2 citations · 2 across the 8 of their papers we have counts for
8 papers
NCL-UoR at SemEval-2026 Task 5: Embedding-Based Methods, Fine-Tuning, and LLMs for Word Sense Plausibility Rating
Tong Wu, Thanet Markchom, Huizhi Liang
Word sense plausibility rating requires predicting the human-perceived plausibility of a given word sense on a 1-5 scale in the context of short narrative stories containing ambigu…
Understanding Multi-Agent Reasoning with Large Language Models for Cartoon VQA
Tong Wu, Thanet Markchom
Visual Question Answering (VQA) for stylised cartoon imagery presents challenges, such as interpreting exaggerated visual abstraction and narrative-driven context, which are not ad…
Art2Music: Generating Music for Art Images with Multi-modal Feeling Alignment
Jiaying Hong, Ting Zhu, Thanet Markchom +1
With the rise of AI-generated content (AIGC), generating perceptually natural and feeling-aligned music from multimodal inputs has become a central challenge. Existing approaches o…
NCL-UoR at SemEval-2025 Task 3: Detecting Multilingual Hallucination and Related Observable Overgeneration Text Spans with Modified RefChecker and Modified SeflCheckGPT
Jiaying Hong, Thanet Markchom, Jianfei Xu +2
SemEval-2025 Task 3 (Mu-SHROOM) focuses on detecting hallucinations in content generated by various large language models (LLMs) across multiple languages. This task involves not o…
UoR-NCL at SemEval-2025 Task 1: Using Generative LLMs and CLIP Models for Multilingual Multimodal Idiomaticity Representation
Thanet Markchom, Tong Wu, Liting Huang +1
SemEval-2025 Task 1 focuses on ranking images based on their alignment with a given nominal compound that may carry idiomatic meaning in both English and Brazilian Portuguese. To a…
CRRG-CLIP: Automatic Generation of Chest Radiology Reports and Classification of Chest Radiographs
Jianfei Xu, Thanet Markchom, Huizhi Liang
The complexity of stacked imaging and the massive number of radiographs make writing radiology reports complex and inefficient. Even highly experienced radiologists struggle to mai…
Review of Explainable Graph-Based Recommender Systems
Thanet Markchom, Huizhi Liang, James Ferryman
Explainability of recommender systems has become essential to ensure users' trust and satisfaction. Various types of explainable recommender systems have been proposed including ex…
Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection
Feng Xiong, Thanet Markchom, Ziwei Zheng +3
SemEval-2024 Task 8 introduces the challenge of identifying machine-generated texts from diverse Large Language Models (LLMs) in various languages and domains. The task comprises t…