5 citations · 7 across the 7 of their papers we have counts for
7 papers
Distill and Align Decomposition for Enhanced Claim Verification
Jabez Magomere, Elena Kochkina, Samuel Mensah +6
Complex claim verification requires decomposing sentences into verifiable subclaims, yet existing methods struggle to align decomposition quality with verification performance. We…
Trading Syntax Trees for Wordpieces: Target-oriented Opinion Words Extraction with Wordpieces and Aspect Enhancement
Samuel Mensah, Kai Sun, Nikolaos Aletras
State-of-the-art target-oriented opinion word extraction (TOWE) models typically use BERT-based text encoders that operate on the word level, along with graph convolutional network…
Self-training through Classifier Disagreement for Cross-Domain Opinion Target Extraction
Kai Sun, Richong Zhang, Samuel Mensah +3
Opinion target extraction (OTE) or aspect extraction (AE) is a fundamental task in opinion mining that aims to extract the targets (or aspects) on which opinions have been expresse…
A Hierarchical N-Gram Framework for Zero-Shot Link Prediction
Mingchen Li, Junfan Chen, Samuel Mensah +3
Due to the incompleteness of knowledge graphs (KGs), zero-shot link prediction (ZSLP) which aims to predict unobserved relations in KGs has attracted recent interest from researche…
An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction
Samuel Mensah, Kai Sun, Nikolaos Aletras
Target-oriented opinion words extraction (TOWE) (Fan et al., 2019b) is a new subtask of target-oriented sentiment analysis that aims to extract opinion words for a given aspect in…
Towards the Localisation of Lesions in Diabetic Retinopathy
Samuel Ofosu Mensah, Bubacarr Bah, Willie Brink
Convolutional Neural Networks (CNNs) have successfully been used to classify diabetic retinopathy (DR) fundus images in recent times. However, deeper representations in CNNs may ca…
Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations
Kai Sun, Richong Zhang, Samuel Mensah +2
The idea of using multi-task learning approaches to address the joint extraction of entity and relation is motivated by the relatedness between the entity recognition task and the…