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cs.IR2026
LURE-RAG: Lightweight Utility-driven Reranking for Efficient RAG
Manish Chandra, Debasis Ganguly, Iadh Ounis
Most conventional Retrieval-Augmented Generation (RAG) pipelines rely on relevance-based retrieval, which often misaligns with utility -- that is, whether the retrieved passages ac…
cs.IR2024
"In-Context Learning" or: How I learned to stop worrying and love "Applied Information Retrieval"
Andrew Parry, Debasis Ganguly, Manish Chandra
With the increasing ability of large language models (LLMs), in-context learning (ICL) has evolved as a new paradigm for natural language processing (NLP), where instead of fine-tu…