Peng Wang

About Peng Wang

Peng Wang, With an exceptional h-index of 19 and a recent h-index of 14 (since 2020), a distinguished researcher at Southeast University, specializes in the field of Knowledge Graph, Large Language Model, Deep Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Unify Named Entity Recognition Scenarios via Contrastive Real-Time Updating Prototype

Unlocking Instructive In-Context Learning with Tabular Prompting for Relational Triple Extraction

MDM: Meta diffusion model for hard-constrained text generation

A comprehensive study of knowledge editing for large language models

Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors

Boosting LLMS with Ontology-Aware Prompt for Ner Data Augmentation

AdaptiveUKE: Towards adaptive unsupervised keyphrase extraction with gated topic modeling

ConsistNER: Towards Instructive NER Demonstrations for LLMs with the Consistency of Ontology and Context

Peng Wang Information

University

Position

School of Computer Science and Engineering

Citations(all)

2188

Citations(since 2020)

1169

Cited By

1644

hIndex(all)

19

hIndex(since 2020)

14

i10Index(all)

44

i10Index(since 2020)

21

Email

University Profile Page

Google Scholar

Peng Wang Skills & Research Interests

Knowledge Graph

Large Language Model

Deep Learning

Top articles of Peng Wang

Unify Named Entity Recognition Scenarios via Contrastive Real-Time Updating Prototype

Proceedings of the AAAI Conference on Artificial Intelligence

2024/3/24

Peng Wang
Peng Wang

H-Index: 13

Guozheng Li
Guozheng Li

H-Index: 3

Unlocking Instructive In-Context Learning with Tabular Prompting for Relational Triple Extraction

arXiv preprint arXiv:2402.13741

2024/2/21

MDM: Meta diffusion model for hard-constrained text generation

Knowledge-Based Systems

2024/1/11

Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors

arXiv preprint arXiv:2404.17807

2024/4/27

Boosting LLMS with Ontology-Aware Prompt for Ner Data Augmentation

2024/4/14

Rui Qi
Rui Qi

H-Index: 3

Peng Wang
Peng Wang

H-Index: 13

AdaptiveUKE: Towards adaptive unsupervised keyphrase extraction with gated topic modeling

Expert Systems with Applications

2024/4/6

ConsistNER: Towards Instructive NER Demonstrations for LLMs with the Consistency of Ontology and Context

Proceedings of the AAAI Conference on Artificial Intelligence

2024/3/24

Towards continual knowledge graph embedding via incremental distillation

Proceedings of the AAAI Conference on Artificial Intelligence

2024/3/24

Ontofact: Unveiling fantastic fact-skeleton of llms via ontology-driven reinforcement learning

Proceedings of the AAAI Conference on Artificial Intelligence

2024/3/24

Prompt-based event relation identification with Constrained Prefix ATTention mechanism

Knowledge-Based Systems

2023/12/3

ASKRL: An Aligned-Spatial Knowledge Representation Learning Framework for Open-World Knowledge Graph

2023/10/27

Peng Wang
Peng Wang

H-Index: 13

Jiajun Liu
Jiajun Liu

H-Index: 1

Revisiting large language models as zero-shot relation extractors

arXiv preprint arXiv:2310.05028

2023/10/8

Guozheng Li
Guozheng Li

H-Index: 3

Peng Wang
Peng Wang

H-Index: 13

Reasoning through memorization: Nearest neighbor knowledge graph embeddings

2023/10/8

Discriminative Question Answering via Cascade Prompt Learning and Sentence Level Attention Mechanism

IEICE TRANSACTIONS on Information and Systems

2023/9/1

Xinyu Fan
Xinyu Fan

H-Index: 17

Peng Wang
Peng Wang

H-Index: 13

PasCore: a chinese overlapping relation extraction model based on global pointer annotation strategy

2023/8/19

Towards incremental NER data augmentation via syntactic-aware insertion transformer

2023/8/19

Automatic skill-oriented question generation and recommendation for intelligent job interviews

ACM Transactions on Information Systems (TOIS)

2023

Easyedit: An easy-to-use knowledge editing framework for large language models

arXiv preprint arXiv:2308.07269

2023/8/14

Learned adapters are better than manually designed adapters

2023/7

See List of Professors in Peng Wang University(Southeast University)