug 2020 • Ningyu Zhang, Qianghuai Jia, Kangping Yin, Liang Dong, Feng Gao, Nengwei Hua
In this paper, we investigate how the recently introduced pre-trained language model BERT can be adapted for Chinese biomedical corpora and propose a novel conceptualized representation learning approach.
no code implementations • 8 Nov 2019 • Ningyu Zhang, Shumin Deng, Zhanlin Sun, Jiaoayan Chen, Wei zhang, Huajun Chen
Specifically, the framework takes advantage of a relation discriminator to distinguish between samples from different relations, and help learn relation-invariant features more transferable from source relations to target relations.
1 code implementation • 25 Oct 2019 • Shumin Deng, Ningyu Zhang, Jiaojian Kang, Yichi Zhang, Wei zhang, Huajun Chen
Differing from vanilla prototypical networks simply computing event prototypes by averaging, which only consume event mentions once, our model is more robust and is capable of distilling contextual information from event mentions for multiple times due to the multi-hop mechanism of DMNs.
no code implementations • 6 Sep 2019 • Qianghuai Jia, Ningyu Zhang, Nengwei Hua
Entity recommendation, providing search users with an improved experience via assisting them in finding related entities for a given query, has become an indispensable feature of today's search engines.
no code implementations • 22 Aug 2019 • Ningyu Zhang, Shumin Deng, Zhanlin Sun, Jiaoyan Chen, Wei zhang, Huajun Chen
However, the human annotation is expensive, while human-crafted patterns suffer from semantic drift and distant supervision samples are usually noisy.
no code implementations • 22 Aug 2019 • Shumin Deng, Ningyu Zhang, Zhanlin Sun, Jiaoyan Chen, Huajun Chen
Text classification tends to be difficult when data are deficient or when it is required to adapt to unseen classes.
Ranked #1 on Multi-Domain Sentiment Classification on ARSC
no code implementations • NAACL 2019 • Ningyu Zhang, Shumin Deng, Zhanlin Sun, Guanying Wang, Xi Chen, Wei zhang, Huajun Chen
Here, the challenge is to learn accurate "few-shot" models for classes existing at the tail of the class distribution, for which little data is available.
1 code implementation • EMNLP 2018 • Ningyu Zhang, Shumin Deng, Zhanlin Sun, Xi Chen, Wei zhang, Huajun Chen
A capsule is a group of neurons, whose activity vector represents the instantiation parameters of a specific type of entity.