activity
20212025
most citedLLMs4OL: Large Language Models for Ontology Learning

10 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025★ 1 cited

Homa at SemEval-2025 Task 5: Aligning Librarian Records with OntoAligner for Subject Tagging

Hadi Bayrami Asl Tekanlou, Jafar Razmara, Mahsa Sanaei +2

This paper presents our system, Homa, for SemEval-2025 Task 5: Subject Tagging, which focuses on automatically assigning subject labels to technical records from TIBKAT using the G…

cs.IR2024

Towards Effective Authorship Attribution: Integrating Class-Incremental Learning

Mostafa Rahgouy, Hamed Babaei Giglou, Mehnaz Tabassum +5

AA is the process of attributing an unidentified document to its true author from a predefined group of known candidates, each possessing multiple samples. The nature of AA necessi…

cs.AI2023★ 10 cited

LLMs4OL: Large Language Models for Ontology Learning

Hamed Babaei Giglou, Jennifer D'Souza, Sören Auer

We propose the LLMs4OL approach, which utilizes Large Language Models (LLMs) for Ontology Learning (OL). LLMs have shown significant advancements in natural language processing, de…

cs.CL2021

ViraPart: A Text Refinement Framework for Automatic Speech Recognition and Natural Language Processing Tasks in Persian

Narges Farokhshad, Milad Molazadeh, Saman Jamalabbasi +2

The Persian language is an inflectional subject-object-verb language. This fact makes Persian a more uncertain language. However, using techniques such as Zero-Width Non-Joiner (ZW…

cs.CL2021

UoT-UWF-PartAI at SemEval-2021 Task 5: Self Attention Based Bi-GRU with Multi-Embedding Representation for Toxicity Highlighter

Hamed Babaei Giglou, Taher Rahgooy, Mostafa Rahgouy +1

Toxic Spans Detection(TSD) task is defined as highlighting spans that make a text toxic. Many works have been done to classify a given comment or document as toxic or non-toxic. Ho…