Muhammad Hannan Akram


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2025

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The Chunking Paradigm: Recursive Semantic for RAG Optimization
Seemab Latif | Huma Ameer | Muhammad Hannan Akram | Mehwish Fatima
Proceedings of the 8th International Conference on Natural Language and Speech Processing (ICNLSP-2025)

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NUST Omega at RIRAG 2025: Investigating Context-aware Retrieval and Answer Generations-Lessons and Challenges
Huma Ameer | Muhammad Hannan Akram | Seemab Latif | Mehwish Fatima
Proceedings of the 1st Regulatory NLP Workshop (RegNLP 2025)

NUST Omega participates in Regulatory Information Retrieval and Answer Generation (RIRAG) Shared Task. Regulatory documents poses unique challenges in retrieving and generating precise and relevant answers due to their inherent complexities. We explore the task by proposing a progressive retrieval pipeline and investigate its performance with multiple variants. Some variants include different embeddings to explore their effects on the retrieval score. Some variants examine the inclusion of keyword-driven query matching technique. After exploring such variations, we include topic modeling in our pipeline to investigate its impact on the performance. We also study the performance of various prompt techniques with our proposed pipeline. With empirical experiments, we find some strengths and limitations in the proposed pipeline. These findings will help the research community by offering valuable insights to make advancements in tackling this complex task.