activity
20242026
collaborators

10 papers

cs.CL2026

Multi-Agent LLMs for Generating Research Limitations

Ibrahim Al Azher, Zhishuai Guo, Hamed Alhoori

Identifying and articulating limitations is essential for transparent and rigorous scientific research. However, zero-shot large language models (LLMs) approach often produce super…

cs.CL2025

Generation, Evaluation, and Explanation of Novelists' Styles with Single-Token Prompts

Mosab Rezaei, Mina Rajaei Moghadam, Abdul Rahman Shaikh +2

Recent advances in large language models have created new opportunities for stylometry, the study of writing styles and authorship. Two challenges, however, remain central: trainin…

cs.DL2025

BAGELS: Benchmarking the Automated Generation and Extraction of Limitations from Scholarly Text

Ibrahim Al Azher, Miftahul Jannat Mokarrama, Zhishuai Guo +2

In scientific research, ``limitations'' refer to the shortcomings, constraints, or weaknesses of a study. A transparent reporting of such limitations can enhance the quality and re…

cs.CL2025

FutureGen: A RAG-based Approach to Generate the Future Work of Scientific Article

Ibrahim Al Azher, Miftahul Jannat Mokarrama, Zhishuai Guo +2

The Future Work section of a scientific article outlines potential research directions by identifying gaps and limitations of a current study. This section serves as a valuable res…

cs.HC2025

iTrace : Interactive Tracing of Cross-View Data Relationships

Abdul Rahman Shaikh, Maoyuan Sun, Xingchen Liu +3

Exploring data relations across multiple views has been a common task in many domains such as bioinformatics, cybersecurity, and healthcare. To support this, various techniques (e.…

cs.CL2025

LimTopic: LLM-based Topic Modeling and Text Summarization for Analyzing Scientific Articles limitations

Ibrahim Al Azhar, Venkata Devesh Reddy, Hamed Alhoori +1

The limitations sections of scientific articles play a crucial role in highlighting the boundaries and shortcomings of research, thereby guiding future studies and improving resear…