4 papers
PARAM-1 BharatGen 2.9B Model
Kundeshwar Pundalik, Piyush Sawarkar, Nihar Sahoo +19
Large Language Models (LLMs) have emerged as powerful general-purpose reasoning systems, yet their development remains dominated by English-centric data, architectures, and optimiz…
MorphTok: Morphologically Grounded Tokenization for Indian Languages
Maharaj Brahma, N J Karthika, Atul Singh +5
Tokenization is a crucial step in NLP, especially with the rise of large language models (LLMs), impacting downstream performance, computational cost, and efficiency. Existing LLMs…
Towards More Relevant Product Search Ranking Via Large Language Models: An Empirical Study
Qi Liu, Atul Singh, Jingbo Liu +2
Training Learning-to-Rank models for e-commerce product search ranking can be challenging due to the lack of a gold standard of ranking relevance. In this paper, we decompose ranki…
Long or Short or Both? An Exploration on Lookback Time Windows of Behavioral Features in Product Search Ranking
Qi Liu, Atul Singh, Jingbo Liu +3
Customer shopping behavioral features are core to product search ranking models in eCommerce. In this paper, we investigate the effect of lookback time windows when aggregating the…