Search Results for author: Ningyu Zhang

Found 109 papers, 85 papers with code

Existence Is Chaos: Enhancing 3D Human Motion Prediction with Uncertainty Consideration

no code implementations21 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.

Decoder Human motion prediction +1

Detoxifying Large Language Models via Knowledge Editing

1 code implementation21 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).

knowledge editing

Editing Conceptual Knowledge for Large Language Models

1 code implementation10 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).

knowledge editing

KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents

1 code implementation5 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.

Hallucination Self-Learning

InstructEdit: Instruction-based Knowledge Editing for Large Language Models

1 code implementation25 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.

knowledge editing

IEPile: Unearthing Large-Scale Schema-Based Information Extraction Corpus

1 code implementation22 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).

Zero-shot Generalization

ChatCell: Facilitating Single-Cell Analysis with Natural Language

1 code implementation13 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.

Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

6 code implementations8 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.

Entity Alignment Image Classification +4

EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models

3 code implementations5 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).

Unified Hallucination Detection for Multimodal Large Language Models

1 code implementation5 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.

Hallucination

DeCoF: Generated Video Detection via Frame Consistency

no code implementations3 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.

Video Generation

Neighboring Perturbations of Knowledge Editing on Large Language Models

1 code implementation31 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.

knowledge editing

AUTOACT: Automatic Agent Learning from Scratch via Self-Planning

1 code implementation10 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.

Question Answering

Towards A Unified View of Answer Calibration for Multi-Step Reasoning

no code implementations15 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.

FactCHD: Benchmarking Fact-Conflicting Hallucination Detection

1 code implementation18 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.

Benchmarking Hallucination

Unveiling the Pitfalls of Knowledge Editing for Large Language Models

1 code implementation3 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.

knowledge editing

Editing Personality for Large Language Models

1 code implementation3 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.

Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View

1 code implementation3 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.

Navigate

OceanGPT: A Large Language Model for Ocean Science Tasks

1 code implementation3 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.

Language Modelling Large Language Model

Tool-Augmented Reward Modeling

1 code implementation2 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.

Agents: An Open-source Framework for Autonomous Language Agents

1 code implementation14 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.

When Do Program-of-Thoughts Work for Reasoning?

1 code implementation29 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.

Code Generation Mathematical Reasoning

EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models

2 code implementations14 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.

knowledge editing

Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

1 code implementation13 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

Newton-Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems

1 code implementation24 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.

Making Language Models Better Tool Learners with Execution Feedback

1 code implementation22 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.

Language Modelling Large Language Model +1

Editing Large Language Models: Problems, Methods, and Opportunities

2 code implementations22 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.

Model Editing

LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

1 code implementation22 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.

Event Extraction graph construction +4

InstructIE: A Bilingual Instruction-based Information Extraction Dataset

3 code implementations19 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.

Schema-adaptable Knowledge Graph Construction

1 code implementation15 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.

graph construction UIE

Knowledge Rumination for Pre-trained Language Models

1 code implementation15 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.

Language Modelling

Continual Multimodal Knowledge Graph Construction

1 code implementation15 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.

Continual Learning graph construction +1

How to Unleash the Power of Large Language Models for Few-shot Relation Extraction?

2 code implementations2 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.

In-Context Learning Language Modelling +3

Revisiting k-NN for Fine-tuning Pre-trained Language Models

1 code implementation18 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).

CodeKGC: Code Language Model for Generative Knowledge Graph Construction

2 code implementations18 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.

Code Completion graph construction +1

Domain-Agnostic Molecular Generation with Chemical Feedback

1 code implementation26 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.

Language Modelling Molecular Docking +1

Editing Language Model-based Knowledge Graph Embeddings

2 code implementations25 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.

EDIT Task knowledge editing +2

One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NER

2 code implementations25 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.

NER Text Generation

A Concept Knowledge Graph for User Next Intent Prediction at Alipay

no code implementations2 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.

Reasoning with Language Model Prompting: A Survey

2 code implementations19 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.

Arithmetic Reasoning Common Sense Reasoning +4

Generative Knowledge Graph Construction: A Review

1 code implementation23 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.

graph construction Knowledge Graphs

Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction

1 code implementation19 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.

