3 papers
cs.CL2026
When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering
Mahdi Astaraki, Mohammad Arshi Saloot, Ali Shiraee Kasmaee +2
Retrieval-Augmented Generation (RAG) extends large language models (LLMs) beyond parametric knowledge, yet it is unclear when iterative retrieval-reasoning loops meaningfully outpe…
cs.IR2025
ChEmbed: Enhancing Chemical Literature Search Through Domain-Specific Text Embeddings
Ali Shiraee Kasmaee, Mohammad Khodadad, Mehdi Astaraki +4
Retrieval-Augmented Generation (RAG) systems in chemistry heavily depend on accurate and relevant retrieval of chemical literature. However, general-purpose text embedding models f…
cs.CL2025
ChemTEB: Chemical Text Embedding Benchmark, an Overview of Embedding Models Performance & Efficiency on a Specific Domain
Ali Shiraee Kasmaee, Mohammad Khodadad, Mohammad Arshi Saloot +4
Recent advancements in language models have started a new era of superior information retrieval and content generation, with embedding models playing an important role in optimizin…