Large language models for generative information extraction: A survey
Abstract Information Extraction (IE) aims to extract structural knowledge from plain natural
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …
A survey on open Information Extraction from rule-based model to large language model
Abstract Open Information Extraction (OpenIE) represents a crucial NLP task aimed at
deriving structured information from unstructured text, unrestricted by relation type or …
deriving structured information from unstructured text, unrestricted by relation type or …
The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective
The rapid development of large language models (LLMs) has been witnessed in recent
years. Based on the powerful LLMs, multi-modal LLMs (MLLMs) extend the modality from …
years. Based on the powerful LLMs, multi-modal LLMs (MLLMs) extend the modality from …
Generative Multimodal Data Augmentation for Low-Resource Multimodal Named Entity Recognition
As an important task in multimodal information extraction, Multimodal Named Entity
Recognition (MNER) has recently attracted considerable attention. One key challenge of …
Recognition (MNER) has recently attracted considerable attention. One key challenge of …
Unlocking the Potential: A Comprehensive Systematic Review of ChatGPT in Natural Language Processing Tasks.
EA Alomari - CMES-Computer Modeling in Engineering & …, 2024 - search.ebscohost.com
Abstract As Natural Language Processing (NLP) continues to advance, driven by the
emergence of sophisticated large language models such as ChatGPT, there has been a …
emergence of sophisticated large language models such as ChatGPT, there has been a …
Multi-grained query-guided set prediction network for grounded multimodal named entity recognition
Grounded Multimodal Named Entity Recognition (GMNER) is an emerging information
extraction (IE) task, aiming to simultaneously extract entity spans, types, and corresponding …
extraction (IE) task, aiming to simultaneously extract entity spans, types, and corresponding …
[PDF][PDF] Open information extraction from 2007 to 2022–a survey
Open information extraction is an important NLP task that targets extracting structured
information from unstructured text without limitations on the relation type or the domain of the …
information from unstructured text without limitations on the relation type or the domain of the …
Advancing Grounded Multimodal Named Entity Recognition via LLM-Based Reformulation and Box-Based Segmentation
Grounded Multimodal Named Entity Recognition (GMNER) task aims to identify named
entities, entity types and their corresponding visual regions. GMNER task exhibits two …
entities, entity types and their corresponding visual regions. GMNER task exhibits two …
VP-MEL: Visual Prompts Guided Multimodal Entity Linking
H Mi, J Li, X Zhang, H Cheng, J Wang, D Sun… - arXiv preprint arXiv …, 2024 - arxiv.org
Multimodal Entity Linking (MEL) is extensively utilized in the domains of information retrieval.
However, existing MEL methods typically utilize mention words as mentions for retrieval …
However, existing MEL methods typically utilize mention words as mentions for retrieval …
[PDF][PDF] 多模态知识图谱构建技术及其在军事领域的应用综述.
姚奕， 陈朝阳， 杜晓明， 姚天磊， 李青尚… - Journal of Computer …, 2024 - lib.zjsru.edu.cn
随着数据资源类型的丰富与大模型技术的发展, 能够处理多源异构数据的多模态知识图谱(
multimodal knowledge graph, MMKG) 以出色的数据处理与管理能力而被广泛关注 …
multimodal knowledge graph, MMKG) 以出色的数据处理与管理能力而被广泛关注 …