12 citations · 13 across the 3 of their papers we have counts for
3 papers
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★ 12 cited
"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…
cs.CL2024★ 1 cited
One size doesn't fit all: Predicting the Number of Examples for In-Context Learning
Manish Chandra, Debasis Ganguly, Iadh Ounis
In-context learning (ICL) refers to the process of adding a small number of localized examples from a training set of labelled data to an LLM's prompt with an objective to effectiv…