8 citations · 11 across the 3 of their papers we have counts for
8 papers
ASTRA: Accurate and Scalable ANNS-based Training of Extreme Classifiers
Sonu Mehta, Jayashree Mohan, Nagarajan Natarajan +2
`Extreme Classification'' (or XC) is the task of annotating data points (queries) with relevant labels (documents), from an extremely large set of possible labels, arising in s…
CROSS-JEM: Accurate and Efficient Cross-encoders for Short-text Ranking Tasks
Bhawna Paliwal, Deepak Saini, Mudit Dhawan +6
Ranking a set of items based on their relevance to a given query is a core problem in search and recommendation. Transformer-based ranking models are the state-of-the-art approache…
Provably Robust DPO: Aligning Language Models with Noisy Feedback
Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan
Learning from preference-based feedback has recently gained traction as a promising approach to align language models with human interests. While these aligned generative models ha…
GAR-meets-RAG Paradigm for Zero-Shot Information Retrieval
Daman Arora, Anush Kini, Sayak Ray Chowdhury +3
Given a query and a document corpus, the information retrieval (IR) task is to output a ranked list of relevant documents. Combining large language models (LLMs) with embedding-bas…
Differentially Private Reward Estimation with Preference Feedback
Sayak Ray Chowdhury, Xingyu Zhou, Nagarajan Natarajan
Learning from preference-based feedback has recently gained considerable traction as a promising approach to align generative models with human interests. Instead of relying on num…
Frustrated with Code Quality Issues? LLMs can Help!
Nalin Wadhwa, Jui Pradhan, Atharv Sonwane +5
As software projects progress, quality of code assumes paramount importance as it affects reliability, maintainability and security of software. For this reason, static analysis to…