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20242026
most citedOn the Limitations of Large Language Models (LLMs): False Attribution

1 citations · 2 across the 8 of their papers we have counts for

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cs.CL2026

Author Representation Strategies for Zero-Shot Authorship Attribution: A Comparative Study of LLM-Based and Embedding-Based Approaches

Nudrat Habib, Tosin Adewumi, Sana Sabah Al-Azzawi +2

Authorship Attribution (AA) requires capturing fine-grained stylistic characteristics, making it particularly challenging in zero-shot (ZS) settings where no task-specific supervis…

cs.CL2026

Computational Analysis of Semantic Connections Between Herman Melville Reading and Writing

Nudrat Habib, Elisa Barney Smith, Steven Olsen Smith

This study investigates the potential influence of Herman Melville reading on his own writings through computational semantic similarity analysis. Using documented records of books…

cs.CL2025

From the Rock Floor to the Cloud: A Systematic Survey of State-of-the-Art NLP in Battery Life Cycle

Tosin Adewumi, Martin Karlsson, Marcus Liwicki +5

This work presents a systematic review of the application of natural language processing (NLP) along the entire battery life cycle, instead of the review of one stage or method, an…

cs.CL2025

Trends and Challenges in Authorship Analysis: A Review of ML, DL, and LLM Approaches

Nudrat Habib, Tosin Adewumi, Marcus Liwicki +1

Authorship analysis plays an important role in diverse domains, including forensic linguistics, academia, cybersecurity, and digital content authentication. This paper presents a s…

cs.CL2024

Urdu Dependency Parsing and Treebank Development: A Syntactic and Morphological Perspective

Nudrat Habib

Parsing is the process of analyzing a sentence's syntactic structure by breaking it down into its grammatical components. and is critical for various linguistic applications. Urdu…

cs.CL2024★ 1 cited

On the Limitations of Large Language Models (LLMs): False Attribution

Tosin Adewumi, Nudrat Habib, Lama Alkhaled +1

In this work, we introduce a new hallucination metric - Simple Hallucination Index (SHI) and provide insight into one important limitation of the parametric knowledge of large lang…