1 citations · 1 across the 5 of their papers we have counts for
5 papers
Generate to Accelerate: Improved Reranking via LLM-Generated Pivot Documents
Nilanjan Sinhababu, Soumedhik Bharati, Debasis Ganguly +1
Common approaches to reduce the computational overhead of reranking models include identifying a candidate set of documents for reranking or constructing comparison graphs to minim…
Modeling Ranking Properties with In-Context Learning
Nilanjan Sinhababu, Andrew Parry, Debasis Ganguly +1
While standard IR models are primarily designed to optimize relevance, real-world search often needs to balance additional objectives such as diversity and fairness. These objectiv…
Few-shot Prompting for Pairwise Ranking: An Effective Non-Parametric Retrieval Model
Nilanjan Sinhababu, Andrew Parry, Debasis Ganguly +2
A supervised ranking model, despite its advantage of being effective, usually involves complex processing - typically multiple stages of task-specific pre-training and fine-tuning.…
Medical Information Retrieval and Interpretation: A Question-Answer based Interaction Model
Nilanjan Sinhababu, Rahul Saxena, Monalisa Sarma +1
The Internet has become a very powerful platform where diverse medical information are expressed daily. Recently, a huge growth is seen in searches like symptoms, diseases, medicin…
Computational Intelligence Approach to Improve the Classification Accuracy of Brain Neoplasm in MRI Data
Nilanjan Sinhababu, Monalisa Sarma, Debasis Samanta
Automatic detection of brain neoplasm in Magnetic Resonance Imaging (MRI) is gaining importance in many medical diagnostic applications. This report presents two improvements for b…