2 citations · 4 across the 5 of their papers we have counts for
6 papers
Towards Explaining Query Expansion Performance in Information Retrieval
Sourav Saha, Aditya Dutta, Soumajit Pramanik +1
Query Expansion (QE) techniques have long been widely used in Information Retrieval (IR) to address the vocabulary mismatch problem. They remain relevant in modern retrieval system…
LiCQA : A Lightweight Complex Question Answering System
Sourav Saha, Dwaipayan Roy, Mandar Mitra
Over the last twenty years, significant progress has been made in designing and implementing Question Answering (QA) systems. However, addressing complex questions, the answers to…
LLMs as Assessors: Right for the Right Reason?
Sourav Saha, Mandar Mitra, Aditya Dutta
A good deal of recent research has focused on how Large Language Models (LLMs) may be used as judges in place of humans to evaluate the quality of the output produced by various te…
Combining Query Performance Predictors: A Reproducibility Study
Sourav Saha, Suchana Datta, Dwaipayan Roy +2
A large number of approaches to Query Performance Prediction (QPP) have been proposed over the last two decades. As early as 2009, Hauff et al. [28] explored whether different QPP…
ir_explain: a Python Library of Explainable IR Methods
Sourav Saha, Harsh Agarwal, V Venktesh +4
While recent advancements in Neural Ranking Models have resulted in significant improvements over traditional statistical retrieval models, it is generally acknowledged that the us…
Explainability of Text Processing and Retrieval Methods: A Survey
Sourav Saha, Debapriyo Majumdar, Mandar Mitra
Deep Learning and Machine Learning based models have become extremely popular in text processing and information retrieval. However, the non-linear structures present inside the ne…