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 deep learning for named entity recognition
Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …
belonging to predefined semantic types such as person, location, organization etc. NER …
Tweeteval: Unified benchmark and comparative evaluation for tweet classification
F Barbieri, J Camacho-Collados, L Neves… - arXiv preprint arXiv …, 2020 - arxiv.org
The experimental landscape in natural language processing for social media is too
fragmented. Each year, new shared tasks and datasets are proposed, ranging from classics …
fragmented. Each year, new shared tasks and datasets are proposed, ranging from classics …
The hateful memes challenge: Detecting hate speech in multimodal memes
This work proposes a new challenge set for multimodal classification, focusing on detecting
hate speech in multimodal memes. It is constructed such that unimodal models struggle and …
hate speech in multimodal memes. It is constructed such that unimodal models struggle and …
Hybrid transformer with multi-level fusion for multimodal knowledge graph completion
Multimodal Knowledge Graphs (MKGs), which organize visual-text factual knowledge, have
recently been successfully applied to tasks such as information retrieval, question …
recently been successfully applied to tasks such as information retrieval, question …
Bi-bimodal modality fusion for correlation-controlled multimodal sentiment analysis
Multimodal sentiment analysis aims to extract and integrate semantic information collected
from multiple modalities to recognize the expressed emotions and sentiment in multimodal …
from multiple modalities to recognize the expressed emotions and sentiment in multimodal …
[HTML][HTML] Few-shot learning for medical text: A review of advances, trends, and opportunities
Background: Few-shot learning (FSL) is a class of machine learning methods that require
small numbers of labeled instances for training. With many medical topics having limited …
small numbers of labeled instances for training. With many medical topics having limited …
Good visual guidance makes a better extractor: Hierarchical visual prefix for multimodal entity and relation extraction
Multimodal named entity recognition and relation extraction (MNER and MRE) is a
fundamental and crucial branch in information extraction. However, existing approaches for …
fundamental and crucial branch in information extraction. However, existing approaches for …
Cross-modal multitask transformer for end-to-end multimodal aspect-based sentiment analysis
As an emerging task in opinion mining, End-to-End Multimodal Aspect-Based Sentiment
Analysis (MABSA) aims to extract all the aspect-sentiment pairs mentioned in a pair of …
Analysis (MABSA) aims to extract all the aspect-sentiment pairs mentioned in a pair of …
Multi-modal graph fusion for named entity recognition with targeted visual guidance
Multi-modal named entity recognition (MNER) aims to discover named entities in free text
and classify them into pre-defined types with images. However, dominant MNER models do …
and classify them into pre-defined types with images. However, dominant MNER models do …