Event Extraction graph construction +2

LambdaKG: A Library for Pre-trained Language Model-Based Knowledge Graph Embeddings

2 code implementations1 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.

Graph Representation Learning Knowledge Graph Embeddings +3

LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection

1 code implementation26 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.

Decoder Knowledge Graphs +3

Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning

2 code implementations29 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.

Few-Shot Text Classification Memorization +5

Multi-modal Protein Knowledge Graph Construction and Applications

no code implementations27 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.

graph construction

Commonsense Knowledge Salience Evaluation with a Benchmark Dataset in E-commerce

1 code implementation22 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.

Good Visual Guidance Makes A Better Extractor: Hierarchical Visual Prefix for Multimodal Entity and Relation Extraction

1 code implementation7 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.

named-entity-recognition Named Entity Recognition +3

Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion

1 code implementation4 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.

Information Retrieval Link Prediction +4

Relation Extraction as Open-book Examination: Retrieval-enhanced Prompt Tuning

1 code implementation4 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.

Few-Shot Learning Memorization +3

Contrastive Demonstration Tuning for Pre-trained Language Models

1 code implementation9 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.

Knowledge-informed Molecular Learning: A Survey on Paradigm Transfer

no code implementations17 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.

Molecular Property Prediction Property Prediction

Information Extraction in Low-Resource Scenarios: Survey and Perspective

2 code implementations16 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.

Ontology-enhanced Prompt-tuning for Few-shot Learning

no code implementations27 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.

Event Extraction Few-Shot Learning +1

OntoProtein: Protein Pretraining With Gene Ontology Embedding

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.

Contrastive Learning Knowledge Graphs +2

Kformer: Knowledge Injection in Transformer Feed-Forward Layers

1 code implementation15 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.

Language Modelling Question Answering

Reasoning Through Memorization: Nearest Neighbor Knowledge Graph Embeddings

1 code implementation14 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.

Knowledge Graph Embedding Knowledge Graph Embeddings +2

Learning to Ask for Data-Efficient Event Argument Extraction

no code implementations1 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.

Event Argument Extraction

SentiPrompt: Sentiment Knowledge Enhanced Prompt-Tuning for Aspect-Based Sentiment Analysis

no code implementations17 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

Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners

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.

Language Modelling Prompt Engineering

Document-level Relation Extraction as Semantic Segmentation

2 code implementations7 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.

Document-level Relation Extraction Relation +2

Field Embedding: A Unified Grain-Based Framework for Word Representation

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.

Word Embeddings

Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embedding

1 code implementation12 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.

Interventional Aspect-Based Sentiment Analysis

no code implementations20 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)

KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction

1 code implementation15 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)

Dialog Relation Extraction Language Modelling +3

Disentangled Contrastive Learning for Learning Robust Textual Representations

1 code implementation11 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.

Contrastive Learning

Normal vs. Adversarial: Salience-based Analysis of Adversarial Samples for Relation Extraction

1 code implementation1 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.

Relation Relation Extraction

Towards Robust Textual Representations with Disentangled Contrastive Learning

no code implementations1 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.

Contrastive Learning

Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot Relational Triple Extraction

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.

Finding Influential Instances for Distantly Supervised Relation Extraction

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.

Relation Relation Extraction

The Devil is the Classifier: Investigating Long Tail Relation Classification with Decoupling Analysis

1 code implementation15 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.

General Classification Relation +1

On Robustness and Bias Analysis of BERT-based Relation Extraction

1 code implementation14 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.

counterfactual Relation +1

Conceptualized Representation Learning for Chinese Biomedical Text Mining

1 code implementation25 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.

Language Modelling Representation Learning

Relation Adversarial Network for Low Resource Knowledge Graph Completion

no code implementations8 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.

Link Prediction Partial Domain Adaptation +2

Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection

1 code implementation25 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.

Event Detection Event Extraction +2

Context-aware Deep Model for Entity Recommendation in Search Engine at Alibaba

no code implementations6 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.

Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning

no code implementations22 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.

Partial Domain Adaptation Relation +2

Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks

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.

Knowledge Graph Embeddings Relation +1

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