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cs.CL2025
"Lost-in-the-Later": Framework for Quantifying Contextual Grounding in Large Language Models
Yufei Tao, Adam Hiatt, Rahul Seetharaman +1
Large language models are capable of leveraging both contextual and parametric knowledge but how they prioritize and integrate these sources remains underexplored. We introduce CoP…
cs.CL2024
Quantifying reliance on external information over parametric knowledge during Retrieval Augmented Generation (RAG) using mechanistic analysis
Reshmi Ghosh, Rahul Seetharaman, Hitesh Wadhwa +6
Retrieval Augmented Generation (RAG) is a widely used approach for leveraging external context in several natural language applications such as question answering and information r…